Title :
Supporting data-level and processor-level parallelism in data-parallel programming languages
Author :
Hatcher, FMip J. ; Quinn, Michael J.
Author_Institution :
Dept. of Comput. Sci., New Hampshire Univ., NH, USA
Abstract :
The dataparallel C and C* languages do not allow the programmer to express both data-level and processor-level parallelism. Instead, the programmer must choose between them. Choosing data-level parallelism prevents the programmer from applying efficient sequential algorithms to data aggregates and causes unacceptable performance. Choosing processor-level parallelism forces the programmer to sequentialize fundamentally parallel data permutation or reduction operations through the use of `for´ loops. The authors give several prototypical examples that demonstrate how data-parallel algorithms can exhibit both data-level and processor-level parallelism. They suggest several ways that data-parallel programming languages or their compilers could be extended to support both kinds of parallelism, and discuss the advantages and disadvantages of each approach
Keywords :
parallel languages; parallel programming; program compilers; compilers; data-level parallelism; data-parallel programming languages; dataparallel C; parallel data permutation; processor-level parallelism; Aggregates; Application software; Atmospheric modeling; Computer languages; Computer science; Parallel processing; Parallel programming; Program processors; Programming profession; Prototypes;
Conference_Titel :
System Sciences, 1993, Proceeding of the Twenty-Sixth Hawaii International Conference on
Conference_Location :
Wailea, HI
Print_ISBN :
0-8186-3230-5
DOI :
10.1109/HICSS.1993.284056