1. Benchmarking and Applications

2. Purpose of Our Benchmarking Effort Reveal compiler (and run-time systems) weak points and lack of adequate automatic optimizations Quantify potential benefit from improvements –Against ideal behavior –Against other paradigms (e.g. MPI)

3. Strategy Develop hand optimizations that mimic the automatic optimizations Compare to compiler and run-time based optimizations

4. Possible optimizations under the UPC Model Privatization of local shared accesses Prefetching Aggregation Overlapping remote accesses with computations Low level optimized implementations of libraries (collective, I/O, other) Other

5. Applicable and easy to compare Privateization Aggregation and Prefetching Effect of low level optimized implementations under other paradigms (such as collective MPI calls)

6. Action Plan Matured applications and kernels should should be hosted on the main web site in a common area For a subgroup of the applications and kernels the following versions of the code should be made available by members of consortium –C –C or FORTRAN + MPI –UPC with no hand optimization –UPC with privatization optimization –UPC with privatization, perfecting and access aggregation –UPC with all optimizations possible

7. Action Plan cont. Producing Benchmarking results –C vs. C under UPC vs. UPC with one thread –Each hand optimized version against corresponding automatic optimizations from compiler and run-time –Fully hand optimized against MPI –Fully optimized (automatic) against MPI

8. Action Plan cont.: Programming Practices Groups should compile by SC 2002 observations on efficient UPC porting and programming methods –Start with C –Optimize single thread or parallelize and optimize parallel –Avoiding MPI bias and getting UPC benefit –Other

9. Action Plan cont.: Ease of Use Expressability for different problem domains –Data structures –Classic problems –Methods of parallelization Lines of codes for different problem domains Compare against HPF, MPI, OpenMP, Co-Array,.. etc Time to solution –To having a running parallel code –To having a tuned running parallel code

10. Action Plan cont.: Ease of use Strategy SC 2002, contest at booth SC 2003, conference level Worked examples

11. Action Plan cont.: Applications Micro benchmarks NAS SPLASH 2