UPC at CRD/LBNL Kathy Yelick Dan Bonachea, Jason Duell, Paul Hargrove, Parry Husbands, Costin Iancu, Mike Welcome, Christian Bell

What is UPC? UPC is an explicitly parallel language –Global address space; can read/write remote memory –Programmer control over layout and scheduling –From Split-C, AC, PCP Why a new language? –Easier to use than MPI, especially for program with complicated data structures –Possibly faster on some machines, but current goal is comparable performance p0p1p2

Background UPC efforts elsewhere –IDA: Bill Carlson, UPC promoter –GMU (documentation) and UMC (benchmarking) –HP (Alpha cluster and C+MPI compiler (with MTU)) –Cray (implementations) –Intrepid (SGI and t3e compiler) UPC Book: –T. El-Ghazawi, B. Carlson, T. Sterling, K. Yelick –3 chapters in draft form; goal is to have proofs by SC03 Three components of NERSC effort 1)Compilers for DOE machines (SP and PC clusters) 2)Runtime systems for ours and other compilers 3)Applications and benchmarks

UPC Funding Base program funding K52004 –Compiler/translator work –Applications –Runtime for DOE machines Part of Pmodels Center K52018 –Runtime support common to Titanium (and hopefully CoArray Fortran, at some point) –Collaboration with ARMCI group NSA funding –UPC for “clusters”

Compiler Status NERSC compiler/translator –Costin Iancu and Wei Chen –Translates UPC to C + “Berkeley UPC Runtime” –Based on Open64 compiler for C –Status Complete in prototype form Debugging, tuning, extensions ongoing Release planned for next month: –Quadrics, Myrinet, IBM/SP, and MPI Shared memory/process implementation is next –Investigating optimization opportunities Communication optimizations UPC language optimizations

UPC Compiler UPC Higher WHIRL Lower WHIRL Compiler based on Open64 Multiple front-ends, including gcc Intermediate form called WHIRL Leverage standard optimizations and analyses Pointer analysis Loop optimizations Current focus on C backend IA64 possible in future UPC Runtime built on GASNet Portable Language-independent Optimizing transformations C + Runtime Assembly: IA64, MIPS,… + Runtime

Runtime: Global pointers (opaque type with rich set of pointer operations), memory management, job startup, etc. GASNet Extended API: Supports put, get, locks, barrier, bulk, scatter/gather Portable Runtime Support Developing a runtime layer that can be easily ported and tuned to multiple architectures. GASNet Core API: Small interface based on “Active Messages” Generic support for UPC, CAF, Titanium Core sufficient for functional implementation Direct implementations of parts of full GASNet GASNet released 1/03

Communication Optimizations Characterizing performance of current machines –Latency, overlap (communication & computation) Plan to automatically optimization using communication performance model Preliminary results: 10x improvement on Matmul

Performance without Communication

Preliminary Parallel Performance

Costs of Pointer-to-Shared Arithmetic – Berkeley vs. HP HP is faster for most operations, since HP generates assembly code Both compilers optimize for “phaseless” pointers For some operations, Berkeley can beat the HP (ptr comparison) Expect gap to narrow once the proper optimizations are built-in for Berkeley UPC

Applications NAS Parallel Benchmark Sized Apps –UPC MG complete –UPC CG complete –UPC GUPS –GWU has done IS, EP, and FT Planning on –Several Splash benchmarks –Sparse Cholesky –Possibly AMR

Mesh Generation Parallel Mesh Generation in UPC 2D Delaunay triangulation Based on Triangle software by Shewchuk (UCB) Parallel version from NERSC uses dynamic load balancing, software caching, and parallel sorting

Summary Lots of progress on –Compiler –Runtime –Portable communication layer (GASNet) –Applications Working on developing a large application that depends on UPC –Mesh generation –AMR (?), Sparse LU (?)

Future Plans Runtime support for Intrepid –Gcc-based open source compiler Performance tuning of runtime –Additional machines (Infiniband, X1, Dolphin) Optimization of compiled code –Communication optimizations –Automatic search-based optimizations Application efforts