Add strong scaling GPU actions table

.gitignore

@@ -1,2 +1,4 @@
 *.swp
 outdir
+venv
+dump

experiments/.gitignore

@@ -1,2 +1,10 @@
 venv
 .ipynb_checkpoints
+logs
+__pycache__
+generated/*
+batch/measurements/strong/*
+configs/measurements/strong/*
+*.dat
+*.db
+eval/generated/*

experiments/Makefile

@@ -0,0 +1,27 @@
+VARIED_FILLINGS_IS := $(shell seq -w 0 10 100)
+VARIED_FILLINGS_JOBS := $(addprefix generated/varied-fillings-, $(addsuffix .json, ${VARIED_FILLINGS_IS}))
+
+all: varied-fillings strong
+
+varied-fillings: ${VARIED_FILLINGS_JOBS}
+
+strong:
+	python scripts/gen/strong.py
+
+clean-strong:
+	rm -f batch/measurements/strong/*
+	rm -f configs/measurements/strong/spheroid*.json
+
+clean:
+	rm -f generated/*
+
+clean-logs:
+	rm -f logs/*
+
+clean-outs:
+	rm -rf /p/scratch/cellsinsilico/paul/nastja-out/*
+
+generated/varied-fillings-%.json: scripts/gen/varied_fillings.py templates/varied-fillings.json
+	python scripts/gen/varied_fillings.py $* > $@
+
+.PHONY: varied-fillings strong clean clean-logs clean-outs

experiments/batch/build-cuda

@@ -5,11 +5,11 @@
 #SBATCH --account=hkf6
 #SBATCH --partition=develbooster
 #SBATCH --nodes=1
-#SBATCH --ntasks-per-node=1
+#SBATCH --ntasks=1
 #SBATCH --cpus-per-task=48
 #SBATCH --time=01:00:00
-#SBATCH --output=build-cuda-%j.out
+#SBATCH --output=logs/build-cuda-%j.log
-#SBATCH --error=build-cuda-%j.err
+#SBATCH --error=logs/build-cuda-%j.log
 
 SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
 

experiments/batch/build-nocuda

@@ -5,11 +5,11 @@
 #SBATCH --account=hkf6
 #SBATCH --partition=develbooster
 #SBATCH --nodes=1
-#SBATCH --ntasks-per-node=1
+#SBATCH --ntasks=1
 #SBATCH --cpus-per-task=48
 #SBATCH --time=01:00:00
-#SBATCH --output=build-nocuda-%j.out
+#SBATCH --output=logs/build-nocuda-%j.log
-#SBATCH --error=build-nocuda-%j.err
+#SBATCH --error=logs/build-nocuda-%j.log
 
 SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
 

experiments/batch/cuda

@@ -0,0 +1,32 @@
+#!/usr/bin/env bash
+
+#SBATCH --job-name=cuda
+# Forschergruppe Schug
+#SBATCH --account=hkf6
+# 48 Cores, 512GiB RAM, 4x NVIDIA A100 GPUs
+#SBATCH --partition=booster
+# Right now we're using a single node
+#SBATCH --nodes=1
+# Number of MPI processes
+# TODO: Change the config and set to this the maximum of 48
+#SBATCH --ntasks=16
+#SBATCH --cpus-per-task=1
+# For now, we are using a single GPU only
+#SBATCH --gres=gpu:1
+#SBATCH --time=01:00:00
+#SBATCH --output=logs/cuda-%j.log
+#SBATCH --error=logs/cuda-%j.log
+
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR=/p/scratch/cellsinsilico/paul/nastja-out/cuda
+
+mkdir -p "${OUTPUT_DIR}"
+source "${SOURCE_DIR}/activate-nastja-modules"
+
+# This is actually the default behavior for a single task anyways
+# However I'm leaving this here for documentation reasons
+export CUDA_VISIBLE_DEVICES=0
+
+srun --unbuffered "${SOURCE_DIR}/nastja/build-cuda/nastja" \
+  -c "${SOURCE_DIR}/ma/experiments/configs/genesis.json" \
+  -o "${OUTPUT_DIR}"

experiments/batch/cuda-singleblock

@@ -0,0 +1,30 @@
+#!/usr/bin/env bash
+
+#SBATCH --job-name=cuda-singleblock
+# Forschergruppe Schug
+#SBATCH --account=hkf6
+# 48 Cores, 512GiB RAM, 4x NVIDIA A100 GPUs
+#SBATCH --partition=booster
+# Right now we're using a single node
+#SBATCH --nodes=1
+# Number of MPI processes
+#SBATCH --ntasks=1
+# For now, we are using a single GPU only
+#SBATCH --gres=gpu:1
+#SBATCH --time=01:00:00
+#SBATCH --output=logs/cuda-singleblock-%j.log
+#SBATCH --error=logs/cuda-singleblock-%j.log
+
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR=/p/scratch/cellsinsilico/paul/nastja-out/cuda-singleblock
+
+mkdir -p "${OUTPUT_DIR}"
+source "${SOURCE_DIR}/activate-nastja-modules"
+
+# This is actually the default behavior for a single task anyways
+# However I'm leaving this here for documentation reasons
+export CUDA_VISIBLE_DEVICES=0
+
+srun --unbuffered "${SOURCE_DIR}/nastja/build-cuda/nastja" \
+  -c "${SOURCE_DIR}/ma/experiments/configs/genesis-singleblock.json" \
+  -o "${OUTPUT_DIR}"

experiments/batch/ecm-debug

@@ -0,0 +1,29 @@
+#!/usr/bin/env bash
+
+#SBATCH --job-name=ecm-debug
+# Forschergruppe Schug
+#SBATCH --account=hkf6
+# 48 Cores, 512GiB RAM, 4x NVIDIA A100 GPUs
+#SBATCH --partition=booster
+#SBATCH --nodes=1
+#SBATCH --ntasks=1
+#SBATCH --cpus-per-task=1
+# For now, we are using a single GPU only
+#SBATCH --gres=gpu:1
+#SBATCH --time=00:10:00
+#SBATCH --output=logs/ecm-debug-%j.log
+#SBATCH --error=logs/ecm-debug-%j.log
+
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR=/p/scratch/cellsinsilico/paul/nastja-out/ecm-debug
+
+mkdir -p "${OUTPUT_DIR}"
+source "${SOURCE_DIR}/activate-nastja-modules"
+
+# This is actually the default behavior for a single task anyways
+# However I'm leaving this here for documentation reasons
+export CUDA_VISIBLE_DEVICES=0
+
+srun "${SOURCE_DIR}/nastja/build-cuda/nastja" \
+  -c "${SOURCE_DIR}/ma/experiments/configs/ecm-debug.json" \
+  -o "${OUTPUT_DIR}"

experiments/batch/julian-animation

@@ -0,0 +1,24 @@
+#!/usr/bin/env bash
+
+#SBATCH --job-name=julian-animation
+#SBATCH --account=hkf6
+#SBATCH --partition=booster
+#SBATCH --nodes=8
+#SBATCH --ntasks=32
+# Counted per node
+#SBATCH --gres=gpu:4
+#SBATCH --time=03:30:00
+#SBATCH --output=logs/%x-%A_%a.log
+#SBATCH --error=logs/%x-%A_%a.log
+
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR="/p/scratch/cellsinsilico/paul/nastja-out/${SLURM_JOB_NAME}"
+
+echo "outdir is ${OUTPUT_DIR}"
+
+mkdir -p "${OUTPUT_DIR}"
+source "${SOURCE_DIR}/activate-nastja-modules"
+
+srun --unbuffered "${SOURCE_DIR}/nastja/build-cuda/nastja" \
+  -c "${SOURCE_DIR}/ma/experiments/configs/${SLURM_JOB_NAME}.json" \
+  -o "${OUTPUT_DIR}"

experiments/batch/measurements/strong/.gitkeep

@@ -0,0 +1 @@
+Generated by scripts/gen/strong.py

experiments/batch/nocuda

@@ -9,11 +9,11 @@
 #SBATCH --nodes=1
 # Number of MPI processes
 # TODO: Change the config and set to this the maximum of 48
-#SBATCH --ntasks-per-node=16
+#SBATCH --ntasks=16
 #SBATCH --cpus-per-task=1
 #SBATCH --time=01:00:00
-#SBATCH --output=nocuda-%j.out
+#SBATCH --output=logs/nocuda-%j.log
-#SBATCH --error=nocuda-%j.err
+#SBATCH --error=logs/nocuda-%j.log
 
 SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
 OUTPUT_DIR=/p/scratch/cellsinsilico/paul/nastja-out/nocuda
@@ -21,6 +21,6 @@ OUTPUT_DIR=/p/scratch/cellsinsilico/paul/nastja-out/nocuda
 mkdir -p "${OUTPUT_DIR}"
 source "${SOURCE_DIR}/activate-nastja-modules"
 
-srun "${SOURCE_DIR}/nastja/build-nocuda/nastja" \
+srun --unbuffered "${SOURCE_DIR}/nastja/build-nocuda/nastja" \
   -c "${SOURCE_DIR}/ma/experiments/configs/genesis.json" \
   -o "${OUTPUT_DIR}"

experiments/batch/nocuda-noecm

@@ -0,0 +1,26 @@
+#!/usr/bin/env bash
+
+#SBATCH --job-name=nocuda-noecm
+# Forschergruppe Schug
+#SBATCH --account=hkf6
+# 48 Cores, 512GiB RAM, 4x NVIDIA A100 GPUs
+#SBATCH --partition=booster
+# Right now we're using a single node
+#SBATCH --nodes=1
+# Number of MPI processes
+# TODO: Change the config and set to this the maximum of 48
+#SBATCH --ntasks-per-node=16
+#SBATCH --cpus-per-task=1
+#SBATCH --time=01:00:00
+#SBATCH --output=logs/nocuda-noecm-%j.log
+#SBATCH --error=logs/nocuda-noecm-%j.log
+
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR=/p/scratch/cellsinsilico/paul/nastja-out/nocuda-noecm
+
+mkdir -p "${OUTPUT_DIR}"
+source "${SOURCE_DIR}/activate-nastja-modules"
+
+srun "${SOURCE_DIR}/nastja/build-nocuda/nastja" \
+  -c "${SOURCE_DIR}/ma/experiments/configs/genesis-noecm.json" \
+  -o "${OUTPUT_DIR}"

experiments/batch/nocuda-singleblock

@@ -0,0 +1,24 @@
+#!/usr/bin/env bash
+
+#SBATCH --job-name=nocuda-singleblock
+# Forschergruppe Schug
+#SBATCH --account=hkf6
+# 48 Cores, 512GiB RAM, 4x NVIDIA A100 GPUs
+#SBATCH --partition=booster
+# Right now we're using a single node
+#SBATCH --nodes=1
+# Number of MPI processes
+#SBATCH --ntasks=1
+#SBATCH --time=06:00:00
+#SBATCH --output=logs/nocuda-singleblock-%j.log
+#SBATCH --error=logs/nocuda-singleblock-%j.log
+
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR=/p/scratch/cellsinsilico/paul/nastja-out/nocuda-singleblock
+
+mkdir -p "${OUTPUT_DIR}"
+source "${SOURCE_DIR}/activate-nastja-modules"
+
+srun --unbuffered "${SOURCE_DIR}/nastja/build-nocuda/nastja" \
+  -c "${SOURCE_DIR}/ma/experiments/configs/genesis-singleblock.json" \
+  -o "${OUTPUT_DIR}"

experiments/batch/varied-fillings-nocuda

@@ -0,0 +1,26 @@
+#!/usr/bin/env bash
+
+#SBATCH --job-name=varied-fillings-nocuda
+# Forschergruppe Schug
+#SBATCH --account=hkf6
+# 48 Cores, 512GiB RAM, 4x NVIDIA A100 GPUs
+#SBATCH --partition=booster
+# Right now we're using a single node
+#SBATCH --nodes=1
+#SBATCH --ntasks=48
+#SBATCH --cpus-per-task=1
+#SBATCH --time=02:00:00
+#SBATCH --output=logs/varied-fillings-nocuda-%A-%3a.log
+#SBATCH --error=logs/varied-fillings-nocuda-%A-%3a.log
+#SBATCH --array=0-100:10
+
+IDENT=$(printf "%03d" "${SLURM_ARRAY_TASK_ID}")
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR="/p/scratch/cellsinsilico/paul/nastja-out/varied-fillings-nocuda-${IDENT}"
+
+mkdir -p "${OUTPUT_DIR}"
+source "${SOURCE_DIR}/activate-nastja-modules"
+
+srun "${SOURCE_DIR}/nastja/build-nocuda/nastja" \
+  -c "${SOURCE_DIR}/ma/experiments/generated/varied-fillings-${IDENT}.json" \
+  -o "${OUTPUT_DIR}"

experiments/configs/comp.json

@@ -0,0 +1,102 @@
+{
+  "#Testing": {
+    "description": "Small experiment for comparing CPU and GPU implementations"
+  },
+  "Application": "Cells",
+  "Geometry": {
+    "blocksize": [10, 10, 10],
+    "blockcount": [1, 1, 1]
+  },
+  "Settings": {
+    "timesteps": 4,
+    "randomseed": 42
+  },
+  "Filling": {
+    "cells": [
+      {
+        "_comment": "This is for the dynamic ECM",
+        "shape": "cube",
+        "box": [
+          [0, 0, 0],
+          [9, 9, 9]
+        ],
+        "value": 0,
+        "celltype": 0
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [4, 4, 4],
+          [7, 7, 7]
+        ],
+        "celltype": 2
+      }
+    ]
+  },
+  "CellsInSilico": {
+    "liquid": 1,
+    "adhesion": {
+      "matrix": [
+        [0, 0,  0, 0],
+        [0, 0,  0, 0],
+        [0, 0, 10, 5],
+        [0, 0,  5, 5]
+      ]
+    },
+    "temperature": 15,
+    "volume": {
+      "default": [0, 0, 64, 64],
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "surface": {
+      "default": [0, 0, 80, 80],
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "cleaner": {
+      "killdistance": 100
+    },
+    "checkerboard": "00",
+    "energyfunctions": ["Volume00", "Surface00", "Adhesion00", "DynamicECM00"],
+    "centerofmass": {
+      "steps": 10
+    },
+    "dynamicecm": {
+      "enabled": true,
+      "stepsPerMcs": 10,
+      "pushSteps": 10,
+      "pushWeight": 2,
+      "ecmCellID": 0,
+      "deltat": 0.1,
+      "eta": 0.25,
+      "k0": 0.1,
+      "k1": 0.1,
+      "c": 4,
+      "alpha": 2,
+      "d": 0.3,
+      "phi": 1,
+      "lambda": 50
+    }
+  },
+  "Writers": {
+    "ParallelVTK_Cells": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "UInt32",
+      "field": "cells",
+      "steps": 1
+    },
+    "ParallelVTK_Displacement": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "Float32",
+      "field": "dynamicecm",
+      "components": [0, 1, 2],
+      "steps": 1
+    }
+  },
+  "WriteActions": ["ParallelVTK_Cells", "ParallelVTK_Displacement"]
+}

experiments/configs/ecm-debug.json

@@ -0,0 +1,88 @@
+{
+  "#Testing": {
+    "description": "Just dynamic ECM for debugging"
+  },
+  "Application": "Cells",
+  "Geometry": {
+    "blocksize": [5, 5, 5],
+    "blockcount": [1, 1, 1]
+  },
+  "Settings": {
+    "timesteps": 10,
+    "randomseed": 42
+  },
+  "Filling": {
+    "cells": [
+      {
+        "_comment": "This is for the dynamic ECM",
+        "shape": "cube",
+        "box": [
+          [0, 0, 0],
+          [4, 4, 4]
+        ],
+        "value": 0,
+        "celltype": 0
+      }
+    ]
+  },
+  "CellsInSilico": {
+    "liquid": 1,
+    "adhesion": {
+      "matrix": [
+        [0, 0,  0, 0],
+        [0, 0,  0, 0],
+        [0, 0, 10, 5],
+        [0, 0,  5, 5]
+      ]
+    },
+    "temperature": 15,
+    "volume": {
+      "default": [0, 0, 7000, 1000],
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "surface": {
+      "default": [0, 0, 2500, 1000],
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "checkerboard": "00",
+    "energyfunctions": ["Volume00", "Surface00", "Adhesion00", "DynamicECM00"],
+    "dynamicecm": {
+      "enabled": true,
+      "stepsPerMcs": 1,
+      "pushSteps": 1,
+      "pushWeight": 2,
+      "ecmCellID": 0,
+      "deltat": 0.1,
+      "eta": 0.25,
+      "k0": 0.1,
+      "k1": 0.1,
+      "c": 4,
+      "alpha": 2,
+      "d": 0.3,
+      "phi": 1,
+      "lambda": 50
+    }
+  },
+  "Writers": {
+    "ParallelVTK_Cells": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "UInt32",
+      "field": "cells",
+      "steps": 1
+    },
+    "ParallelVTK_Displacement": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "Float32",
+      "field": "dynamicecm",
+      "components": [0, 1, 2],
+      "steps": 1
+    }
+  },
+  "WriteActions": ["ParallelVTK_Cells", "ParallelVTK_Displacement"]
+}

experiments/configs/genesis-noecm.json

@@ -0,0 +1,109 @@
+{
+  "#Testing": {
+    "description": "Cellular Potts Model with dynamic ECM"
+  },
+  "Application": "Cells",
+  "Geometry": {
+    "blocksize": [20, 40, 40],
+    "blockcount": [4, 2, 2]
+  },
+  "Settings": {
+    "timesteps": 250,
+    "randomseed": 42
+  },
+  "Filling": {
+    "cells": [
+      {
+        "_comment": "This is for the dynamic ECM",
+        "shape": "cube",
+        "box": [
+          [0, 0, 0],
+          [79, 79, 79]
+        ],
+        "value": 0,
+        "celltype": 0
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [41, 35, 10],
+          [45, 39, 15]
+        ],
+        "celltype": 2
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [40, 15, 14],
+          [47, 22, 20]
+        ],
+        "celltype": 2
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [40, 20, 20],
+          [47, 27, 26]
+        ],
+        "celltype": 3
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [38, 20, 60],
+          [45, 27, 66]
+        ],
+        "celltype": 3
+      }
+    ]
+  },
+  "CellsInSilico": {
+    "liquid": 1,
+    "adhesion": {
+      "matrix": [
+        [0, 0,  0, 0],
+        [0, 0,  0, 0],
+        [0, 0, 10, 5],
+        [0, 0,  5, 5]
+      ]
+    },
+    "temperature": 15,
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 2000
+      },
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 800
+      },
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "cleaner": {
+      "killdistance": 100
+    },
+    "checkerboard": "00",
+    "energyfunctions": ["Volume00", "Surface00", "Adhesion00"],
+    "centerofmass": {
+      "steps": 10
+    }
+  },
+  "Writers": {
+    "ParallelVTK_Cells": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "UInt32",
+      "field": "cells",
+      "steps": 1
+    }
+  },
+  "WriteActions": ["ParallelVTK_Cells"]
+}

experiments/configs/genesis-singleblock.json

@@ -0,0 +1,131 @@
+{
+  "#Testing": {
+    "description": "Cellular Potts Model with dynamic ECM"
+  },
+  "Application": "Cells",
+  "Geometry": {
+    "blocksize": [80, 80, 80],
+    "blockcount": [1, 1, 1]
+  },
+  "Settings": {
+    "timesteps": 250,
+    "randomseed": 42
+  },
+  "Filling": {
+    "cells": [
+      {
+        "_comment": "This is for the dynamic ECM",
+        "shape": "cube",
+        "box": [
+          [0, 0, 0],
+          [79, 79, 79]
+        ],
+        "value": 0,
+        "celltype": 0
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [41, 35, 10],
+          [45, 39, 15]
+        ],
+        "celltype": 2
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [40, 15, 14],
+          [47, 22, 20]
+        ],
+        "celltype": 2
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [40, 20, 20],
+          [47, 27, 26]
+        ],
+        "celltype": 3
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [38, 20, 60],
+          [45, 27, 66]
+        ],
+        "celltype": 3
+      }
+    ]
+  },
+  "CellsInSilico": {
+    "liquid": 1,
+    "adhesion": {
+      "matrix": [
+        [0, 0,  0, 0],
+        [0, 0,  0, 0],
+        [0, 0, 10, 5],
+        [0, 0,  5, 5]
+      ]
+    },
+    "temperature": 15,
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 2000
+      },
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 800
+      },
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "cleaner": {
+      "killdistance": 100
+    },
+    "checkerboard": "00",
+    "energyfunctions": ["Volume00", "Surface00", "Adhesion00", "DynamicECM00"],
+    "centerofmass": {
+      "steps": 10
+    },
+    "dynamicecm": {
+      "enabled": true,
+      "stepsPerMcs": 100,
+      "pushSteps": 10,
+      "pushWeight": 2,
+      "ecmCellID": 0,
+      "deltat": 0.1,
+      "eta": 0.25,
+      "k0": 0.1,
+      "k1": 0.1,
+      "c": 4,
+      "alpha": 2,
+      "d": 0.3,
+      "phi": 1
+    }
+  },
+  "Writers": {
+    "ParallelVTK_Cells": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "UInt32",
+      "field": "cells",
+      "steps": 1
+    },
+    "ParallelVTK_Displacement": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "Float32",
+      "field": "dynamicecm",
+      "components": [0, 1, 2],
+      "steps": 1
+    }
+  },
+  "WriteActions": ["ParallelVTK_Cells", "ParallelVTK_Displacement"]
+}

experiments/configs/julian-animation.json

@@ -0,0 +1,330 @@
+{
+  "Comments": [
+    "Celltype         Usage",
+    "0                Dynamic ECM",
+    "1-5             Not Used",
+    "6               Liquid  ",
+    "7               Apoptotic cell Type ",
+    "8               Basic Non Dividing Cell type (surrounding)",
+    "9               Cancer"
+  ],
+  "Application": "Cells",
+  "CellsInSilico": {
+    "ecmdegradation": {
+      "enabled": "false",
+      "steps": 99999,
+      "stochastic": "true",
+      "probability": 0.5
+    },
+    "energyfunctions": [
+      "Volume00",
+      "Surface01",
+      "Motility00",
+      "Adhesion01",
+      "DynamicECM00"
+    ],
+    "liquid": 6,
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 500
+      },
+      "lambda": [
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        7.5,
+        7.5,
+        7.5
+      ],
+      "sizechange": [
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        -0.05,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0
+      ]
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 400
+      },
+      "lambda": [
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        5.625,
+        5.625,
+        1
+      ],
+      "sizechange": [
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        -0.05,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0
+      ]
+    },
+    "adhesion": {
+      "matrix": [
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0
+        ],
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          450
+        ],
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0
+        ],
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0
+        ],
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0
+        ],
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0
+        ],
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0
+        ],
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0
+        ],
+        [
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0
+        ],
+        [
+          0,
+          450,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          50
+        ]
+      ]
+    },
+    "temperature": 50,
+    "division": {
+      "enabled": "true",
+      "condition": [
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "( volume >= 0.9 * volume0 )  & ( rnd() <= 0.00001 ) & generation < 1"
+      ]
+    },
+    "centerofmass": {
+      "steps": 1
+    },
+    "signaling": {
+      "enabled": false
+    },
+    "orientation": {
+      "enabled": true,
+      "motility": "persistentRandomWalk",
+      "persistenceMagnitude": 0.0,
+      "recalculationtime": 200,
+      "motilityamount": [
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        0
+      ]
+    },
+    "visitor": {
+      "stepwidth": 10,
+      "checkerboard": "01"
+    },
+    "cleaner": {
+      "killDistance": 20
+    },
+    "dynamicecm": {
+      "enabled": true,
+      "stepsPerMcs": 100,
+      "pushSteps": 10,
+      "pushWeight": 2,
+      "ecmCellID": 0,
+      "deltat": 0.1,
+      "eta": 0.25,
+      "k0": 0.1,
+      "k1": 0.1,
+      "c": 4,
+      "alpha": 2,
+      "d": 0.3,
+      "phi": 1
+    }
+  },
+  "Geometry": {
+    "blockcount": [
+      2,
+      4,
+      4
+    ],
+    "blocksize": [
+      200,
+      100,
+      100
+    ]
+  },
+  "Settings": {
+    "randomseed": 0,
+    "timesteps": 5000,
+    "statusoutput": 1
+  },
+  "WriteActions": ["ParallelVTK_Cells", "ParallelVTK_Displacement"],
+  "Writers": {
+    "CellInfo": {
+      "field": "",
+      "groupsize": 0,
+      "steps": 1,
+      "writer": "CellInfo"
+    },
+    "ParallelVTK_Cells": {
+      "field": "cells",
+      "outputtype": "UInt32",
+      "printhints": false,
+      "steps": 100,
+      "writer": "ParallelVtkImage"
+    },
+    "ParallelVTK_Displacement": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "Float32",
+      "field": "dynamicecm",
+      "components": [
+        0,
+        1,
+        2
+      ],
+      "steps": 100
+    }
+  },
+  "Include": "measurements/strong/config_filling_1.json"
+}

experiments/configs/measurements/.gitkeep

@@ -0,0 +1 @@
+Autogenerated by scripts/gen/strong.py

experiments/configs/measurements/strong/config_filling_1.json

@@ -0,0 +1,44 @@
+{
+    "DefineFunctions": [
+        "r_angle()=360*rnd()",
+        "r_size()=400*rnd()"
+    ],
+    "Filling": {
+        "cells": [
+            {
+                "_comment": "This is for the dynamic ECM",
+                "shape": "cube",
+                "box": [
+                  [0, 0, 0],
+                  [399, 399, 401]
+                ],
+                "value": 0,
+                "celltype": 0
+            },
+            {
+                "shape": "sphere",
+                "pattern": "voronoi",
+                "count": 5500,
+                "radius": 75,
+                "center": [
+                    200,
+                    200,
+                    200
+                ],
+                "box": [
+                    [
+                        110,
+                        110,
+                        110
+                    ],
+                    [
+                        290,
+                        290,
+                        290
+                    ]
+                ],
+                "celltype": 9
+            }
+        ]
+    }
+}

experiments/configs/medium.json

@@ -0,0 +1,110 @@
+{
+  "#Testing": {
+    "description": "Cellular Potts Model with dynamic ECM"
+  },
+  "Application": "Cells",
+  "Geometry": {
+    "blocksize": [180, 180, 180],
+    "blockcount": [1, 1, 1]
+  },
+  "Settings": {
+    "timesteps": 100,
+    "randomseed": 42,
+    "statusoutput": 1
+  },
+  "Filling": {
+    "cells": [
+      {
+        "_comment": "This is for the dynamic ECM",
+        "shape": "cube",
+        "box": [
+          [0, 0, 0],
+          [179, 179, 179]
+        ],
+        "value": 0,
+        "celltype": 0
+      },
+      {
+        "shape": "cube",
+        "pattern": "voronoi",
+        "box": [
+            [20, 20, 20],
+            [159, 159, 159]
+        ],
+        "count": 1500,
+        "celltype": [0, 0, 750, 750]
+      }
+    ]
+  },
+  "CellsInSilico": {
+    "liquid": 1,
+    "adhesion": {
+      "matrix": [
+        [0, 0,  0, 0],
+        [0, 0,  0, 0],
+        [0, 0, 10, 5],
+        [0, 0,  5, 5]
+      ]
+    },
+    "temperature": 15,
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 2000
+      },
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 800
+      },
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "cleaner": {
+      "killdistance": 100
+    },
+    "checkerboard": "00",
+    "energyfunctions": ["Volume00", "Surface00", "Adhesion00", "DynamicECM00"],
+    "centerofmass": {
+      "steps": 10
+    },
+    "dynamicecm": {
+      "enabled": true,
+      "stepsPerMcs": 100,
+      "pushSteps": 10,
+      "pushWeight": 2,
+      "ecmCellID": 0,
+      "deltat": 0.1,
+      "eta": 0.25,
+      "k0": 0.1,
+      "k1": 0.1,
+      "c": 4,
+      "alpha": 2,
+      "d": 0.3,
+      "phi": 1
+    }
+  },
+  "Writers": {
+    "ParallelVTK_Cells": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "UInt32",
+      "field": "cells",
+      "steps": 10
+    },
+    "ParallelVTK_Displacement": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "Float32",
+      "field": "dynamicecm",
+      "components": [0, 1, 2],
+      "steps": 10
+    }
+  },
+  "WriteActions": ["ParallelVTK_Cells", "ParallelVTK_Displacement"]
+}

experiments/configs/mini.json

@@ -4,11 +4,11 @@
   },
   "Application": "Cells",
   "Geometry": {
-    "blocksize": [20, 20, 20],
+    "blocksize": [40, 20, 20],
-    "blockcount": [2, 1, 1]
+    "blockcount": [1, 1, 1]
   },
   "Settings": {
-    "timesteps": 500,
+    "timesteps": 200,
     "randomseed": 42
   },
   "Filling": {
@@ -76,7 +76,7 @@
     },
     "dynamicecm": {
       "enabled": true,
-      "stepsPerMcs": 100,
+      "stepsPerMcs": 10,
       "pushSteps": 10,
       "pushWeight": 2,
       "ecmCellID": 0,

experiments/configs/small.json

@@ -1,21 +1,40 @@
 {
   "#Testing": {
-    "description": "Cellular Potts Model with dynamic ECM"
+    "description": "Minimal config for debugging CUDA code"
   },
   "Application": "Cells",
   "Geometry": {
-    "blocksize": [15, 15, 15],
+    "blocksize": [5, 5, 5],
     "blockcount": [1, 1, 1]
   },
   "Settings": {
-    "timesteps": 100,
+    "timesteps": 3,
     "randomseed": 42
   },
   "Filling": {
     "cells": [
+      {
+        "_comment": "This is for the dynamic ECM",
+        "shape": "cube",
+        "box": [
+          [0, 0, 0],
+          [4, 2, 4]
+        ],
+        "value": 0,
+        "celltype": 0
+      },
+      {
+        "shape": "cube",
+        "box": [
+          [1, 1, 1],
+          [3, 3, 3]
+        ],
+        "celltype": 2
+      }
     ]
   },
   "CellsInSilico": {
+    "liquid": 1,
     "adhesion": {
       "matrix": [
         [0, 0, 0, 0],
@@ -53,12 +72,15 @@
       "killdistance": 100
     },
     "checkerboard": "00",
-    "energyfunctions": ["Volume00", "Surface00", "Adhesion00", "Potential00"],
+    "energyfunctions": ["Volume00", "Surface00", "Adhesion00", "Potential00", "DynamicECM00"],
     "centerofmass": {
       "steps": 10
     },
     "dynamicecm": {
       "enabled": true,
+      "ecmCellID": 0,
+      "stepsPerMcs": 1,
+      "pushSteps": 1,
       "deltat": 0.1,
       "eta": 0.5
     }
@@ -67,7 +89,7 @@
     "ParallelVTK_Displacement": {
       "writer": "ParallelVtkImage",
       "outputtype": "Float32",
-      "field": "dynamicecm_displacement",
+      "field": "dynamicecm",
       "steps": 1
     }
   },

experiments/configs/spheroid/config.json

@@ -0,0 +1,116 @@
+{
+    "Comments": ["Celltype         Usage", "0                Not Used", "1-5             Solids for blood vessels / ECM", "6               Liquid  ", "7               Apoptotic cell Type ", "8               Basic Non Dividing Cell type (surrounding)", "9               Cancer"],
+    "Application": "Cells",
+    "CellsInSilico": {
+        "ecmdegradation": {
+            "enabled": "false",
+            "steps": 99999,
+            "stochastic": "true",
+            "probability": 0.5
+        },
+        "energyfunctions": ["Volume00", "Surface01", "Motility00", "Adhesion01", "DynamicECM00"],
+        "liquid": 6,
+        "volume": {
+            "default": {
+                "storage": "const",
+                "value": 500
+            },
+            "lambda": [0, 0, 0, 0, 0, 0, 0, 7.5, 7.5, 7.5],
+            "sizechange": [0, 0, 0, 0, 0, 0, 0, -0.05, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "surface": {
+            "default": {
+                "storage": "const",
+                "value": 400
+            },
+            "lambda": [0, 0, 0, 0, 0, 0, 0, 5.625, 5.625, 1],
+            "sizechange": [0, 0, 0, 0, 0, 0, 0, -0.05, 0, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "adhesion": {
+            "matrix": [
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 450],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 450, 0, 0, 0, 0, 0, 0, 0, 50]
+            ]
+        },
+        "temperature": 50,
+        "division": {
+            "enabled": "true",
+            "condition": ["", "", "", "", "", "", "", "", "", "( volume >= 0.9 * volume0 )  & ( rnd() <= 0.00001 ) & generation < 1"]
+        },
+        "centerofmass": {
+            "steps": 1
+        },
+        "signaling": {
+            "enabled": false
+        },
+        "orientation": {
+            "enabled": true,
+            "motility": "persistentRandomWalk",
+            "persistenceMagnitude": 0.0,
+            "recalculationtime": 200,
+            "motilityamount": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "visitor": {
+            "stepwidth": 10,
+            "checkerboard": "01"
+        },
+        "cleaner": {
+            "killDistance": 20
+        },
+        "dynamicecm": {
+            "enabled": true,
+            "stepsPerMcs": 100,
+            "pushSteps": 10,
+            "pushWeight": 2,
+            "ecmCellID": 0,
+            "deltat": 0.1,
+            "eta": 0.25,
+            "k0": 0.1,
+            "k1": 0.1,
+            "c": 4,
+            "alpha": 2,
+            "d": 0.3,
+            "phi": 1
+        }
+    },
+    "Geometry": {
+        "blockcount": [8, 8, 6],
+        "blocksize": [50, 50, 67]
+    },
+    "Settings": {
+        "randomseed": 0,
+        "timesteps": 100
+    },
+    "WriteActions": ["CellInfo"],
+    "Writers": {
+        "CellInfo": {
+            "field": "",
+            "groupsize": 0,
+            "steps": 1,
+            "writer": "CellInfo"
+        },
+        "ParallelVTK_Cells": {
+            "field": "cells",
+            "outputtype": "UInt32",
+            "printhints": false,
+            "steps": 1,
+            "writer": "ParallelVtkImage"
+        },
+        "ParallelVTK_Displacement": {
+            "writer": "ParallelVtkImage",
+            "outputtype": "Float32",
+            "field": "dynamicecm",
+            "components": [0, 1, 2],
+            "steps": 1
+        }
+    },
+    "Include": "config_filling_1.json"
+}

experiments/configs/spheroid/config_filling_1.json

@@ -0,0 +1,44 @@
+{
+    "DefineFunctions": [
+        "r_angle()=360*rnd()",
+        "r_size()=400*rnd()"
+    ],
+    "Filling": {
+        "cells": [
+            {
+                "_comment": "This is for the dynamic ECM",
+                "shape": "cube",
+                "box": [
+                  [0, 0, 0],
+                  [399, 399, 401]
+                ],
+                "value": 0,
+                "celltype": 0
+            },
+            {
+                "shape": "sphere",
+                "pattern": "voronoi",
+                "count": 5500,
+                "radius": 75,
+                "center": [
+                    200,
+                    200,
+                    200
+                ],
+                "box": [
+                    [
+                        110,
+                        110,
+                        110
+                    ],
+                    [
+                        290,
+                        290,
+                        290
+                    ]
+                ],
+                "celltype": 9
+            }
+        ]
+    }
+}

experiments/eval/Makefile

@@ -0,0 +1,13 @@
+generate-batch-strong-cpu:
+	python scripts/substitute.py strong-batch.j2 < strong-cpu.json
+
+generate-batch-strong-gpu:
+	python scripts/substitute.py strong-batch.j2 < strong-gpu.json
+
+generate-batch-strong-booster:
+	python scripts/substitute.py strong-batch.j2 < strong-booster.json
+
+clean-logs:
+	rm logs/*
+
+.PHONY: generate-batch-strong-cpu clean-logs

experiments/eval/data/actions-normalized.csv

@@ -0,0 +1,4 @@
+label,BC:cells,BC:dynamicecm,Sweep:Cells,Sweep:DynamicECM,Sweep:DynamicECMDampers,Filling,Other
+CPU,0.04629667717328299,3.88243023434036,0.002164069189058585,82.18255346583861,13.842310640806883,0.005797982839735358,0.03844692981207934
+GPU,0.034897486509106485,41.227398706349675,13.180664898871365,22.432483220415783,19.749714111977486,1.9939606413394697,1.3808809345371023
+Booster,0.09128030041871667,42.736382370072874,12.260298369798207,22.36492489089858,16.070196185259338,4.364304866307413,2.1126130172448816

experiments/eval/data/actions.csv

@@ -0,0 +1,4 @@
+label,BC:cells,BC:dynamicecm,Sweep:Cells,Sweep:DynamicECM,Sweep:DynamicECMDampers,Other
+CPU,0.9047934333333334,75.87579921250001,0.04229322083333333,1606.12465625,270.5255006333333,0.8646950250000001
+GPU,0.11372260000000001,134.35027680000002,42.952648800000006,73.102122,64.3596162,10.9978052
+Booster,0.155221,72.67267939999999,20.848482800000003,38.0312728,27.327165999999995,11.013917200000002

experiments/eval/data/strong-booster.tsv

@@ -0,0 +1,9 @@
+label	nodes	tasks	mean_time	std_time	speedup	speedup_std	speedup_error
+1	1	1	161.08257980000002	1.0725827874500897	1.0	0.0066585895804611986	0.004614167168572558
+1	1	2	109.2771463	1.3498701967829918	1.474073813730255	0.018208823861030076	0.012618071172974463
+1	1	4	94.5763083	2.921107861707173	1.7032022363258181	0.052605536545441436	0.03645377698685362
+2	2	8	75.06436665	5.345617315509918	2.145926049720424	0.15281950626022228	0.10589851499069955
+4	4	16	42.842002025	1.5314070839490197	3.759921856733072	0.13440013758310768	0.09313454370387199
+8	8	32	16.40522446875	4.395440141154071	9.818980539208297	2.6307924825691393	1.823046180232846
+16	16	64	9.361684956249999	5.010216046116417	17.206579857449583	9.208671612370724	6.381283859970849
+32	32	128	5.214438346875	0.113661681579046	30.891645290338204	0.6733604113945479	0.4666149588180552

experiments/eval/data/strong-cpu.tsv

@@ -0,0 +1,10 @@
+label	nodes	tasks	mean_time	std_time	speedup	speedup_std	speedup_error
+1	1	48	1953.3832839708334	14.087268287606769	1.0	0.007211727674340593	0.004711662080569187
+2	2	96	1046.3540047312501	6.0880471399828595	1.866847429396085	0.010861959816590314	0.007096480413505672
+4	4	192	566.0709002166666	5.005298021298787	3.4507749527897755	0.030512356378918384	0.019934739500893344
+8	8	384	318.1225953708333	9.706195475255436	6.1403475024896865	0.18734731205020752	0.12240024387280224
+16	16	768	178.56471887994792	9.393026972005948	10.939357428631386	0.5754422263707719	0.375955587895571
+32	32	1536	99.82801128216144	1.4413062581268035	19.56748670921274	0.28251330150299214	0.18457535698195485
+64	64	3072	55.75610567220052	1.0303316198245824	35.034428255357376	0.6474103379133267	0.42297475410337343
+128	128	6144	31.589132888118492	0.32226687791817415	61.83719226764697	0.6308523555205254	0.41215687227340997
+256	256	12288	19.11704500200738	0.18528928846832715	102.18018965617955	0.9903672160087601	0.6470399144590566

experiments/eval/data/strong-gpu-actions.csv

@@ -0,0 +1,9 @@
+label,BC:cells,BC:dynamicecm,Sweep:Cells,Sweep:DynamicECM,Sweep:DynamicECMDampers,Filling,Other
+1,0.034897486509106485,41.227398706349675,13.180664898871365,22.432483220415783,19.749714111977486,1.9939606413394697,1.3808809345371023
+2,0.7137918070198439,50.7137377526309,8.923981074147767,19.35772833011394,17.571497161475467,1.320924803923136,1.3983390706889622
+4,0.6647403410134337,58.291944402330074,7.087118055335309,16.67352093599457,15.236952119238136,1.092645293437499,0.953078852650984
+8,0.6788278363464717,65.05900206274784,5.2089254465999275,14.249993130938188,13.176763096049008,0.7851584656500297,0.8413299616685318
+16,1.441574901760373,61.1245906198054,4.832237599492141,16.029377636605524,14.996293924006913,0.716990077435801,0.858935240893841
+32,3.3736940900007966,47.94830950907802,5.622259685491874,21.238716402604393,19.97281149065964,0.8196124452570666,1.0245963769081996
+64,6.284545018581091,45.28808866195176,4.502683326147901,21.66574860147326,20.522789117514915,0.6460791296539419,1.0900661446771265
+128,11.788574344478201,40.04977497065291,3.2677482351392375,22.1995263401806,21.209134936528987,0.4598839494487746,1.0253572235712836

experiments/eval/data/strong-gpu.tsv

@@ -0,0 +1,9 @@
+label	nodes	tasks	mean_time	std_time	speedup	speedup_std	speedup_error
+1	1	1	316.56674059999995	1.3298279828832311	1.0	0.004200782370133899	0.002910993666206366
+1	1	2	239.7297573	1.3705192585818793	1.3205150005797797	0.007549297425250635	0.00523139621453709
+1	1	4	150.86725470000002	1.463195211854327	2.098313124537819	0.020350616990413285	0.014102258089746373
+2	2	8	103.758313	1.3959932139830615	3.051001230137579	0.041049019495199714	0.028445519245192213
+4	4	16	56.423368849999996	0.8293394846143929	5.610560784514376	0.08246688711191473	0.057146637198176795
+8	8	32	24.168551143749998	0.5503559531334744	13.09829202078025	0.29826872726631265	0.20668968287257275
+16	16	64	15.05716248125	0.04648043269670786	21.024329185144023	0.06490066896072916	0.044973869063161365
+32	32	128	9.9111531140625	0.08848604506395903	31.940455056721632	0.28516203039001964	0.19760720531719309

experiments/eval/data/weak-booster.tsv

@@ -0,0 +1,9 @@
+nodes	tasks	mean_time	std_time	efficiency	efficiency_error
+1	1	41.98463099999999	1.4067920862965122	1.0	0.023219381860496473
+1	2	49.85189340000001	1.7669363566083227	0.8421872899214694	0.020685165974491628
+1	4	59.9694977	2.209151778903949	0.7000997608822725	0.01787171173813342
+2	8	72.810012625	0.5538313058789631	0.5766326565034021	0.003039461920431096
+4	16	84.718001525	5.20969191162485	0.4955809892140865	0.021118450727088397
+8	32	87.22569569999999	1.7018797711775082	0.4813332890390463	0.0065079080866405825
+16	64	85.36740952500001	1.0197522041876155	0.49181099946232654	0.004071100890302765
+32	128	87.5995021046875	0.8707125543332932	0.47927933368645675	0.003301208459097849

experiments/eval/data/weak-cpu.tsv

@@ -0,0 +1,10 @@
+nodes	tasks	mean_time	std_time	efficiency	efficiency_error
+1	48	234.09125610833334	4.9756238110995765	1.0	0.013886639526655382
+2	96	234.09269640000002	1.9886350551995884	0.9999938473447108	0.005550081636855162
+4	192	239.06532950520833	1.8931447841474947	0.9791936647310181	0.005066063671757703
+8	384	241.32357499479167	0.977728668984766	0.9700306160033705	0.0025676679349660694
+16	768	260.8008324059896	12.802824235961744	0.8975863073317291	0.028787758154736998
+32	1536	266.59983470546877	13.970338204797093	0.8780622702446538	0.03006125980502309
+64	3072	281.61153985800786	25.95560834859075	0.8312559074332151	0.05005532970709546
+128	6144	293.4177162058594	10.8076489888669	0.7978088683101088	0.019198998510810975
+256	12288	310.9775802693196	14.459893325743863	0.7527592693518308	0.022867934404056486

experiments/eval/data/weak-gpu.tsv

@@ -0,0 +1,9 @@
+nodes	tasks	mean_time	std_time	efficiency	efficiency_error
+1	1	60.658062599999994	1.8711952545625232	1.0	0.021376748626269895
+1	2	80.6903592	1.1554429061827625	0.751738661240214	0.007459415624087278
+1	4	89.01234124999999	1.3979557323025515	0.6814567704677693	0.00741639040919915
+2	8	101.357940575	4.784240687736861	0.5984539766286584	0.01957478845779047
+4	16	106.2530252	1.5044057675724636	0.5708831582519497	0.005601211794070455
+8	32	113.70197445	2.069642901549501	0.5334829310873062	0.006729131548114211
+16	64	119.22770070624999	0.7600051865549382	0.5087581345667959	0.00224730403456563
+32	128	121.8124414140625	0.5170666166834136	0.4979627852118346	0.0014647476739746731

experiments/eval/load-modules

@@ -0,0 +1 @@
+module load SciPy-Stack

experiments/eval/scripts/build-pgf-datafiles.py

@@ -0,0 +1,52 @@
+#!/usr/bin/env python
+
+
+import argparse
+import json
+import math
+
+
+def print_table(data, spec):
+    print("\t".join(column for column in spec.keys()))
+
+    for data_item in data:
+        values = []
+        for retrieve in spec.values():
+            raw_value = retrieve(data_item)
+            values.append(raw_value if isinstance(raw_value, str) else str(raw_value))
+        print("\t".join(values))
+
+
+if __name__ == "__main__":
+    p = argparse.ArgumentParser(description="Turn files generated by timing.py into pgf datafiles")
+    p.add_argument("timing_file")
+    p.add_argument("--weak", action="store_true")
+    args = p.parse_args()
+
+    with open(args.timing_file, "r", encoding="utf8") as f:
+        jobs = json.load(f)
+
+    if not args.weak:
+        scaling_spec = {
+            "label": lambda job: job["accounting"][0]["nodes"]["count"],
+            "nodes": lambda job: job["accounting"][0]["nodes"]["count"],
+            "tasks": lambda job: job["accounting"][0]["tasks"]["count"],
+            "mean_time": lambda job: job["means"]["TimeStep"],
+            "std_time": lambda job: job["stds"]["TimeStep"],
+            "speedup": lambda job: jobs[0]["means"]["TimeStep"] / job["means"]["TimeStep"],
+            # Standard deviation scaled to speedup
+            "speedup_std": lambda job: (jobs[0]["means"]["TimeStep"] / job["means"]["TimeStep"]) * (job["stds"]["TimeStep"] / job["means"]["TimeStep"]),
+            # 95% confidence interval
+            "speedup_error": lambda job: (jobs[0]["means"]["TimeStep"] / job["means"]["TimeStep"]) * (job["stds"]["TimeStep"] / job["means"]["TimeStep"]) / math.sqrt(len(jobs)) * 1.96,
+        }
+    else:
+        scaling_spec = {
+            "nodes": lambda job: job["accounting"][0]["nodes"]["count"],
+            "tasks": lambda job: job["accounting"][0]["tasks"]["count"],
+            "mean_time": lambda job: job["means"]["TimeStep"],
+            "std_time": lambda job: job["stds"]["TimeStep"],
+            "efficiency": lambda job: jobs[0]["means"]["TimeStep"] / job["means"]["TimeStep"],
+            "efficiency_error": lambda job: (jobs[0]["means"]["TimeStep"] / job["means"]["TimeStep"]) * (job["stds"]["TimeStep"] / job["means"]["TimeStep"]) / math.sqrt(len(jobs)) * 1.96,
+        }
+
+    print_table(jobs, scaling_spec)

experiments/eval/scripts/generate-strong-booster-configs.py

@@ -0,0 +1,34 @@
+#!/usr/bin/env python
+
+import copy
+import json
+
+from pathlib import Path
+
+SIZE = [384, 384, 384]
+
+with (Path(__file__).parent.parent / "templates" / "strong-booster.json").open(encoding="utf8") as f:
+    template = json.load(f)
+
+configs = [
+    [  1,  1,  1],
+    [  1,  1,  2],
+    [  1,  2,  2],
+    [  2,  2,  2],
+    [  2,  2,  4],
+    [  2,  4,  4],
+    [  4,  4,  4],
+    [  4,  4,  8],
+]
+
+out_path = Path(__file__).parent.parent / "generated" / "config"
+
+for c in configs:
+    nc = copy.deepcopy(template)
+    nc["Geometry"]["blockcount"] = c
+    nc["Geometry"]["blocksize"] = [bs // bc for bc, bs in zip(c, SIZE)]
+
+    nc_out_path = out_path / f"strong-booster-{c[0]:02}-{c[1]:02}-{c[2]:02}.json"
+    print(f"Dumping {(c[0] * c[1] * c[2])} to {nc_out_path}")
+    with nc_out_path.open("w", encoding="utf8") as f:
+        json.dump(nc, f)

experiments/eval/scripts/generate-strong-cpu-configs.py

@@ -0,0 +1,35 @@
+#!/usr/bin/env python
+
+import copy
+import json
+
+from pathlib import Path
+
+SIZE = [384, 384, 384]
+
+with (Path(__file__).parent.parent / "templates" / "strong-cpu.json").open(encoding="utf8") as f:
+    template = json.load(f)
+
+configs = [
+    [  4,  4,  3],
+    [  4,  4,  6],
+    [  4,  4, 12],
+    [  4,  8, 12],
+    [  8,  8, 12],
+    [  8,  8, 24],
+    [  8, 16, 24],
+    [ 16, 16, 24],
+    [ 16, 16, 48]
+]
+
+out_path = Path(__file__).parent.parent / "generated" / "config"
+
+for c in configs:
+    nc = copy.deepcopy(template)
+    nc["Geometry"]["blockcount"] = c
+    nc["Geometry"]["blocksize"] = [bs // bc for bc, bs in zip(c, SIZE)]
+
+    nc_out_path = out_path / f"strong-cpu-{c[0]:02}-{c[1]:02}-{c[2]:02}.json"
+    print(f"Dumping {(c[0] * c[1] * c[2]) // 48} to {nc_out_path}")
+    with nc_out_path.open("w", encoding="utf8") as f:
+        json.dump(nc, f)

experiments/eval/scripts/generate-strong-gpu-configs.py

@@ -0,0 +1,34 @@
+#!/usr/bin/env python
+
+import copy
+import json
+
+from pathlib import Path
+
+SIZE = [384, 384, 384]
+
+with (Path(__file__).parent.parent / "templates" / "strong-gpu.json").open(encoding="utf8") as f:
+    template = json.load(f)
+
+configs = [
+    [  1,  1,  1],
+    [  1,  1,  2],
+    [  1,  2,  2],
+    [  2,  2,  2],
+    [  2,  2,  4],
+    [  2,  4,  4],
+    [  4,  4,  4],
+    [  4,  4,  8],
+]
+
+out_path = Path(__file__).parent.parent / "generated" / "config"
+
+for c in configs:
+    nc = copy.deepcopy(template)
+    nc["Geometry"]["blockcount"] = c
+    nc["Geometry"]["blocksize"] = [bs // bc for bc, bs in zip(c, SIZE)]
+
+    nc_out_path = out_path / f"strong-gpu-{c[0]:02}-{c[1]:02}-{c[2]:02}.json"
+    print(f"Dumping {(c[0] * c[1] * c[2])} to {nc_out_path}")
+    with nc_out_path.open("w", encoding="utf8") as f:
+        json.dump(nc, f)

experiments/eval/scripts/generate-weak-configs.py

@@ -0,0 +1,207 @@
+#!/usr/bin/env python
+
+
+import jinja2
+import json
+import sys
+
+
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Tuple
+
+
+SIZE = (192, 192, 192)
+
+
+templates_env = jinja2.Environment(
+    loader=jinja2.FileSystemLoader(Path(__file__).parent.parent / "templates"),
+    autoescape=jinja2.select_autoescape()
+)
+        
+
+@dataclass
+class Experiment:
+    job_name: str
+    account: str
+    partition: str
+    nastja_binary_path: str
+    nodes: int
+    tasks: int
+    num_blocks: Tuple[int, int, int]
+    domain_scale: Tuple[int, int, int]
+    time: str = "00:15:00"
+    extra_sbatch_line: str = ""
+    logfile_path: str = "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/logs/%x-%A.%a"
+    config_path: str = "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/generated/config/${SLURM_JOB_NAME}.json"
+    output_dir_path: str = "/p/scratch/cellsinsilico/paul/nastja-out/${SLURM_JOB_NAME}-${SLURM_ARRAY_JOB_ID}.${SLURM_ARRAY_TASK_ID}"
+
+    def get_config(self):
+        with (Path(__file__).parent.parent / "templates" / "weak.json").open(encoding="utf8") as f:
+            config = json.load(f)
+
+        size = (
+            SIZE[0] * self.domain_scale[0],
+            SIZE[1] * self.domain_scale[1],
+            SIZE[2] * self.domain_scale[2],
+        )
+        blocksize = (
+            size[0] // self.num_blocks[0],
+            size[1] // self.num_blocks[1],
+            size[2] // self.num_blocks[2],
+        )
+        config["Geometry"] = {
+            "blockcount": list(self.num_blocks),
+            "blocksize": list(blocksize),
+        }
+
+        cells_filling = [{
+            "box": [
+                [0, 0, 0],
+                list(size)
+            ],
+            "celltype": 0,
+            "component": 0,
+            "pattern": "const",
+            "seed": 0,
+            "shape": "cube",
+            "value": 0,
+        }]
+        for z in range(self.domain_scale[2]):
+            for y in range(self.domain_scale[1]):
+                for x in range(self.domain_scale[0]):
+                    cx = x * SIZE[0] + SIZE[0] // 2
+                    cy = y * SIZE[1] + SIZE[1] // 2
+                    cz = z * SIZE[2] + SIZE[2] // 2
+                    cells_filling.append({
+                        "shape": "sphere",
+                        "pattern": "voronoi",
+                        "count": 715,
+                        "radius": 38,
+                        "center": [cx, cy, cz],
+                        "box": [
+                            [cx - 38, cy - 38, cz - 38],
+                            [cx + 38, cy + 38, cz + 38]
+                        ],
+                        "celltype": 9,
+                        "seed": 758960,
+                    })
+
+        config["Filling"]["cells"] = cells_filling
+
+        return config
+    
+    def write_batch_file(self, out_path: Path):
+        t = templates_env.get_template("strong-batch.j2")
+        t.stream(
+            name=self.job_name,
+            account=self.account,
+            partition=self.partition,
+            nodes=self.nodes,
+            tasks=self.tasks,
+            extra_sbatch_line=self.extra_sbatch_line,
+            time=self.time,
+            logfile_path=self.logfile_path,
+            nastja_binary_path=self.nastja_binary_path,
+            config_path=self.config_path,
+            output_dir_path=self.output_dir_path,
+        ).dump(str(out_path))
+
+
+def make_cpu_ex(x: int, y: int, z: int) -> Experiment:
+    num_blocks = x * y * z
+    assert num_blocks % 48 == 0
+    num_nodes = num_blocks // 48
+
+    assert x % 4 == 0
+    assert y % 4 == 0
+    assert z % 3 == 0
+
+    return Experiment(
+        job_name=f"weak-cpu-{x:02}-{y:02}-{z:02}",
+        account="cellsinsilico",
+        partition="batch",
+        nastja_binary_path="/p/project/cellsinsilico/paulslustigebude/nastja/build-nocuda/nastja",
+        nodes=num_nodes,
+        tasks=num_blocks,
+        num_blocks=(x, y, z),
+        domain_scale=(x // 4, y // 4, z // 3),
+    )
+
+
+def make_gpu_ex(x: int, y: int, z: int) -> Experiment:
+    num_blocks = x * y * z
+    gpus_per_node = num_blocks if num_blocks <= 4 else 4
+    num_nodes = 1 if num_blocks <= 4 else num_blocks // 4
+
+    return Experiment(
+        job_name=f"weak-gpu-{x:02}-{y:02}-{z:02}",
+        account="cellsinsilico",
+        partition="gpus",
+        extra_sbatch_line=f"#SBATCH --gres=gpu:{gpus_per_node}",
+        nastja_binary_path="/p/project/cellsinsilico/paulslustigebude/nastja/build-cuda/nastja",
+        nodes=num_nodes,
+        tasks=num_blocks,
+        num_blocks=(x, y, z),
+        domain_scale=(x, y, z),
+    )
+
+
+def make_booster_ex(x: int, y: int, z: int) -> Experiment:
+    num_blocks = x * y * z
+    gpus_per_node = num_blocks if num_blocks <= 4 else 4
+    num_nodes = 1 if num_blocks <= 4 else num_blocks // 4
+
+    return Experiment(
+        job_name=f"weak-booster-{x:02}-{y:02}-{z:02}",
+        account="hkf6",
+        partition="booster",
+        extra_sbatch_line=f"#SBATCH --gres=gpu:{gpus_per_node}",
+        nastja_binary_path="/p/project/cellsinsilico/paulslustigebude/nastja/build-cuda/nastja",
+        nodes=num_nodes,
+        tasks=num_blocks,
+        num_blocks=(x, y, z),
+        domain_scale=(x, y, z),
+    )
+
+
+experiments = [
+    make_cpu_ex(4, 4, 3),
+    make_cpu_ex(4, 4, 6),
+    make_cpu_ex(4, 4, 12),
+    make_cpu_ex(4, 8, 12),
+    make_cpu_ex(8, 8, 12),
+    make_cpu_ex(8, 8, 24),
+    make_cpu_ex(8, 16, 24),
+    make_cpu_ex(16, 16, 24),
+    make_cpu_ex(16, 16, 48),
+
+    make_gpu_ex(1, 1, 1),
+    make_gpu_ex(1, 1, 2),
+    make_gpu_ex(1, 2, 2),
+    make_gpu_ex(2, 2, 2),
+    make_gpu_ex(2, 2, 4),
+    make_gpu_ex(2, 4, 4),
+    make_gpu_ex(4, 4, 4),
+    make_gpu_ex(4, 4, 8),
+
+    make_booster_ex(1, 1, 1),
+    make_booster_ex(1, 1, 2),
+    make_booster_ex(1, 2, 2),
+    make_booster_ex(2, 2, 2),
+    make_booster_ex(2, 2, 4),
+    make_booster_ex(2, 4, 4),
+    make_booster_ex(4, 4, 4),
+    make_booster_ex(4, 4, 8),
+]
+
+if __name__ == "__main__":
+    outdir = Path(__file__).parent.parent / "generated"
+
+    for e in experiments:
+        print(f"Generating config for {e.job_name}", file=sys.stderr)
+        config_path = (outdir / "config" / e.job_name).with_suffix(".json")
+        with config_path.open("w", encoding="utf8") as f:
+            json.dump(e.get_config(), f, indent=2)
+        print(f"Generating batch file for {e.job_name}", file=sys.stderr)
+        e.write_batch_file(outdir / "batch" / e.job_name)

experiments/eval/scripts/make-latex-table.py

@@ -0,0 +1,24 @@
+#!/usr/bin/env python
+
+
+import argparse
+import pandas
+
+
+def show_seconds(s: float) -> str:
+    return f"{s:.2f}s"
+
+
+if __name__ == '__main__':
+    p = argparse.ArgumentParser(description="Make a latex table from a timings tsv")
+    p.add_argument("timingfile")
+    p.add_argument("--weak", action="store_true")
+    args = p.parse_args()
+
+    df = pandas.read_csv(args.timingfile, sep="\t")
+
+    for i in range(len(df)):
+        if not args.weak:
+            print(f"{df['nodes'][i]} & {df['tasks'][i]} & {show_seconds(df['mean_time'][i])} & {show_seconds(df['std_time'][i])} & {df['speedup'][i]:.02f} & {df['speedup_error'][i]:.02f} \\\\")
+        else:
+            print(f"{df['nodes'][i]} & {df['tasks'][i]} & {show_seconds(df['mean_time'][i])} & {show_seconds(df['std_time'][i])} & {df['efficiency'][i]:.02f} & {df['efficiency_error'][i]:.02f} \\\\")

experiments/eval/scripts/substitute.py

@@ -0,0 +1,21 @@
+#!/usr/bin/env python
+
+import jinja2
+import json
+import sys
+
+from pathlib import Path
+
+data = json.load(sys.stdin)
+
+templates_env = jinja2.Environment(
+    loader=jinja2.FileSystemLoader(Path(__file__).parent.parent / "templates"),
+    autoescape=jinja2.select_autoescape()
+)
+
+for possibly_incomplete_batch in data["batches"]:
+    batch = dict(list(data["common"].items()) + list(possibly_incomplete_batch.items()))
+    out_path = Path(__file__).parent.parent / "generated" / "batch" / batch["name"]
+    t = templates_env.get_template(sys.argv[1])
+    print(f"Dumping to {out_path}")
+    t.stream(**batch).dump(str(out_path))

experiments/eval/scripts/timing-actions.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python
+
+
+import argparse
+import sys
+
+
+import timing
+
+
+ignore = ["TimeStep"]
+
+
+if __name__ == "__main__":
+    p = argparse.ArgumentParser()
+    p.add_argument("jobs", nargs="+")
+    p.add_argument("--normalize", action="store_true")
+    p.add_argument("--extra-columns", nargs="*")
+    args = p.parse_args()
+
+    columns = [
+        "BC:cells",
+        "BC:dynamicecm",
+        "Sweep:Cells",
+        "Sweep:DynamicECM",
+        "Sweep:DynamicECMDampers",
+    ] + (args.extra_columns or [])
+
+    dfs = dict()
+    labels = []
+    for label, jobid in [jobarg.split(":") for jobarg in args.jobs]:
+        jobs, excluded_array_indices = timing.get_jobs(jobid)
+        df = timing.load_array_mean_timings(jobid, excluded_array_indices).mean()
+        dfs[label] = df
+        labels.extend(df.index)
+
+    labels = set(labels)
+    print(",".join(["label"] + columns + ["Other"]))
+
+    values_by_label = dict()
+    for label, df in dfs.items():
+        values = {"Other": 0}
+        for c in df.index:
+            if c in ignore:
+                continue
+            elif c not in columns:
+                values["Other"] += df[c]
+                print(f"Others+= {c}={df[c]}", file=sys.stderr)
+            else:
+                values[c] = df[c]
+        values_by_label[label] = values
+
+    if args.normalize:
+        print("Normalizing data to 100%...", file=sys.stderr)
+        for values in values_by_label.values():
+            row_length = sum(values.values())
+            for c in values.keys():
+                values[c] *= 100 / row_length
+
+    for label, values in values_by_label.items():
+        print(label + "," + ",".join(f"{values[c]}" for c in columns + ["Other"]))

experiments/eval/scripts/timing.py

@@ -0,0 +1,116 @@
+#!/usr/bin/env python
+
+
+import argparse
+import json
+import pandas
+import subprocess
+import sys
+
+
+from pathlib import Path
+
+
+def load_timing_file(timing_path: Path):
+    df = pandas.read_csv(timing_path, delim_whitespace=True)
+    headers = list(df["#Name"][1:])
+    times = list(df["TotalTime"][1:])
+    return pandas.DataFrame([times], columns=headers)
+
+
+def load_all_timings(outdir_path: Path):
+    timingdir_path = outdir_path / "timing"
+    timing_paths = sorted(timingdir_path.iterdir())
+
+    print(f"Loading {len(timing_paths)} timing files from {timingdir_path}...", file=sys.stderr)
+    dfs = []
+    for i, timing_path in enumerate(timing_paths, 1):
+        dfs.append(load_timing_file(timing_path))
+        sys.stderr.write("\x1b[1K\r")
+        sys.stderr.flush()
+        print(f"[{i:8}/{len(timing_paths):8}] {i/len(timing_paths)*100:6.2f}%", file=sys.stderr, end="", flush=True)
+    print(file=sys.stderr, flush=True)
+
+    return pandas.concat(dfs)
+
+
+def load_mean_timings(outdir_path: Path):
+    df = load_all_timings(outdir_path)
+    return df.mean() / 1000000
+
+
+def get_outdirs(jobid: str):
+    print(f"Globbing for {jobid}...", file=sys.stderr)
+    return sorted(Path("/p/scratch/cellsinsilico/paul/nastja-out").glob(f"*{jobid}*"))
+
+
+def load_array_mean_timings(jobid: str, excluded_array_indices):
+    mts = []
+    for outdir_path in get_outdirs(jobid):
+        if any(str(outdir_path).endswith(str(i)) for i in excluded_array_indices):
+            print(f"Not loading timings for {outdir_path} because it was excluded.", file=sys.stderr)
+            continue
+        mts.append(load_mean_timings(outdir_path))
+
+    return pandas.DataFrame(list(mts), columns=mts[0].index)
+
+
+def get_mean_mean_totaltimes(jobid: str):
+    return load_array_mean_timings(jobid).mean()
+
+
+def get_std_mean_totaltimes(jobid: str):
+    return load_array_mean_timings(jobid).std()
+
+
+def get_accounting_data(jobid: str):
+    sacct_results = subprocess.run(
+        ["sacct", "--json", "--jobs", jobid],
+        check=True, # Throw on non-zero exit code,
+        capture_output=True
+    )
+    return json.loads(sacct_results.stdout.decode("utf8"))
+
+
+def get_jobs(jobid: str):
+    accounting_data = get_accounting_data(jobid)
+    jobs = []
+    excluded_array_indices = []
+    for array_job in accounting_data["jobs"]:
+        # Get metadata related to array
+        array_main_job = array_job["array"]["job_id"]
+        array_index = array_job["array"]["task_id"]
+        # The last step is the actual job we want the data for
+        # The steps before set up cluster etc.
+        last_step = array_job["steps"][-1]
+        if last_step["state"] != "COMPLETED":
+            print(f"WARNING: {array_main_job}.{array_index} has state {last_step['state']}, excluding it from measurements", file=sys.stderr)
+            excluded_array_indices.append(array_index)
+            continue
+        jobs.append(last_step)
+
+    return jobs, excluded_array_indices
+
+
+if __name__ == "__main__":
+    p = argparse.ArgumentParser(description="Load and analzye data from nastja timing files")
+    p.add_argument("jobid", nargs="+")
+    p.add_argument("--prettify", action="store_true")
+    p.add_argument("--dump-timings", action="store_true")
+    args = p.parse_args()
+
+    results = []
+    for i, jobid in enumerate(args.jobid, 1):
+        print(f"({i:2}/{len(args.jobid):2}) Loading accounting data for {jobid}", file=sys.stderr)
+        jobs, excluded_array_indices = get_jobs(jobid)
+        array_mean_timings = load_array_mean_timings(jobid, excluded_array_indices)
+        if args.dump_timings:
+            print(array_mean_timings, file=sys.stderr)
+
+        results.append({
+            "jobid": jobid,
+            "means": array_mean_timings.mean().to_dict(),
+            "stds": array_mean_timings.std().to_dict(),
+            "accounting": jobs
+        })
+    print(json.dumps(results, indent=2 if args.prettify else None))

experiments/eval/strong-booster.json

@@ -0,0 +1,63 @@
+{
+  "common": {
+    "account": "hkf6",
+    "partition": "booster",
+    "extra_sbatch_line": "#SBATCH --gres=gpu:4",
+    "logfile_path": "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/logs/%x-%A.%a",
+    "nastja_binary_path": "/p/project/cellsinsilico/paulslustigebude/nastja/build-cuda/nastja",
+    "config_path": "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/generated/config/${SLURM_JOB_NAME}.json",
+    "output_dir_path": "/p/scratch/cellsinsilico/paul/nastja-out/${SLURM_JOB_NAME}-${SLURM_ARRAY_JOB_ID}.${SLURM_ARRAY_TASK_ID}"
+  },
+  "batches": [
+    {
+      "name": "strong-booster-01-01-01",
+      "nodes": 1,
+      "tasks": 1,
+      "time": "00:15:00",
+      "extra_sbatch_line": "#SBATCH --gres=gpu:1"
+    },
+    {
+      "name": "strong-booster-01-01-02",
+      "nodes": 1,
+      "tasks": 2,
+      "time": "00:15:00",
+      "extra_sbatch_line": "#SBATCH --gres=gpu:2"
+    },
+    {
+      "name": "strong-booster-01-02-02",
+      "nodes": 1,
+      "tasks": 4,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-booster-02-02-02",
+      "nodes": 2,
+      "tasks": 8,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-booster-02-02-04",
+      "nodes": 4,
+      "tasks": 16,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-booster-02-04-04",
+      "nodes": 8,
+      "tasks": 32,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-booster-04-04-04",
+      "nodes": 16,
+      "tasks": 64,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-booster-04-04-08",
+      "nodes": 32,
+      "tasks": 128,
+      "time": "00:15:00"
+    }
+  ]
+}

experiments/eval/strong-cpu.json

@@ -0,0 +1,67 @@
+{
+  "common": {
+    "account": "cellsinsilico",
+    "partition": "batch",
+    "extra_sbatch_line": "",
+    "logfile_path": "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/logs/%x-%A.%a",
+    "nastja_binary_path": "/p/project/cellsinsilico/paulslustigebude/nastja/build-nocuda/nastja",
+    "config_path": "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/generated/config/${SLURM_JOB_NAME}.json",
+    "output_dir_path": "/p/scratch/cellsinsilico/paul/nastja-out/${SLURM_JOB_NAME}-${SLURM_ARRAY_JOB_ID}.${SLURM_ARRAY_TASK_ID}"
+  },
+  "batches": [
+    {
+      "name": "strong-cpu-04-04-03",
+      "nodes": 1,
+      "tasks": 48,
+      "time": "01:00:00"
+    },
+    {
+      "name": "strong-cpu-04-04-06",
+      "nodes": 2,
+      "tasks": 96,
+      "time": "01:00:00"
+    },
+    {
+      "name": "strong-cpu-04-04-12",
+      "nodes": 4,
+      "tasks": 192,
+      "time": "00:20:00"
+    },
+    {
+      "name": "strong-cpu-04-08-12",
+      "nodes": 8,
+      "tasks": 384,
+      "time": "00:10:00"
+    },
+    {
+      "name": "strong-cpu-08-08-12",
+      "nodes": 16,
+      "tasks": 768,
+      "time": "00:10:00"
+    },
+    {
+      "name": "strong-cpu-08-08-24",
+      "nodes": 32,
+      "tasks": 1536,
+      "time": "00:10:00"
+    },
+    {
+      "name": "strong-cpu-08-16-24",
+      "nodes": 64,
+      "tasks": 3072,
+      "time": "00:10:00"
+    },
+    {
+      "name": "strong-cpu-16-16-24",
+      "nodes": 128,
+      "tasks": 6144,
+      "time": "00:10:00"
+    },
+    {
+      "name": "strong-cpu-16-16-48",
+      "nodes": 256,
+      "tasks": 12288,
+      "time": "00:10:00"
+    }
+  ]
+}

experiments/eval/strong-gpu.json

@@ -0,0 +1,63 @@
+{
+  "common": {
+    "account": "cellsinsilico",
+    "partition": "gpus",
+    "extra_sbatch_line": "#SBATCH --gres=gpu:4",
+    "logfile_path": "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/logs/%x-%A.%a",
+    "nastja_binary_path": "/p/project/cellsinsilico/paulslustigebude/nastja/build-cuda/nastja",
+    "config_path": "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/generated/config/${SLURM_JOB_NAME}.json",
+    "output_dir_path": "/p/scratch/cellsinsilico/paul/nastja-out/${SLURM_JOB_NAME}-${SLURM_ARRAY_JOB_ID}.${SLURM_ARRAY_TASK_ID}"
+  },
+  "batches": [
+    {
+      "name": "strong-gpu-01-01-01",
+      "nodes": 1,
+      "tasks": 1,
+      "time": "00:15:00",
+      "extra_sbatch_line": "#SBATCH --gres=gpu:1"
+    },
+    {
+      "name": "strong-gpu-01-01-02",
+      "nodes": 1,
+      "tasks": 2,
+      "time": "00:15:00",
+      "extra_sbatch_line": "#SBATCH --gres=gpu:2"
+    },
+    {
+      "name": "strong-gpu-01-02-02",
+      "nodes": 1,
+      "tasks": 4,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-gpu-02-02-02",
+      "nodes": 2,
+      "tasks": 8,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-gpu-02-02-04",
+      "nodes": 4,
+      "tasks": 16,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-gpu-02-04-04",
+      "nodes": 8,
+      "tasks": 32,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-gpu-04-04-04",
+      "nodes": 16,
+      "tasks": 64,
+      "time": "00:15:00"
+    },
+    {
+      "name": "strong-gpu-04-04-08",
+      "nodes": 32,
+      "tasks": 128,
+      "time": "00:15:00"
+    }
+  ]
+}

experiments/eval/templates/strong-batch.j2

@@ -0,0 +1,31 @@
+#!/usr/bin/env bash
+
+#SBATCH --job-name={{ name }}
+#SBATCH --account={{ account }}
+#SBATCH --partition={{ partition }}
+#SBATCH --nodes={{ nodes }}
+#SBATCH --ntasks={{ tasks }}
+# Counted per node
+{{ extra_sbatch_line }}
+#SBATCH --time={{ time }}
+#SBATCH --output={{ logfile_path }}
+#SBATCH --error={{ logfile_path }}
+#SBATCH --array=1-5
+
+NASTJA_BINARY="{{ nastja_binary_path }}"
+CONFIG_FILE="{{ config_path }}"
+OUTPUT_DIR="{{ output_dir_path }}"
+module load Stages/2024 GCC/12.3.0 ParaStationMPI/5.9.2-1 CMake/3.26.3 mold/1.11.0 jq/1.6 git Python
+
+echo "${NASTJA_BINARY_PATH}"
+echo "${CONFIG_FILE}"
+echo "${OUTPUT_DIR}"
+
+cat "${CONFIG_FILE}"
+
+mkdir -p "${OUTPUT_DIR}"
+
+srun "${NASTJA_BINARY}" \
+  -c "${CONFIG_FILE}" \
+  -o "${OUTPUT_DIR}"
+

experiments/eval/templates/strong-booster.json

@@ -0,0 +1,263 @@
+{
+  "Application": "Cells",
+  "CellsInSilico": {
+    "2D": false,
+    "adhesion": {
+      "matrix": [
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 450.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 450.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0]
+      ],
+      "polarityenabled": false
+    },
+    "centerofmass": {
+      "steps": 1
+    },
+    "cleaner": {
+      "killdistance": 0,
+      "steps": 100
+    },
+    "contactinhibition": {
+      "enabled": false
+    },
+    "division": {
+      "condition": [
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "( volume >= 0.9 * volume0 )  & ( rnd() <= 0.00001 ) & generation < 1"
+      ],
+      "enabled": true,
+      "halveSignals": false
+    },
+    "dynamicecm": {
+      "alpha": 2.0,
+      "beta": 0.5,
+      "c": 4.0,
+      "deltat": 0.10000000149011612,
+      "ecmCellID": 0,
+      "enabled": true,
+      "eta": 0.25,
+      "k0": 0.10000000149011612,
+      "k1": 0.10000000149011612,
+      "lambda": 10.0,
+      "phi": 1.0,
+      "pushSteps": 10,
+      "pushWeight": 0.5,
+      "stepsPerMcs": 100
+    },
+    "ecmdegradation": {
+      "enabled": false
+    },
+    "energyfunctions": [
+      "Volume00",
+      "Surface01",
+      "Motility00",
+      "Adhesion01",
+      "DynamicECM00"
+    ],
+    "liquid": 6,
+    "logcellproperties": {
+      "enabled": false
+    },
+    "orientation": {
+      "enabled": true,
+      "motility": "persistentRandomWalk",
+      "motilityamount": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "numRandomNumbers": 5,
+      "persistenceMagnitude": 0.0,
+      "persistentDecay": 0.8,
+      "recalculationtime": 200
+    },
+    "polarity": {
+      "enabled": false
+    },
+    "signaling": {
+      "constant": false,
+      "enabled": false
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 400.0
+      },
+      "lambda": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        5.625,
+        5.625,
+        1.0
+      ],
+      "sizechange": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        -0.05,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    },
+    "temperature": 50.0,
+    "visitor": {
+      "checkerboard": "01",
+      "stepwidth": 10
+    },
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 500.0
+      },
+      "lambda": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        7.5,
+        7.5,
+        7.5
+      ],
+      "sizechange": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        -0.05,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    }
+  },
+  "DefineFunctions": [
+    "r_angle()=360*rnd()",
+    "r_size()=400*rnd()"
+  ],
+  "Filling": {
+    "cells": [
+      {
+        "box": [
+          [
+            0,
+            0,
+            0
+          ],
+          [
+            384,
+            384,
+            384
+          ]
+        ],
+        "celltype": 0,
+        "component": 0,
+        "pattern": "const",
+        "seed": 0,
+        "shape": "cube",
+        "value": 0
+      },
+      {
+        "box": [
+          [117, 117, 177],
+          [267, 267, 267]
+        ],
+        "celltype": 9,
+        "center": [192, 192, 192],
+        "component": 0,
+        "count": 5500,
+        "pattern": "voronoi",
+        "radius": 75,
+        "seed": 758960,
+        "shape": "sphere",
+        "value": 8
+      }
+    ],
+    "initialoutput": false,
+    "randomseed": 758959
+  },
+  "Geometry": {
+    "blockcount": [
+      4,
+      4,
+      3
+    ],
+    "blockdefault": "fill",
+    "blocksize": [
+      96,
+      96,
+      128
+    ],
+    "blocktype": [
+      [
+        [
+          1
+        ]
+      ]
+    ]
+  },
+  "Settings": {
+    "deltat": 1.0,
+    "deltax": 1.0,
+    "handleFPE": "signal",
+    "logger": {
+      "group": 0,
+      "steps": 100
+    },
+    "randomseed": 42,
+    "statusoutput": 1,
+    "timestepguard": 1,
+    "timesteps": 10,
+    "cuda": {
+      "subblocks": {
+        "blockDim": [8, 8, 8]
+      }
+    }
+  }
+}

experiments/eval/templates/strong-cpu.json

@@ -0,0 +1,258 @@
+{
+  "Application": "Cells",
+  "CellsInSilico": {
+    "2D": false,
+    "adhesion": {
+      "matrix": [
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 450.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 450.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0]
+      ],
+      "polarityenabled": false
+    },
+    "centerofmass": {
+      "steps": 1
+    },
+    "cleaner": {
+      "killdistance": 0,
+      "steps": 100
+    },
+    "contactinhibition": {
+      "enabled": false
+    },
+    "division": {
+      "condition": [
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "( volume >= 0.9 * volume0 )  & ( rnd() <= 0.00001 ) & generation < 1"
+      ],
+      "enabled": true,
+      "halveSignals": false
+    },
+    "dynamicecm": {
+      "alpha": 2.0,
+      "beta": 0.5,
+      "c": 4.0,
+      "deltat": 0.10000000149011612,
+      "ecmCellID": 0,
+      "enabled": true,
+      "eta": 0.25,
+      "k0": 0.10000000149011612,
+      "k1": 0.10000000149011612,
+      "lambda": 10.0,
+      "phi": 1.0,
+      "pushSteps": 10,
+      "pushWeight": 0.5,
+      "stepsPerMcs": 100
+    },
+    "ecmdegradation": {
+      "enabled": false
+    },
+    "energyfunctions": [
+      "Volume00",
+      "Surface01",
+      "Motility00",
+      "Adhesion01",
+      "DynamicECM00"
+    ],
+    "liquid": 6,
+    "logcellproperties": {
+      "enabled": false
+    },
+    "orientation": {
+      "enabled": true,
+      "motility": "persistentRandomWalk",
+      "motilityamount": [
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+        0.0,
+        0.0,
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+        0.0,
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+      ],
+      "numRandomNumbers": 5,
+      "persistenceMagnitude": 0.0,
+      "persistentDecay": 0.8,
+      "recalculationtime": 200
+    },
+    "polarity": {
+      "enabled": false
+    },
+    "signaling": {
+      "constant": false,
+      "enabled": false
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 400.0
+      },
+      "lambda": [
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+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
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+        5.625,
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+        0.0
+      ]
+    },
+    "temperature": 50.0,
+    "visitor": {
+      "checkerboard": "01",
+      "stepwidth": 10
+    },
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 500.0
+      },
+      "lambda": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        7.5,
+        7.5,
+        7.5
+      ],
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+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    }
+  },
+  "DefineFunctions": [
+    "r_angle()=360*rnd()",
+    "r_size()=400*rnd()"
+  ],
+  "Filling": {
+    "cells": [
+      {
+        "box": [
+          [
+            0,
+            0,
+            0
+          ],
+          [
+            384,
+            384,
+            384
+          ]
+        ],
+        "celltype": 0,
+        "component": 0,
+        "pattern": "const",
+        "seed": 0,
+        "shape": "cube",
+        "value": 0
+      },
+      {
+        "box": [
+          [117, 117, 177],
+          [267, 267, 267]
+        ],
+        "celltype": 9,
+        "center": [192, 192, 192],
+        "component": 0,
+        "count": 5500,
+        "pattern": "voronoi",
+        "radius": 75,
+        "seed": 758960,
+        "shape": "sphere",
+        "value": 8
+      }
+    ],
+    "initialoutput": false,
+    "randomseed": 758959
+  },
+  "Geometry": {
+    "blockcount": [
+      4,
+      4,
+      3
+    ],
+    "blockdefault": "fill",
+    "blocksize": [
+      96,
+      96,
+      128
+    ],
+    "blocktype": [
+      [
+        [
+          1
+        ]
+      ]
+    ]
+  },
+  "Settings": {
+    "deltat": 1.0,
+    "deltax": 1.0,
+    "handleFPE": "signal",
+    "logger": {
+      "group": 0,
+      "steps": 100
+    },
+    "randomseed": 42,
+    "statusoutput": 1,
+    "timestepguard": 1,
+    "timesteps": 10
+  }
+}

experiments/eval/templates/strong-gpu.json

@@ -0,0 +1,263 @@
+{
+  "Application": "Cells",
+  "CellsInSilico": {
+    "2D": false,
+    "adhesion": {
+      "matrix": [
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 450.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 450.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0]
+      ],
+      "polarityenabled": false
+    },
+    "centerofmass": {
+      "steps": 1
+    },
+    "cleaner": {
+      "killdistance": 0,
+      "steps": 100
+    },
+    "contactinhibition": {
+      "enabled": false
+    },
+    "division": {
+      "condition": [
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "( volume >= 0.9 * volume0 )  & ( rnd() <= 0.00001 ) & generation < 1"
+      ],
+      "enabled": true,
+      "halveSignals": false
+    },
+    "dynamicecm": {
+      "alpha": 2.0,
+      "beta": 0.5,
+      "c": 4.0,
+      "deltat": 0.10000000149011612,
+      "ecmCellID": 0,
+      "enabled": true,
+      "eta": 0.25,
+      "k0": 0.10000000149011612,
+      "k1": 0.10000000149011612,
+      "lambda": 10.0,
+      "phi": 1.0,
+      "pushSteps": 10,
+      "pushWeight": 0.5,
+      "stepsPerMcs": 100
+    },
+    "ecmdegradation": {
+      "enabled": false
+    },
+    "energyfunctions": [
+      "Volume00",
+      "Surface01",
+      "Motility00",
+      "Adhesion01",
+      "DynamicECM00"
+    ],
+    "liquid": 6,
+    "logcellproperties": {
+      "enabled": false
+    },
+    "orientation": {
+      "enabled": true,
+      "motility": "persistentRandomWalk",
+      "motilityamount": [
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+        0.0,
+        0.0,
+        0.0,
+        0.0,
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+        0.0,
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+        0.0
+      ],
+      "numRandomNumbers": 5,
+      "persistenceMagnitude": 0.0,
+      "persistentDecay": 0.8,
+      "recalculationtime": 200
+    },
+    "polarity": {
+      "enabled": false
+    },
+    "signaling": {
+      "constant": false,
+      "enabled": false
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 400.0
+      },
+      "lambda": [
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+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        5.625,
+        5.625,
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+        0.0,
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+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    },
+    "temperature": 50.0,
+    "visitor": {
+      "checkerboard": "01",
+      "stepwidth": 10
+    },
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 500.0
+      },
+      "lambda": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        7.5,
+        7.5,
+        7.5
+      ],
+      "sizechange": [
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+        0.0,
+        0.0,
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+        0.0,
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+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    }
+  },
+  "DefineFunctions": [
+    "r_angle()=360*rnd()",
+    "r_size()=400*rnd()"
+  ],
+  "Filling": {
+    "cells": [
+      {
+        "box": [
+          [
+            0,
+            0,
+            0
+          ],
+          [
+            384,
+            384,
+            384
+          ]
+        ],
+        "celltype": 0,
+        "component": 0,
+        "pattern": "const",
+        "seed": 0,
+        "shape": "cube",
+        "value": 0
+      },
+      {
+        "box": [
+          [117, 117, 177],
+          [267, 267, 267]
+        ],
+        "celltype": 9,
+        "center": [192, 192, 192],
+        "component": 0,
+        "count": 5500,
+        "pattern": "voronoi",
+        "radius": 75,
+        "seed": 758960,
+        "shape": "sphere",
+        "value": 8
+      }
+    ],
+    "initialoutput": false,
+    "randomseed": 758959
+  },
+  "Geometry": {
+    "blockcount": [
+      4,
+      4,
+      3
+    ],
+    "blockdefault": "fill",
+    "blocksize": [
+      96,
+      96,
+      128
+    ],
+    "blocktype": [
+      [
+        [
+          1
+        ]
+      ]
+    ]
+  },
+  "Settings": {
+    "deltat": 1.0,
+    "deltax": 1.0,
+    "handleFPE": "signal",
+    "logger": {
+      "group": 0,
+      "steps": 100
+    },
+    "randomseed": 42,
+    "statusoutput": 1,
+    "timestepguard": 1,
+    "timesteps": 10,
+    "cuda": {
+      "subblocks": {
+        "blockDim": [8, 8, 8]
+      }
+    }
+  }
+}

experiments/eval/templates/weak.json

@@ -0,0 +1,193 @@
+{
+  "Application": "Cells",
+  "CellsInSilico": {
+    "2D": false,
+    "adhesion": {
+      "matrix": [
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 450.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+        [0.0, 450.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0]
+      ],
+      "polarityenabled": false
+    },
+    "centerofmass": {
+      "steps": 1
+    },
+    "cleaner": {
+      "killdistance": 0,
+      "steps": 100
+    },
+    "contactinhibition": {
+      "enabled": false
+    },
+    "division": {
+      "condition": [
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "",
+        "( volume >= 0.9 * volume0 )  & ( rnd() <= 0.00001 ) & generation < 1"
+      ],
+      "enabled": true,
+      "halveSignals": false
+    },
+    "dynamicecm": {
+      "alpha": 2.0,
+      "beta": 0.5,
+      "c": 4.0,
+      "deltat": 0.1,
+      "ecmCellID": 0,
+      "enabled": true,
+      "eta": 0.25,
+      "k0": 0.1,
+      "k1": 0.1,
+      "lambda": 10.0,
+      "phi": 1.0,
+      "pushSteps": 10,
+      "pushWeight": 0.5,
+      "stepsPerMcs": 100
+    },
+    "ecmdegradation": {
+      "enabled": false
+    },
+    "energyfunctions": [
+      "Volume00",
+      "Surface01",
+      "Motility00",
+      "Adhesion01",
+      "DynamicECM00"
+    ],
+    "liquid": 6,
+    "logcellproperties": {
+      "enabled": false
+    },
+    "orientation": {
+      "enabled": true,
+      "motility": "persistentRandomWalk",
+      "motilityamount": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "numRandomNumbers": 5,
+      "persistenceMagnitude": 0.0,
+      "persistentDecay": 0.8,
+      "recalculationtime": 200
+    },
+    "polarity": {
+      "enabled": false
+    },
+    "signaling": {
+      "constant": false,
+      "enabled": false
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 400.0
+      },
+      "lambda": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        5.625,
+        5.625,
+        1.0
+      ],
+      "sizechange": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        -0.05,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    },
+    "temperature": 50.0,
+    "visitor": {
+      "checkerboard": "01",
+      "stepwidth": 10
+    },
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 500.0
+      },
+      "lambda": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        7.5,
+        7.5,
+        7.5
+      ],
+      "sizechange": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        -0.05,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    }
+  },
+  "DefineFunctions": [
+    "r_angle()=360*rnd()",
+    "r_size()=400*rnd()"
+  ],
+  "Filling": {
+    "initialoutput": false,
+    "randomseed": 758959
+  },
+  "Settings": {
+    "randomseed": 42,
+    "statusoutput": 1,
+    "timesteps": 10
+  }
+}

experiments/requirements.txt

@@ -1,98 +1 @@
-anyio==3.7.0
+click==8.1.7
-argon2-cffi==21.3.0
-argon2-cffi-bindings==21.2.0
-arrow==1.2.3
-asttokens==2.2.1
-async-lru==2.0.2
-attrs==23.1.0
-Babel==2.12.1
-backcall==0.2.0
-beautifulsoup4==4.12.2
-bleach==6.0.0
-certifi==2023.5.7
-cffi==1.15.1
-charset-normalizer==3.1.0
-comm==0.1.3
-contourpy==1.1.0
-cycler==0.11.0
-debugpy==1.6.7
-decorator==5.1.1
-defusedxml==0.7.1
-exceptiongroup==1.1.1
-executing==1.2.0
-fastjsonschema==2.17.1
-fonttools==4.40.0
-fqdn==1.5.1
-idna==3.4
-ipykernel==6.23.2
-ipython==8.14.0
-ipywidgets==8.0.6
-isoduration==20.11.0
-jedi==0.18.2
-Jinja2==3.1.2
-json5==0.9.14
-jsonpointer==2.3
-jsonschema==4.17.3
-jupyter-events==0.6.3
-jupyter-lsp==2.2.0
-jupyter_client==8.2.0
-jupyter_core==5.3.1
-jupyter_server==2.6.0
-jupyter_server_terminals==0.4.4
-jupyterlab==4.0.2
-jupyterlab-pygments==0.2.2
-jupyterlab-widgets==3.0.7
-jupyterlab_server==2.23.0
-kiwisolver==1.4.4
-MarkupSafe==2.1.3
-matplotlib==3.7.1
-matplotlib-inline==0.1.6
-mistune==2.0.5
-nbclient==0.8.0
-nbconvert==7.5.0
-nbformat==5.9.0
-nest-asyncio==1.5.6
-notebook_shim==0.2.3
-numpy==1.24.3
-overrides==7.3.1
-packaging==23.1
-pandocfilters==1.5.0
-parso==0.8.3
-pexpect==4.8.0
-pickleshare==0.7.5
-Pillow==9.5.0
-platformdirs==3.5.3
-prometheus-client==0.17.0
-prompt-toolkit==3.0.38
-psutil==5.9.5
-ptyprocess==0.7.0
-pure-eval==0.2.2
-pycparser==2.21
-Pygments==2.15.1
-pyparsing==3.0.9
-pyrsistent==0.19.3
-python-dateutil==2.8.2
-python-json-logger==2.0.7
-PyYAML==6.0
-pyzmq==25.1.0
-requests==2.31.0
-rfc3339-validator==0.1.4
-rfc3986-validator==0.1.1
-Send2Trash==1.8.2
-six==1.16.0
-sniffio==1.3.0
-soupsieve==2.4.1
-stack-data==0.6.2
-terminado==0.17.1
-tinycss2==1.2.1
-tomli==2.0.1
-tornado==6.3.2
-traitlets==5.9.0
-typing_extensions==4.6.3
-uri-template==1.2.0
-urllib3==2.0.3
-wcwidth==0.2.6
-webcolors==1.13
-webencodings==0.5.1
-websocket-client==1.5.3
-widgetsnbextension==4.0.7

experiments/scripts/gen/strong.py

@@ -0,0 +1,96 @@
+import copy
+import json
+
+from typing import Tuple
+
+from toolkit import Configuration
+
+SIZE_X = 400
+SIZE_Y = 400
+SIZE_Z = 400
+
+def make_config(gpus: int, blockcount: Tuple[int, int, int]) -> Configuration:
+    assert gpus % 4 == 0
+    assert SIZE_X % blockcount[0] == 0
+    assert SIZE_Y % blockcount[1] == 0
+    assert SIZE_Z % blockcount[2] == 0
+    assert blockcount[0] * blockcount[1] * blockcount[2] == gpus
+
+    return Configuration(
+        gpus // 4,
+        gpus,
+        4,
+        blockcount,
+        (SIZE_X // blockcount[0], SIZE_Y // blockcount[1], SIZE_Z // blockcount[2])
+    )
+
+configurations = [
+    Configuration(1, 1, 1, (1, 1, 1), (400, 400, 400)),
+    Configuration(1, 2, 2, (1, 1, 2), (400, 400, 200)),
+    Configuration(1, 2, 2, (1, 2, 1), (400, 200, 400)),
+    Configuration(1, 2, 2, (2, 1, 1), (200, 400, 400)),
+    make_config(4, (1, 1, 4)),
+    make_config(4, (1, 4, 1)),
+    make_config(4, (4, 1, 1)),
+    make_config(4, (1, 2, 2)),
+    make_config(4, (2, 1, 2)),
+    make_config(4, (2, 2, 1)),
+    make_config(8, (2, 2, 2)),
+    make_config(8, (1, 2, 4)),
+    make_config(16, (1, 4, 4)),
+    make_config(16, (2, 2, 4)),
+    make_config(32, (2, 4, 4)),
+    make_config(64, (4, 4, 4)),
+    make_config(128, (4, 4, 8)),
+    make_config(256, (4, 8, 8)),
+    make_config(512, (8, 8, 8)),
+    make_config(1024, (8, 8, 16)),
+    make_config(2048, (8, 16, 16))
+]
+
+with open("templates/spheroid.json") as template_file:
+    template = json.load(template_file)
+
+for c in configurations:
+    print(c)
+    assert(c.get_domain_size() == configurations[0].get_domain_size())
+
+    nastja_config = copy.deepcopy(template)
+
+    nastja_config["Geometry"]["blockcount"] = c.blockcount
+    nastja_config["Geometry"]["blocksize"] = c.blocksize
+
+    label = c.get_label()
+
+    with open(f"configs/measurements/strong/spheroid_{label}.json", "w") as config_file:
+        json.dump(nastja_config, config_file, indent=2)
+
+    batch_config = f"""#!/usr/bin/env bash
+
+#SBATCH --job-name=strong-{label}
+#SBATCH --account=hkf6
+#SBATCH --partition=booster
+#SBATCH --nodes={c.nodes}
+#SBATCH --ntasks={c.tasks}
+# Counted per node
+#SBATCH --gres=gpu:{c.gpus_per_node}
+#SBATCH --time=00:30:00
+#SBATCH --output=logs/strong-{label}-%A_%a.log
+#SBATCH --error=logs/strong-{label}-%A_%a.log
+#SBATCH --array=1-5
+
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR="/p/scratch/cellsinsilico/paul/nastja-out/strong-{label}-${{SLURM_ARRAY_TASK_ID}}"
+
+echo "outdir is ${{OUTPUT_DIR}}"
+
+mkdir -p "${{OUTPUT_DIR}}"
+source "${{SOURCE_DIR}}/activate-nastja-modules"
+
+srun --unbuffered "${{SOURCE_DIR}}/nastja/build-cuda/nastja" \\
+  -c "${{SOURCE_DIR}}/ma/experiments/configs/measurements/strong/spheroid_{label}.json" \\
+  -o "${{OUTPUT_DIR}}"
+"""
+
+    with open(f"batch/measurements/strong/strong-{label}", "w", encoding="utf8") as batch_config_file:
+        batch_config_file.write(batch_config)

experiments/scripts/gen/toolkit.py

@@ -0,0 +1,16 @@
+from dataclasses import dataclass
+from typing import Tuple
+
+@dataclass
+class Configuration:
+    nodes: int
+    tasks: int
+    gpus_per_node: int
+    blockcount: Tuple[int, int, int]
+    blocksize: Tuple[int, int, int]
+
+    def get_domain_size(self) -> int:
+        return self.blockcount[0] * self.blocksize[0] * self.blockcount[1] * self.blocksize[1] * self.blockcount[2] * self.blocksize[2]
+
+    def get_label(self) -> str:
+        return f"t{self.tasks:04}n{self.nodes:03}g{self.gpus_per_node}x{self.blockcount[0]}y{self.blockcount[1]}z{self.blockcount[2]}"

experiments/scripts/gen/varied_fillings.py

@@ -0,0 +1,54 @@
+#!/usr/bin/env python
+
+import json
+import sys
+
+from functools import reduce
+from operator import mul
+from pathlib import Path
+
+percent_filled = float(sys.argv[1])
+template_path = Path("templates/varied-fillings.json")
+
+initial_cell_size = 4200
+
+with template_path.open(encoding="utf-8") as template_file:
+    config = json.load(template_file)
+
+dims = [
+    size * count
+    for size, count
+    in zip(config["Geometry"]["blocksize"], config["Geometry"]["blockcount"])
+]
+total_volume = reduce(mul, dims, 1)
+target_volume = total_volume * percent_filled / 100
+n_cells = int(target_volume // initial_cell_size)
+# If n_cells is odd, second type gets one more cell
+n_cells_first_type = n_cells // 2
+n_cells_second_type = n_cells - n_cells_first_type
+edge_length = int(target_volume ** (1 / 3))
+offsets = [
+    (dims[0] - edge_length) // 2,
+    (dims[1] - edge_length) // 2,
+    (dims[2] - edge_length) // 2
+]
+
+print(f"Target volume: {target_volume} ({percent_filled}%, edge length: {edge_length}), # of cells: {n_cells}", file=sys.stderr)
+
+if target_volume > 0:
+    config["Filling"]["cells"].append({
+        "shape": "cube",
+        "pattern": "voronoi",
+        "box": [
+            offsets,
+            [
+                min(offsets[0] + edge_length, dims[0] - 1),
+                min(offsets[1] + edge_length, dims[1] - 1),
+                min(offsets[2] + edge_length, dims[2] - 1)
+            ]
+        ],
+        "count": n_cells,
+        "celltype": [0, 0, n_cells_first_type, n_cells_second_type]
+    })
+
+json.dump(config, sys.stdout, indent=2)

experiments/scripts/gen/weak.py

@@ -0,0 +1,107 @@
+import copy
+import json
+
+from dataclasses import dataclass
+
+configurations = [
+    (1, 1, 1),
+    (1, 1, 2),
+    (1, 2, 2),
+    (2, 2, 2),
+    (2, 2, 4),
+    (2, 4, 4),
+    (4, 4, 4),
+    (4, 4, 8),
+    (4, 8, 8),
+    (8, 8, 8)
+]
+
+with open("templates/spheroid_weak.json") as template_file:
+    template = json.load(template_file)
+
+SIZE_X = 400
+SIZE_Y = 400
+SIZE_Z = 400
+
+for bx, by, bz in configurations:
+    nastja_config = copy.deepcopy(template)
+    nastja_config["Geometry"]["blockcount"] = [bx, by, bz]
+    nastja_config["Geometry"]["blocksize"] = [SIZE_X, SIZE_Y, SIZE_Z]
+
+    # Fill the whole domain with ECM
+    cells_filling = [
+        {
+            "shape": "cube",
+            "box": [
+              [0, 0, 0],
+              [bx * SIZE_X, by * SIZE_Y, bz * SIZE_Z]
+            ],
+            "value": 0,
+            "celltype": 0
+        }
+    ]
+
+    # Place a bunch of cells in each block to keep each rank busy
+    for z in range(bz):
+        for y in range(by):
+            for x in range(bx):
+                sx = x * SIZE_X
+                sy = y * SIZE_Y
+                sz = z * SIZE_Z
+                cells_filling.append({
+                    "shape": "sphere",
+                    "pattern": "voronoi",
+                    "count": 5500,
+                    "radius": 75,
+                    "center": [sx + 200, sy + 200, sz + 200],
+                    "box": [
+                        [sx + 110, sy + 110, sz + 110],
+                        [sx + 290, sy + 290, sz + 290]
+                    ],
+                    "celltype": 9
+                })
+    nastja_config["Filling"]["cells"] = cells_filling
+
+    ntasks = bx * by * bz
+    if ntasks < 4:
+        nodes = 1
+        gpus_per_node = ntasks
+    else:
+        assert ntasks % 4 == 0
+        nodes = ntasks // 4
+        gpus_per_node = 4
+
+    label = f"weak400-t{ntasks:04}n{nodes:03}g{gpus_per_node}x{bx}y{by}z{bz}"
+
+    with open(f"configs/measurements/weak/spheroid_{label}.json", "w") as config_file:
+        json.dump(nastja_config, config_file, indent=2)
+
+    batch_config = f"""#!/usr/bin/env bash
+
+#SBATCH --job-name={label}
+#SBATCH --account=hkf6
+#SBATCH --partition=booster
+#SBATCH --nodes={nodes}
+#SBATCH --ntasks={ntasks}
+# Counted per node
+#SBATCH --gres=gpu:{gpus_per_node}
+#SBATCH --time=00:15:00
+#SBATCH --output=logs/{label}-%A_%a.log
+#SBATCH --error=logs/{label}-%A_%a.log
+#SBATCH --array=1-5
+
+SOURCE_DIR=/p/project/cellsinsilico/paulslustigebude
+OUTPUT_DIR="/p/scratch/cellsinsilico/paul/nastja-out/{label}-${{SLURM_ARRAY_TASK_ID}}"
+
+echo "outdir is ${{OUTPUT_DIR}}"
+
+mkdir -p "${{OUTPUT_DIR}}"
+source "${{SOURCE_DIR}}/activate-nastja-modules"
+
+srun --unbuffered "${{SOURCE_DIR}}/nastja/build-cuda/nastja" \\
+  -c "${{SOURCE_DIR}}/ma/experiments/configs/measurements/weak/spheroid_{label}.json" \\
+  -o "${{OUTPUT_DIR}}"
+"""
+
+    with open(f"batch/measurements/weak/{label}", "w", encoding="utf8") as batch_config_file:
+        batch_config_file.write(batch_config)

experiments/scripts/timing.py

@@ -0,0 +1,146 @@
+import click
+import csv
+import re
+import sqlite3
+
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Tuple
+
+@dataclass
+class TimingData:
+    tasks: int
+    nodes: int
+    gpus_per_node: int
+    blockcount: Tuple[int, int, int]
+    array_index: int
+
+    # Given in seconds
+    timings_by_task: [float]
+
+RUN_PATTERN = re.compile(r".*t([0-9]+)n([0-9]+)g([0-9]+)x([0-9]+)y([0-9]+)z([0-9]+)-([0-9]+)")
+TIMING_PATTERN = re.compile(r"timing-([0-9]+)\.dat")
+TIMING_ROW_PATTERN = re.compile(r"([^ ]+) +([^ ]+) +([^ ]+) +([^ ]+) +([^ ]+).*")
+
+def get_timing(timing_path: Path, action: str) -> float:
+    with timing_path.open(encoding="utf8") as timing_file:
+        for line in timing_file:
+            m = TIMING_ROW_PATTERN.match(line)
+            if not m:
+                continue
+
+            if m.group(1) == action:
+                return float(m.group(5))
+
+    raise f"Could not find action '{action}' in {timing_path}"
+
+def get_timings(d: Path, action: str) -> [float]:
+    timings = []
+    for timing_path in d.iterdir():
+        i = int(TIMING_PATTERN.match(timing_path.name).group(1))
+        timings.append((i, get_timing(timing_path, action) / 1_000_000))
+
+    return [timing for i, timing in sorted(timings, key=lambda t: t[0])]
+
+def get_outdir_timing_data(d: Path, action: str) -> TimingData:
+    match_results = RUN_PATTERN.match(d.name)
+    tasks = int(match_results.group(1))
+    nodes = int(match_results.group(2))
+    gpus_per_node = int(match_results.group(3))
+    blockcount = (
+        int(match_results.group(4)),
+        int(match_results.group(5)),
+        int(match_results.group(6))
+    )
+    array_index = int(match_results.group(7))
+    timings_by_task = get_timings(d / "timing", action)
+
+    return TimingData(
+        tasks,
+        nodes,
+        gpus_per_node,
+        blockcount,
+        array_index,
+        timings_by_task
+    )
+
+@click.group()
+def timing():
+    pass
+
+@timing.command()
+@click.argument(
+    "directories",
+    type=click.Path(exists=True, file_okay=False, path_type=Path),
+    nargs=-1
+)
+@click.option("--db", default="timings.db", help="Path of sqlite database file")
+def make_timing_db(directories, db):
+    """
+    Collect NAStJA timing data from all passed directories and save them into a SQLite database.
+
+    Drops the timings table from the given database and creates a new timings table.
+
+    @param db asjdas
+    """
+    db = sqlite3.connect(db)
+    c = db.cursor()
+    c.execute("drop table if exists timings")
+    c.execute("create table timings (tasks, blockcount_x, blockcount_y, blockcount_z, array_index, averagetime)")
+
+    print("Collecting timing info...")
+    for d in directories:
+        print(d)
+        t = get_outdir_timing_data(d, "Sweep:DynamicECM")
+        c.executemany(
+            "insert into timings values (?, ?, ?, ?, ?, ?)",
+            [
+                (t.tasks, t.blockcount[0], t.blockcount[1], t.blockcount[2], t.array_index, sum(t.timings_by_task) / len(t.timings_by_task))
+            ]
+        )
+    print("Done, committing into DB...")
+    
+    db.commit()
+
+    print("Done!")
+
+@timing.command()
+@click.option("--db", default="timings.db", help="Path of sqlite database file")
+@click.option("--time/--no-time", default=False, help="Print average time of best run instead of speedup")
+def strong_dat(db, time):
+    db = sqlite3.connect(db)
+    c = db.cursor()
+    res = c.execute("""
+    select tasks, min(avg)
+    from (
+        select tasks, blockcount_x, blockcount_y, blockcount_z, sum(averagetime) / count(*) as avg
+        from timings group by tasks, blockcount_x, blockcount_y, blockcount_z
+    ) group by tasks order by tasks asc;
+    """)
+    values = res.fetchall()
+
+    if not time:
+        print("gpus\tspeedup")
+        for tasks, time in values:
+            print(f"{tasks}\t{values[0][1] / time}")
+    else:
+        print("gpus\ttime")
+        for tasks, time in values:
+            print(f"{tasks}\t{time}")
+
+@timing.command()
+@click.option("--db", default="timings.db", help="Path of sqlite database file")
+def weak_dat(db):
+    db = sqlite3.connect(db)
+    c = db.cursor()
+    res = c.execute("""
+    select tasks, avg(averagetime) as mean from timings group by tasks order by tasks asc
+    """)
+    values = res.fetchall()
+
+    print("gpus\tefficiency")
+    for tasks, mean in values:
+        print(f"{tasks}\t{values[0][1] / mean}")
+
+if __name__ == "__main__":
+    timing()

experiments/templates/spheroid.json

@@ -0,0 +1,117 @@
+{
+    "Comments": ["Celltype         Usage", "0                Dynamic ECM", "1-5             Not Used", "6               Liquid  ", "7               Apoptotic cell Type ", "8               Basic Non Dividing Cell type (surrounding)", "9               Cancer"],
+    "Application": "Cells",
+    "CellsInSilico": {
+        "ecmdegradation": {
+            "enabled": "false",
+            "steps": 99999,
+            "stochastic": "true",
+            "probability": 0.5
+        },
+        "energyfunctions": ["Volume00", "Surface01", "Motility00", "Adhesion01", "DynamicECM00"],
+        "liquid": 6,
+        "volume": {
+            "default": {
+                "storage": "const",
+                "value": 500
+            },
+            "lambda": [0, 0, 0, 0, 0, 0, 0, 7.5, 7.5, 7.5],
+            "sizechange": [0, 0, 0, 0, 0, 0, 0, -0.05, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "surface": {
+            "default": {
+                "storage": "const",
+                "value": 400
+            },
+            "lambda": [0, 0, 0, 0, 0, 0, 0, 5.625, 5.625, 1],
+            "sizechange": [0, 0, 0, 0, 0, 0, 0, -0.05, 0, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "adhesion": {
+            "matrix": [
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 450],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 450, 0, 0, 0, 0, 0, 0, 0, 50]
+            ]
+        },
+        "temperature": 50,
+        "division": {
+            "enabled": "true",
+            "condition": ["", "", "", "", "", "", "", "", "", "( volume >= 0.9 * volume0 )  & ( rnd() <= 0.00001 ) & generation < 1"]
+        },
+        "centerofmass": {
+            "steps": 1
+        },
+        "signaling": {
+            "enabled": false
+        },
+        "orientation": {
+            "enabled": true,
+            "motility": "persistentRandomWalk",
+            "persistenceMagnitude": 0.0,
+            "recalculationtime": 200,
+            "motilityamount": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "visitor": {
+            "stepwidth": 10,
+            "checkerboard": "01"
+        },
+        "cleaner": {
+            "killDistance": 20
+        },
+        "dynamicecm": {
+            "enabled": true,
+            "stepsPerMcs": 100,
+            "pushSteps": 10,
+            "pushWeight": 2,
+            "ecmCellID": 0,
+            "deltat": 0.1,
+            "eta": 0.25,
+            "k0": 0.1,
+            "k1": 0.1,
+            "c": 4,
+            "alpha": 2,
+            "d": 0.3,
+            "phi": 1
+        }
+    },
+    "Geometry": {
+        "blockcount": null,
+        "blocksize": null
+    },
+    "Settings": {
+        "randomseed": 0,
+        "timesteps": 20,
+        "statusoutput": 1
+    },
+    "WriteActions": [],
+    "Writers": {
+        "CellInfo": {
+            "field": "",
+            "groupsize": 0,
+            "steps": 1,
+            "writer": "CellInfo"
+        },
+        "ParallelVTK_Cells": {
+            "field": "cells",
+            "outputtype": "UInt32",
+            "printhints": false,
+            "steps": 100,
+            "writer": "ParallelVtkImage"
+        },
+        "ParallelVTK_Displacement": {
+            "writer": "ParallelVtkImage",
+            "outputtype": "Float32",
+            "field": "dynamicecm",
+            "components": [0, 1, 2],
+            "steps": 100
+        }
+    },
+    "Include": "config_filling_1.json"
+}

experiments/templates/spheroid_weak.json

@@ -0,0 +1,100 @@
+{
+    "Comments": ["Celltype         Usage", "0                Dynamic ECM", "1-5             Not Used", "6               Liquid  ", "7               Apoptotic cell Type ", "8               Basic Non Dividing Cell type (surrounding)", "9               Cancer"],
+    "Application": "Cells",
+    "CellsInSilico": {
+        "ecmdegradation": {
+            "enabled": "false",
+            "steps": 99999,
+            "stochastic": "true",
+            "probability": 0.5
+        },
+        "energyfunctions": ["Volume00", "Surface01", "Motility00", "Adhesion01", "DynamicECM00"],
+        "liquid": 6,
+        "volume": {
+            "default": {
+                "storage": "const",
+                "value": 500
+            },
+            "lambda": [0, 0, 0, 0, 0, 0, 0, 7.5, 7.5, 7.5],
+            "sizechange": [0, 0, 0, 0, 0, 0, 0, -0.05, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "surface": {
+            "default": {
+                "storage": "const",
+                "value": 400
+            },
+            "lambda": [0, 0, 0, 0, 0, 0, 0, 5.625, 5.625, 1],
+            "sizechange": [0, 0, 0, 0, 0, 0, 0, -0.05, 0, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "adhesion": {
+            "matrix": [
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 450],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+                [0, 450, 0, 0, 0, 0, 0, 0, 0, 50]
+            ]
+        },
+        "temperature": 50,
+        "division": {
+            "enabled": "true",
+            "condition": ["", "", "", "", "", "", "", "", "", "( volume >= 0.9 * volume0 )  & ( rnd() <= 0.00001 ) & generation < 1"]
+        },
+        "centerofmass": {
+            "steps": 1
+        },
+        "signaling": {
+            "enabled": false
+        },
+        "orientation": {
+            "enabled": true,
+            "motility": "persistentRandomWalk",
+            "persistenceMagnitude": 0.0,
+            "recalculationtime": 200,
+            "motilityamount": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+        },
+        "visitor": {
+            "stepwidth": 10,
+            "checkerboard": "01"
+        },
+        "cleaner": {
+            "killDistance": 20
+        },
+        "dynamicecm": {
+            "enabled": true,
+            "stepsPerMcs": 100,
+            "pushSteps": 10,
+            "pushWeight": 2,
+            "ecmCellID": 0,
+            "deltat": 0.1,
+            "eta": 0.25,
+            "k0": 0.1,
+            "k1": 0.1,
+            "c": 4,
+            "alpha": 2,
+            "d": 0.3,
+            "phi": 1
+        }
+    },
+    "Geometry": {
+        "blockcount": null,
+        "blocksize": null
+    },
+    "Settings": {
+        "randomseed": 0,
+        "timesteps": 20,
+        "statusoutput": 1
+    },
+    "DefineFunctions": [
+        "r_angle()=360*rnd()",
+        "r_size()=400*rnd()"
+    ],
+    "Filling": {
+        "cells": null
+    }
+}

experiments/templates/varied-fillings.json

@@ -0,0 +1,103 @@
+{
+  "#Testing": {
+    "description": "Cellular Potts Model with dynamic ECM"
+  },
+  "Application": "Cells",
+  "Geometry": {
+    "blocksize": [30, 30, 40],
+    "blockcount": [4, 4, 3]
+  },
+  "Settings": {
+    "timesteps": 750,
+    "randomseed": 42
+  },
+  "Filling": {
+    "cells": [
+      {
+        "_comment": "This is for the dynamic ECM",
+        "shape": "cube",
+        "box": [
+          [0, 0, 0],
+          [119, 119, 119]
+        ],
+        "value": 0,
+        "celltype": 0
+      }
+    ]
+  },
+  "CellsInSilico": {
+    "liquid": 1,
+    "adhesion": {
+      "matrix": [
+        [ 0, 0,  10, 10],
+        [ 0, 0,  0,  0],
+        [10, 0, 40,  5],
+        [10, 0,  5, 40]
+      ]
+    },
+    "temperature": 15,
+    "volume": {
+      "default": {
+        "storage": "const",
+        "value": 6000
+      },
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "surface": {
+      "default": {
+        "storage": "const",
+        "value": 1000
+      },
+      "lambda": {
+        "storage": "const",
+        "value": 10
+      }
+    },
+    "cleaner": {
+      "killdistance": 100
+    },
+    "checkerboard": "00",
+    "energyfunctions": ["Volume00", "Surface00", "Adhesion00", "DynamicECM00"],
+    "centerofmass": {
+      "steps": 10
+    },
+    "dynamicecm": {
+      "enabled": true,
+      "stepsPerMcs": 200,
+      "pushSteps": 10,
+      "pushWeight": 2,
+      "ecmCellID": 0,
+      "deltat": 0.1,
+      "eta": 0.25,
+      "k0": 0.1,
+      "k1": 0.1,
+      "c": 4,
+      "alpha": 2,
+      "d": 0.3,
+      "phi": 1
+    }
+  },
+  "Writers": {
+    "ParallelVTK_Cells": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "UInt32",
+      "field": "cells",
+      "steps": 10
+    },
+    "ParallelVTK_Displacement": {
+      "writer": "ParallelVtkImage",
+      "outputtype": "Float32",
+      "field": "dynamicecm",
+      "components": [0, 1, 2],
+      "steps": 10
+    },
+    "CellInfo": {
+      "writer": "CellInfo",
+      "steps": 10
+    }
+  },
+  "WriteActions": ["ParallelVTK_Cells", "ParallelVTK_Displacement", "CellInfo"]
+}