Par4all: Auto-Parallelizing C and Fortran for the CUDA Architecture

More documents

Recommendations

Info

•Par4All ◮ (II) ◮ Interprocedural à la make engine to chain the phases as needed. Lazy construction of resources ◮ Polytope lattice (linear algebra) used for semantics analysis, transformations, code generation... to deal with big programs, not only loop-nests ◮ Huge on-going efforts to industrialize the project, extension of the semantics analysis for C • Around 15 programmers currently developing in PIPS (Mines ParisTech, HPC Project, IT SudParis, TÉLÉCOM Bretagne, RPI) with public svn, Trac, mailing lists, IRC, Plone, Skype... and use it for many projects • But still... ◮ Huge need of documentation (even if PIPS uses literate programming...) ◮ Need of industrialization ◮ Need further communication to increase community size �Par4All in CUDA — GPU conference 10/1/2009 � Par4All initiative HPC Project, Mines ParisTech, TÉLÉCOM Bretagne, RPI Ronan KERYELL et al. 8 / 46
•Par4All ◮ • Automatic parallelization (C & Fortran to OpenMP) • Distributed memory computing with OpenMP-to-MPI translation (STEP project) • Generic vectorization for SIMD instructions (SSE, VMX...) (SAC project) • Parallelization for embedded systems (SCALOPES) • Compilation for hardware accelerators (Ter@PIX, SPoC, SIMD, FPGA...) • High-level hardware accelerators synthesis generation for FPGA • Reverse engineering & decompiler (reconstruction from binary to C) Logical next stop GPU! � �Par4All in CUDA — GPU conference 10/1/2009 HPC Project, Mines ParisTech, TÉLÉCOM Bretagne, RPI Ronan KERYELL et al. 9 / 46
Page 1 and 2: • ◮ Par4All: Auto-Parallelizing
Page 3 and 4: •Introduction ◮ • Parallelize
Page 5 and 6: •Par4All ◮ 1 Par4All 2 CUDA gen
Page 7: •Par4All ◮ (I) • PIPS (Interp
Page 11 and 12: •CUDA generation ◮ 1 Par4All 2
Page 13 and 14: •CUDA generation ◮ • Find par
Page 15 and 16: •CUDA generation ◮ (I) Parallel
Page 17 and 18: •CUDA generation ◮ (I) • Memo
Page 19 and 20: •CUDA generation ◮ (I) Conserva
Page 21 and 22: •CUDA generation ◮ • Hardware
Page 23 and 24: •CUDA generation ◮ (II) • So
Page 25 and 26: •CUDA generation ◮ • Reductio
Page 27 and 28: •CUDA generation ◮ (II) • For
Page 29 and 30: •CUDA generation ◮ (I) • CUDA
Page 31 and 32: •CUDA generation ◮ (III) 21 [..
Page 33 and 34: •Results ◮ 1 Par4All 2 CUDA gen
Page 35 and 36: •Results ◮ (I) Average time in
Page 37 and 38: •Results ◮ (I) Average time in
Page 39 and 40: •Conclusion ◮ 1 Par4All 2 CUDA
Page 41 and 42: •Conclusion ◮ Why open source?
Page 43 and 44: •Conclusion ◮ (II) • We have
Page 45 and 46: •Conclusion ◮ (II) • Capitali
Page 47 and 48: •Conclusion ◮ • HPC Project

Par4all: Auto-Parallelizing C and Fortran for the CUDA Architecture

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?