metagraphoptimization.jl/notebooks/large_compton.ipynb
Anton Reinhard 92e0eeaaef heterogeneity (#27)
Prepare things to work with heterogeneity, make things work on GPU

Reviewed-on: Rubydragon/MetagraphOptimization.jl#27
Co-authored-by: Anton Reinhard <anton.reinhard@proton.me>
Co-committed-by: Anton Reinhard <anton.reinhard@proton.me>
2023-12-18 14:31:52 +01:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"12"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"using MetagraphOptimization\n",
"using BenchmarkTools\n",
"\n",
"Threads.nthreads()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Graph:\n",
" Nodes: Total: 15866, DataTask: 7937, ComputeTaskQED_S2: 720, \n",
" ComputeTaskQED_Sum: 1, ComputeTaskQED_V: 4320, ComputeTaskQED_S1: 2880, \n",
" ComputeTaskQED_U: 8\n",
" Edges: 21617\n",
" Total Compute Effort: 66249.0\n",
" Total Data Transfer: 1.314048e6\n",
" Total Compute Intensity: 0.050415966540035065\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"machine = get_machine_info()\n",
"model = QEDModel()\n",
"process = parse_process(\"ke->kkkkke\", model)\n",
"\n",
"inputs = [gen_process_input(process) for _ in 1:1e3];\n",
"graph = gen_graph(process)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Graph:\n",
" Nodes: Total: 2234, DataTask: 1121, ComputeTaskQED_S2: 720, \n",
" ComputeTaskQED_Sum: 1, ComputeTaskQED_V: 312, ComputeTaskQED_S1: 72, \n",
" ComputeTaskQED_U: 8\n",
" Edges: 3977\n",
" Total Compute Effort: 11313.0\n",
" Total Data Transfer: 659712.0\n",
" Total Compute Intensity: 0.017148392025611175\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"optimizer = ReductionOptimizer()\n",
"\n",
"compute_compton = get_compute_function(graph, process, machine)\n",
"optimize_to_fixpoint!(optimizer, graph)\n",
"graph"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Calculated 133942.0 results/s, 11162.0 results/s per thread for QED Process: 'ke->kkkkke' (12 threads)\n"
]
}
],
"source": [
"compute_compton_reduced = get_compute_function(graph, process, machine)\n",
"outputs = [zero(ComplexF64) for _ in 1:1e6]\n",
"\n",
"bench_result = @benchmark begin\n",
" Threads.@threads :static for i in eachindex(inputs)\n",
" outputs[i] = compute_compton_reduced(inputs[i])\n",
" end\n",
"end\n",
"\n",
"rate = length(inputs) / (mean(bench_result.times) / 1.0e9)\n",
"rate_per_thread = rate / Threads.nthreads()\n",
"println(\"Calculated $(round(rate)) results/s, $(round(rate_per_thread)) results/s per thread for $(process) ($(Threads.nthreads()) threads)\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Calculated 17124.0 results/s, 1427.0 results/s per thread for QED Process: 'ke->kkkkke' (12 threads)\n"
]
}
],
"source": [
"bench_result = @benchmark begin\n",
" Threads.@threads :static for i in eachindex(inputs)\n",
" outputs[i] = compute_compton(inputs[i])\n",
" end\n",
"end\n",
"\n",
"rate = length(inputs) / (mean(bench_result.times) / 1.0e9)\n",
"rate_per_thread = rate / Threads.nthreads()\n",
"println(\"Calculated $(round(rate)) results/s, $(round(rate_per_thread)) results/s per thread for $(process) ($(Threads.nthreads()) threads)\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.9.4",
"language": "julia",
"name": "julia-1.9"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.9.4"
}
},
"nbformat": 4,
"nbformat_minor": 4
}