Open TS dynamic parallelization system

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Program Systems Institute Russian Academy of Sciences

Open TS Open TS dynamic parallelization systemdynamic parallelization system

Program Systems Institute RAS, Program Systems Institute RAS, Alexander Moskovsky,Alexander Moskovsky,

09/27/0509/27/05Pereslavl-ZalesskyPereslavl-Zalessky

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Open TS dynamic parallelization systemOpen TS dynamic parallelization system

SKIF Supercomputing SKIF Supercomputing ProjectProject

SKIF Supercomputing SKIF Supercomputing ProjectProject

Joint of Russian Federation Joint of Russian Federation and Republic of Belarusand Republic of Belarus

2000-2004 2000-2004 10 + 10 organizations10 + 10 organizations PSI RAS is lead organization PSI RAS is lead organization

from Russian Federationfrom Russian Federation Hardware and Hardware and SoftwareSoftware

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Comparison: T-System and Comparison: T-System and MPIMPI

Comparison: T-System and Comparison: T-System and MPIMPI

C/Fortran T-System

Assembler MPI

High-levela few

keywords

Low-levelhundred(s)primitives

Sequential Parallel

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Open TS: an OutlineOpen TS: an OutlineOpen TS: an OutlineOpen TS: an Outline High-performance computing High-performance computing ““Automatic dynamic parallelization”Automatic dynamic parallelization” Combining functional and Combining functional and

imperative approaches, high-level imperative approaches, high-level parallel programmingparallel programming

Т++ Т++ language: “Parallel dialect” of language: “Parallel dialect” of C++ — an approach popular in 90-C++ — an approach popular in 90-iesies

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Т-Т-ApproachApproachТ-Т-ApproachApproach ““Pure” function (Pure” function (tfunctiontfunction) invocations ) invocations

produce grains of parallelismproduce grains of parallelism T-Program isT-Program is

Functional – on higher levelFunctional – on higher level Imperative – on low level (optimization)Imperative – on low level (optimization)

C-compatible execution modelC-compatible execution model Non-ready variables, Multiple Non-ready variables, Multiple

assignmentassignment ““Seamless” C-extension Seamless” C-extension (or Fortran-(or Fortran-

extension)extension)

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Т++Т++ Keywords KeywordsТ++Т++ Keywords Keywords tfuntfun —— Т-Т-functionfunction tvaltval—— Т-Т-variablevariable tptrtptr—— Т-Т-pointerpointer touttout —— Output parameter (like &) Output parameter (like &) tdroptdrop —— Make ready Make ready twaittwait —— Wait for readiness Wait for readiness tcttct —— Т-Т-contextcontext

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Sample ProgramSample ProgramSample ProgramSample Program#include <stdio.h>#include <stdio.h>

tfuntfun int fib (int n) { int fib (int n) { return n < 2 ? n : fib(n-1)+fib(n-2);return n < 2 ? n : fib(n-1)+fib(n-2);}}

tfuntfun int main (int argc, char **argv) { int main (int argc, char **argv) { if (argc != 2) { printf("Usage: fib <n>\n"); return 1; }if (argc != 2) { printf("Usage: fib <n>\n"); return 1; } int n = atoi(argv[1]);int n = atoi(argv[1]); printf("fib(%d) = %d\n", n, printf("fib(%d) = %d\n", n, (int)fib(n));(int)fib(n)); return 0;return 0;}}

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Open TSOpen TS: : EnvironmentEnvironmentOpen TSOpen TS: : EnvironmentEnvironment

Supports 1000 000 threads per CPU

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NPB, TestNPB, Test ЕР ЕРRewritten @OpenTSRewritten @OpenTS

NPB, TestNPB, Test ЕР ЕРRewritten @OpenTSRewritten @OpenTS

ЕР – ЕР – EmbarrassinglEmbarrassingly Parallely Parallel

NASA Parallel NASA Parallel Benchmarks Benchmarks suitesuite

SpeedupSpeedup = = 96%96%of theoretical of theoretical maximummaximum(on 10 nodes)(on 10 nodes)

Time, % of sequential

Efficiency,

% of theoretical

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Open TS vs MPI case Open TS vs MPI case studystudy Applications Applications

Open TS vs MPI case Open TS vs MPI case studystudy Applications Applications

Popular and widely used Popular and widely used Developed by independent teams (MPI Developed by independent teams (MPI

experts)experts)

PovRayPovRay – Persistence of Vision Ray- – Persistence of Vision Ray-tracer, enabled for parallel run by a tracer, enabled for parallel run by a patchpatch

ALCMD/MP_liteALCMD/MP_lite – molecular dynamics – molecular dynamics package (Ames Lab)package (Ames Lab)

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T-PovRay vs MPI PovRay: T-PovRay vs MPI PovRay: code complexitycode complexity

T-PovRay vs MPI PovRay: T-PovRay vs MPI PovRay: code complexitycode complexity

ProgramProgram Source code Source code volumevolume

MPI modules for MPI modules for PovRay 3.10gPovRay 3.10g

1,500 lines1,500 lines

MPI patch for MPI patch for PovRay 3.50cPovRay 3.50c

3,000 lines3,000 lines

T++ modules (for T++ modules (for both versions 3.10g & both versions 3.10g & 3.50c)3.50c)

200 lines200 lines

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T-PovRay vs MPI PovRay: T-PovRay vs MPI PovRay: performanceperformance

T-PovRay vs MPI PovRay: T-PovRay vs MPI PovRay: performanceperformance

90%100%110%120%130%140%150%160%170%180%190%200%210%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16Number of processors

Time MPI/Time OpenTS

2CPUs AMD Opteron 248 2.2 GHz RAM 4GB, GigE, LAM 7.1.1

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ALCMD/MPI vs ALCMD/MPI vs ALCMD/OpenTS ALCMD/OpenTS ALCMD/MPI vs ALCMD/MPI vs

ALCMD/OpenTS ALCMD/OpenTS MP_Lite component of ALCMD MP_Lite component of ALCMD

rewritten in T++rewritten in T++ Fortran code is left intact Fortran code is left intact

M PI

M PIM P_Lite

ALCMD

OpenTS

OpenTSM P_Lite

ALCMD

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ALCMD/MPI vs ALCMD/MPI vs ALCMD/OpenTS : ALCMD/OpenTS : code complexitycode complexity

ALCMD/MPI vs ALCMD/MPI vs ALCMD/OpenTS : ALCMD/OpenTS : code complexitycode complexity

ProgramProgram Source code Source code volumevolume

MP_Lite total/MPIMP_Lite total/MPI ~20,000 lines~20,000 lines

MP_Lite,ALCMD-MP_Lite,ALCMD-related/related/MPIMPI

~3,500 lines~3,500 lines

MP_Lite,ALCMD-MP_Lite,ALCMD-related/related/OpenTSOpenTS

500 lines500 lines

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ALCMD/MPI vs ALCMD/MPI vs ALCMD/OpenTS: ALCMD/OpenTS:

performanceperformance

ALCMD/MPI vs ALCMD/MPI vs ALCMD/OpenTS: ALCMD/OpenTS:

performanceperformance

80%

90%

100%

110%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16Number of processors

Time MPI/Time OpenTS

2CPUs AMD Opteron 248 2.2 GHz RAM 4GB, GigE, LAM 7.1.1, Lennard-Jones MD, 512000 atoms

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Т-Т-ApplicationsApplicationsТ-Т-ApplicationsApplications MultiGen – biological activity estimationMultiGen – biological activity estimation Remote sensing applicationsRemote sensing applications Plasma modelingPlasma modeling Protein simulationProtein simulation AeromechanicsAeromechanics Query engine for XMLQuery engine for XML AI-applicationsAI-applications etc.etc.

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ACKNOLEDGEMENTSACKNOLEDGEMENTSACKNOLEDGEMENTSACKNOLEDGEMENTS ““SKIF” supercomputing projectSKIF” supercomputing project Russian Academy of Science grantsRussian Academy of Science grants

Program “High-performance computing systems on Program “High-performance computing systems on new principles of computational process new principles of computational process organization” organization”

Program of Presidium of Russian Academy of Program of Presidium of Russian Academy of Science “Development of basics for implementation Science “Development of basics for implementation of distributed scientific informational-computational of distributed scientific informational-computational environment on GRID technologies”environment on GRID technologies”

Russian Foundation Basic Research “05-07-Russian Foundation Basic Research “05-07-08005-офи_а”08005-офи_а”

Microsoft – contract for “Open TS vs MPI” case Microsoft – contract for “Open TS vs MPI” case studystudy

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Program Systems Institute Russian Academy of Sciences

THANKS THANKS

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Open TS dynamic parallelization system

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