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Patterns for Parallel Programming Semantic Scholar
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UCB s Par Lab Research Overview, Easy to write correct software that runs efficiently on manycore. s Personal Image Hearing Parallel, o n Speech, ati Health Retrieval Music Browser. p lic Design Pattern Language, Composition Coordination Language C CL Static. i ty Verification, ti v C CL Compiler Interpreter, Pr Laye Type. Correctness, Parallel Parallel, Libraries Frameworks Systems.
Efficiency Directed, ncy Languages Testing, i cie r Autotuners. Eff aye Legacy Communication Dynamic, Schedulers, Synch Primitives Checking. Efficiency Language Compilers, OS Libraries Services. OS Legacy OS Hypervisor, with Replay, A rc Intel Multicore GPGPU RAMP Manycore. Our goal use the patterns to guide us to, the right frameworks.
1 Application End user, Domain Experts, patterns application. frameworks programs, 2 Domain literate Parallel Application. programming gurus 1 of patterns frameworks, the population programming. frameworks, 3 Parallel, Parallel programming gurus 1 10 of programming. programmers frameworks, The hope is for Domain Experts to create parallel code with little or no.
understanding of parallel programming, Leave hardcore bare metal efficiency layer programming to the parallel. programming experts, But this is a course on parallel programming languages. I have something much more important to talk to you. about than patterns, besides Kurt Keutzer or I can always come back. and talk about patterns any time you want, Programmability and the Parallel. Programming Problem, Tim Mattson Intel, Computing with 100s or 1000s of cores is not.
new Intel has been doing it for decades, ASCI Option Red. iPSC 2 shipped Delta shipped fastest ASCI Red World s. Scientific, computer in the world First TFLOP, iPSC 860 shipped Paragon shipped ASCI Red upgrade Regains. iPSC 1 Wins Gordon Bell Breaks Delta records title as the world s fastest. shipped prize computer, Source Intel, The result membership in the Dead. Architecture Society, Memory Encore, MIMD Sequent, Myrias Parallel Computing. Distributed Intel SSD, Memory BBN, Workstation PC clusters.
Thinking machines, Denelcore HEP, Tera MTA now Cray. 1980 1990 2000, Any product names on this slide are the property of their owners 7. What went wrong Software, Parallel systems are useless without parallel software. Can we generate parallel software automatically, NO After years of trying we know it just doesn t work. Our only hope is to get programmers to create parallel software. But after 25 years of research we are no closer to solving. the parallel programming problem, Only a tiny fraction of programmers write parallel code.
Will the if you build it they will come principle apply. Many hope so but, that implies that people didn t really try hard enough over the last. 25 years Does that really make sense, All you need is a good Parallel Programming. Language right, Parallel Programming environments in the 90 s. ABCPL CORRELATE GLU Mentat Parafrase2, ACE CPS GUARD Legion Paralation pC. ACT CRL HAsL Meta Chaos Parallel C SCHEDULE, Active messages CSP Haskell Midway Parallaxis SciTL.
Adl Cthreads HPC Millipede ParC POET, Adsmith CUMULVS JAVAR CparPar ParLib SDDA. ADDAP DAGGER HORUS Mirage ParLin SHMEM, AFAPI DAPPLE HPC MpC Parmacs SIMPLE. ALWAN Data Parallel C IMPACT MOSIX Parti Sina, AM DC ISIS Modula P pC SISAL. AMDC DCE JAVAR Modula 2 pC distributed smalltalk, AppLeS DDD JADE Multipol PCN SMI. Amoeba DICE Java RMI MPI PCP SONiC, ARTS DIPC javaPG MPC PH Split C.
Athapascan 0b DOLIB JavaSpace Munin PEACE SR, Aurora DOME JIDL Nano Threads PCU Sthreads. Automap DOSMOS Joyce NESL PET Strand, bb threads DRL Khoros NetClasses PETSc SUIF. Blaze DSM Threads Karma Nexus PENNY Synergy, BSP Ease KOAN Fortran S Nimrod Phosphorus Telegrphos. BlockComm ECO LAM NOW POET SuperPascal, C Eiffel Lilac Objective Linda Polaris TCGMSG. C in C Eilean Linda Occam POOMA Threads h, C Emerald JADA Omega POOL T TreadMarks.
CarlOS EPL WWWinda OpenMP PRESTO TRAPPER, Cashmere Excalibur ISETL Linda Orca P RIO uC. C4 Express ParLin OOF90 Prospero UNITY, CC Falcon Eilean P Proteus UC. Chu Filaments P4 Linda P3L QPC V, Charlotte FM Glenda p4 Linda PVM ViC. Charm FLASH POSYBL Pablo PSI Visifold V NUS, Charm The FORCE Objective Linda PADE PSDM VPE. Cid Fork LiPS PADRE Quake Win32 threads, Cilk Fortran M Locust Panda Quark WinPar.
CM Fortran FX Lparx Papers Quick Threads WWWinda, Converse GA Lucid AFAPI Sage XENOOPS. Code GAMMA Maisie Para SCANDAL XPC, COOL Glenda Manifold Paradigm SAM Zounds. Third party names are the property of their owners 9. All you need is a good Parallel Programming, Language right. Parallel Programming environments in the 90 s, ABCPL CORRELATE GLU Mentat Parafrase2. ACE CPS GUARD Legion Paralation pC, ACT CRL HAsL Meta Chaos Parallel C SCHEDULE.
Active messages CSP Haskell Midway Parallaxis SciTL. Adl Cthreads HPC Millipede ParC POET, Adsmith CUMULVS JAVAR CparPar ParLib SDDA. ADDAP DAGGER HORUS Mirage ParLin SHMEM, AFAPI DAPPLE HPC MpC Parmacs SIMPLE. ALWAN Data Parallel C IMPACT MOSIX Parti Sina, AM DC ISIS Modula P pC SISAL. Before creating any new languages maybe we should, distributed smalltalk. Amoeba DICE Java RMI MPI PCP, figure out why parallel programming language research.
Athapascan 0b, Aurora DOME JIDL Nano Threads PCU, been so unproductive. bb threads, NetClasses, Blaze DSM Threads Karma Nexus PENNY. BSP Ease KOAN Fortran S Nimrod Phosphorus Telegrphos. Maybe part of the problem is how we compare, BlockComm ECO LAM NOW POET SuperPascal. C Eiffel Lilac Objective Linda Polaris TCGMSG, C in C Eilean Linda Occam POOMA Threads h. programming languages, C Emerald JADA Omega POOL T TreadMarks.
CarlOS EPL WWWinda OpenMP PRESTO TRAPPER, Cashmere Excalibur ISETL Linda Orca P RIO uC. C4 Express ParLin OOF90 Prospero UNITY, CC Falcon Eilean P Proteus UC. Chu Filaments P4 Linda P3L QPC V, Charlotte FM Glenda p4 Linda PVM ViC. Charm FLASH POSYBL Pablo PSI Visifold V NUS, Charm The FORCE Objective Linda PADE PSDM VPE. Cid Fork LiPS PADRE Quake Win32 threads, Cilk Fortran M Locust Panda Quark WinPar.
CM Fortran FX Lparx Papers Quick Threads WWWinda, Converse GA Lucid AFAPI Sage XENOOPS. Code GAMMA Maisie Para SCANDAL XPC, COOL Glenda Manifold Paradigm SAM Zounds. Third party names are the property of their owners 10. Comparing programming languages Ct and OpenMP, void smvp csr double 3x3mat double3vec dst. Nested Data Parallel, double3x3mat A, double3vec v. int height, int nonzeros, int numThreads, void pattern.
VEC double sparseMatrixVectorProduct, double3vec scratch. int scratch int, double3vec scratch1 scratch, double3vec scratch2 scratch MAX nonzeros height. double3vec scratch3 scratch MAX nonzeros height 2, int scratch icast int scratch. int baseStripSize nonzeros numThreads, int leftoverStripSize nonzeros numThreads. double3vec incomingarr MAXPRIMTHREADS, int incomingseg MAXPRIMTHREADS.
int incomingsegs MAXPRIMTHREADS, VEC double A VEC int rowindex. int segflags multipattern pattern segdesc, int incomingarr int MAXPRIMTHREADS. pragma omp parallel num threads numThreads, ifdef OPENMP. int threadId omp get thread num, int threadId 0, int lowerBound threadId baseStripSize threadId leftoverStripSize threadId leftoverStripSize. int upperBound threadId 1 baseStripSize threadId 1 leftoverStripSize threadId 1 leftoverStripSize. VEC int cols VEC double v, double3vec incoming, int incomingsgs 0.
int frontier, int seghits 0, int seghit segflags lowerBound. int incoming int 0, incoming 0 0 0, incoming 1 0 0. incoming 2 0 0, if upperBound nonzeros segflags upperBound. Fused Local Phase 1 Inner Product Local Reduction, matrixvector3x3x1 multiply scratch1 lowerBound A lowerBound v cind lowerBound. for elt lowerBound 1 elt upperBound elt nonzeros elt. if segflags elt, matrixvector3x3x1 multiply scratch1 elt A elt v cind elt.
seghit TRUE, matrixvector3x3x1 multiply scratch1 elt A elt v cind elt. vector3x1 add scratch2 elt scratch2 elt 1 scratch1 elt 1. VEC expv distribute v cols, SegReduction Global Phase. pragma omp barrier, incomingsegs threadId seghits, incomingseg threadId seghit. if threadId, vector3x1 add incomingarr threadId scratch2 lowerBound 1 scratch1 lowerBound 1. incomingarr threadId 0 0, VEC product A expv, incomingarr threadId 1 0.
incomingarr threadId 2 0, incoming 0 incomingarr threadId 0. incoming 1 incomingarr threadId 1, incoming 2 incomingarr threadId 2. incomingsgs incomingsegs threadId, seghit FALSE, pragma omp barrier. frontier 1, while frontier numThreads, if threadId frontier. return multiReduceSum product rowindex, if incomingseg threadId frontier seghit.
vector3x1 add incoming incomingarr threadId incomingarr threadId frontier. incomingsgs incomingsegs threadId incomingsegs threadId frontier. if incomingseg threadId frontier, seghit TRUE, frontier 1. pragma omp barrier, incomingarr threadId 0 incoming 0. incomingarr threadId 1 incoming 1, incomingarr threadId 2 incoming 2. incomingsegs threadId incomingsgs, pragma omp barrier. seghit segflags lowerBound, incomingsgs threadId incomingsegs threadId 1 0.
for elt lowerBound elt upperBound elt nonzeros elt. if elt nonzeros 1 segflags elt 1, vector3x1 addinplace scratch3 incomingsgs incomingarr threadId. vector3x1 addinplace scratch3 incomingsgs scratch2 elt. vector3x1 addinplace scratch3 incomingsgs scratch1 elt. vector3x1 addinplace scratch3 incomingsgs scratch2 elt. vector3x1 addinplace scratch3 incomingsgs scratch1 elt. incomingsgs, seghit TRUE, baseStripSize height numThreads. leftoverStripSize height numThreads, lowerBound threadId baseStripSize threadId leftoverStripSize threadId leftoverStripSize. upperBound threadId 1 baseStripSize threadId 1 leftoverStripSize threadId 1 leftoverStripSize. int scratch2 lowerBound 0, scratch icast upperBound 1 rows upperBound 1 rows upperBound 0 1. for elt lowerBound 1 elt upperBound elt height elt. scratch icast elt 1 rows elt 1 rows elt 0 1, int scratch2 elt int scratch2 elt 1 scratch icast elt 1.
6 lines of code, pragma omp barrier, if threadId, incomingarr int threadId int scratch2 lowerBound 1 scratch icast lowerBound 1. incomingarr int threadId 0, pragma omp barrier, incoming int incomingarr int threadId. frontier 1, while frontier numThreads, if threadId frontier. incoming int incomingarr int threadId frontier, frontier 1. pragma omp barrier, incomingarr int threadId incoming int.
pragma omp barrier, int scratch2 upperBound 1 incomingarr int threadId. Better performance scalability, pragma omp barrier. if threadId, incomingarr int threadId int scratch2 lowerBound 1 scratch icast lowerBound 1 barrier above guarantees the dst isn t read until after it s updated. for elt lowerBound elt upperBound 1 elt height elt. int scratch2 elt incomingarr int threadId, if scratch icast elt. vector3x1 copy dst elt scratch3 int scratch2 elt, if scratch icast upperBound 1.
vector3x1 copy dst upperBound 1 scratch3 int scratch2 upperBound 1. else threadId 0, for elt lowerBound elt upperBound elt height elt. if scratch icast elt, vector3x1 copy dst elt scratch3 int scratch2 elt. parallel region, 172 lines of code, Nested data, data parallelism. parallelism enables, enables safe, and scalable, composition. composition of, of software, software modules, What conceptually does this comparison tell us Anything.
Isn t this just marketing speak disguised as reasoned analysis. Win32 API vs OpenMP Which would you rather use, include windows h. define NUM THREADS 2, HANDLE thread handles NUM THREADS. CRITICAL SECTION hUpdateMutex, static long num steps 100000. double step, double global sum 0 0, void Pi void arg. include omp h, int i start, double x sum 0 0, static long num steps 100000 double step.
int i double x pi sum 0 0, start int arg, step 1 0 double num steps. for i start i num steps i i NUM THREADS, x i 0 5 step step 1 0 double num steps. sum sum 4 0 1 0 x x, EnterCriticalSection hUpdateMutex. pragma omp parallel for reduction sum private x, global sum sum. LeaveCriticalSection hUpdateMutex for i 1 i num steps i. x i 0 5 step, double pi int i, DWORD threadID, int threadArg NUM THREADS.
sum sum 4 0 1 0 x x, for i 0 i NUM THREADS i threadArg i i 1. InitializeCriticalSection hUpdateMutex pi step sum. for i 0 i NUM THREADS i, thread handles i CreateThread 0 0 OpenMP. LPTHREAD START ROUTINE Pi, threadArg i 0 threadID, WaitForMultipleObjects NUM THREADS. thread handles TRUE INFINITE, pi global sum step, isaacomparison. comparisonII, printf pi is f n pi often, OpenMPtalks.
Win32 Threads, Comparing programming languages APIs. If we are going to make progress on the parallel programming. problem we must stop taking pot shots at each other and stop acting. like marketers, We need to objectively compare parallel programming languages. Categorize the way people work with parallel programming. languages and use those categories to evaluate different. Define A common terminology for aspects of programmability. Create a set of useful programmability benchmarks

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