Title: UPC at CRDLBNL
1UPC at CRD/LBNL
- Kathy Yelick
- Dan Bonachea, Jason Duell, Paul Hargrove, Parry
Husbands, Costin Iancu, Mike Welcome, Christian
Bell
2What 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
p0
p1
p2
3Background
- UPC efforts elsewhere
- IDA Bill Carlson, UPC promoter
- GMU (documentation) and UMC (benchmarking)
- HP (Alpha cluster and CMPI 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
- Compilers for DOE machines (SP and PC clusters)
- Runtime systems for ours and other compilers
- Applications and benchmarks
4UPC 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
5Compiler 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
6UPC Compiler
- 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
UPC
Higher WHIRL
Optimizing transformations
C Runtime
Lower WHIRL
Assembly IA64, MIPS, Runtime
7Portable Runtime Support
- Developing a runtime layer that can be easily
ported and tuned to multiple architectures.
Direct implementations of parts of full GASNet
Runtime Global pointers (opaque type with rich
set of pointer operations), memory management,
job startup, etc.
Generic support for UPC, CAF, Titanium
GASNet Extended API Supports put, get, locks,
barrier, bulk, scatter/gather
GASNet Core API Small interface based on
Active Messages
Core sufficient for functional implementation
GASNet released 1/03
8Communication Optimizations
- Characterizing performance of current machines
- Latency, overlap (communication computation)
- Plan to automatically optimization using
communication performance model - Preliminary results 10x improvement on Matmul
9Performance without Communication
10Preliminary Parallel Performance
11Costs 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
12Applications
- 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
13Mesh 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
14Summary
- 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 (?)
15Future 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