Compiling SIMULA: a historical study of technological genesis
High Performance Compu2ng Department, Simula Research Laboratory… · 2016. 1. 26. · Johannes...
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Pa$ent Data Johannes Langguth High Performance Compu2ng Department, Simula Research Laboratory, Oslo, Norway Par,,oning Scalable Heterogeneous CPU-GPU Computa$ons for Unstructured Tetrahedral Meshes MPI separator Node interior part MPI separator Node interior part Global problem GPU 1 separator GPU 1 interior part GPU 0 separator GPU 0 interior part MPI separator CPU interior part CPU-GPU separator MPI separator Node interior part ff 3D Tetrahedral Mesh QPI 32 GB/s 51.2 GB/s 51.2 GB/s 8 GB/s 8 GB/s MPI Infiniband Heterogeneous Nodes Compute CPU main part Compute MPI separator Send MPI separator to other nodes Receive MPI separator from other node Compute GPU 0 separator Compute GPU 1 separator Compute GPU 1 main part Compute GPU 0 main part Send CPU<GPU separator to GPU 0 GPU 0 swap GPU 1 swap Send CPU<GPU separator to GPU 1 Send GPU 1 separator to GPU 0 Send GPU 0 separator to GPU 1 CPU swap Thread 0 1 2 15 14 3 Time during compute round 13 … Idle Compute CPU<GPU separator Send GPU 0 separator to host Send GPU 1 separator to host Calcium Handling -75 -50 -25 0 25 scalars -87.2 40 C A B t=150ms t=250ms t=500ms t=600ms t=750ms t=1250ms t=1350ms t=1100ms 0 500 1000 1500 2000 2500 3000 16 32 64 128 GFLOPs GPU only Heterogeneous Communica=on Disabled Scaling Performance
Transcript of High Performance Compu2ng Department, Simula Research Laboratory… · 2016. 1. 26. · Johannes...
MonodomainSimula,onsofCardiacElectrophysiologyoverUnstructured3DHeartGeometry
Pa$entData
JohannesLangguthHighPerformanceCompu2ngDepartment,SimulaResearchLaboratory,Oslo,Norway
Par,,o
ning
ScalableHeterogeneousCPU-GPUComputa$onsforUnstructured
TetrahedralMeshes
MPIseparator
Nodeinteriorpart
MPIseparator
Nodeinteriorpart
Globalproblem
GPU1separator
GPU1interiorpart
GPU0separator
GPU0interiorpart
MPIseparator
CPUinteriorpart
CPU-GPUseparator
MPIseparator
Nodeinteriorpart
ff
3DTetrahedralMesh
QPI$32$GB/s$51.2$GB/s$ 51.2$GB/s$
8$GB/s$ 8$GB/s$
MPI$Infiniband$
HeterogeneousNodes
Compute(CPU(main(part(
Compute(MPI((separator(
Send(MPI(separator(to(other(nodes(
Receive(MPI(separator(from(other(node(
Compute(GPU(0(separator(
Compute(GPU(1(separator( Compute(GPU(1(main(part(
Compute(GPU(0(main(part(
Send(CPU<GPU((separator(to(GPU(0(
GPU(0(swap(
GPU(1(swap(
Send(CPU<GPU((separator(to(GPU(1(
Send(GPU(1((separator(to(GPU(0(
Send(GPU(0((separator(to(GPU(1(
CPU(swap(
Thread(
0(
1(
2(
15(
14(
3(
Time(during(compute(round(
13(
…(
Idle(Compute(CPU<GPU((separator(
Send(GPU(0(separator(to(host(
Send(GPU(1(separator(to(host(
Calcium
Hand
ling
-75
-50
-25
025
scalars
-87.2
40
CA Bt=150ms t=250ms t=500ms t=600ms
t=750ms t=1250ms t=1350mst=1100ms
0"
500"
1000"
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2000"
2500"
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16" 32" 64" 128"
GFLOPs'
GPU"only" Heterogeneous" Communica=on"Disabled"
ScalingPerformance
