An affine partitioning algorithm to maximize parallelism and minimize communication
ICS '99 Proceedings of the 13th international conference on Supercomputing
SMARTS: exploiting temporal locality and parallelism through vertical execution
ICS '99 Proceedings of the 13th international conference on Supercomputing
Blocking and array contraction across arbitrarily nested loops using affine partitioning
PPoPP '01 Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming
Automatic Coarse Grain Task Parallel Processing on SMP Using OpenMP
LCPC '00 Proceedings of the 13th International Workshop on Languages and Compilers for Parallel Computing-Revised Papers
Proceedings of the Fourth International Workshop on Languages and Compilers for Parallel Computing
Coarse grain task parallel processing with cache optimization on shared memory multiprocessor
LCPC'01 Proceedings of the 14th international conference on Languages and compilers for parallel computing
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Effective use of cache memory is getting more important with increasing gap between the processor speed and memory access speed. Also, use of multigrain parallelism is getting more important to improve effective performance beyond the limitation of loop iteration level parallelism. Considering these factors, this paper proposes a coarse grain task static scheduling scheme considering cache optimization. The proposed scheme schedules coarse grain tasks to threads so that shared data among coarse grain tasks can be passed via cache after task and data decomposition considering cache size at compile time. It is implemented on OSCAR Fortran multigrain parallelizing compiler and evaluated on Sun Ultra80 four-processor SMP workstation, using Swim and Tomcatv from the SPEC fp 95. As the results, the proposed scheme gives us 4.56 times speedup for Swim and 2.37 times on 4 processors for Tomcatv respectively against the Sun Forte HPC 6 loop parallelizing compiler.