Work-Efficient Nested Data-Parallelism (1995)
| Venue: | IN PROCEEDINGS OF THE FIFTH SYMPOSIUM ON THE FRONTIERS OF MASSIVELY PARALLEL PROCESSING (FRONTIERS 95). IEEE |
| Citations: | 19 - 3 self |
BibTeX
@INPROCEEDINGS{Palmer95work-efficientnested,
author = {Daniel W. Palmer and Jan F. Prins and Stephen Westfold},
title = {Work-Efficient Nested Data-Parallelism},
booktitle = {IN PROCEEDINGS OF THE FIFTH SYMPOSIUM ON THE FRONTIERS OF MASSIVELY PARALLEL PROCESSING (FRONTIERS 95). IEEE},
year = {1995},
pages = {186--193},
publisher = {IEEE}
}
Bookmark
 |
 |
 |
 |
 |
 |
OpenURL
Abstract
An apply-to-all construct is the key mechanism for expressing data-parallelism, but data-parallel programming languages like HPF and C* significantly restrict which operations can appear in the construct. Allowing arbitrary operations substantially simplifies the expression of irregular and nested data-parallel computations. The technique of flattening nested parallelism introduced by Blelloch, compiles data-parallel programs with unrestricted apply-to-all constructs into vector operations, and has achieved notable success, particularly with irregular data-parallel programs. However, these programs must be carefully constructed so that flattening them does not lead to suboptimal work complexity due to unnecessary replication in index operations. We present new flattening transformations that generate programs with correct work complexity. Because these transformations may introduce concurrent reads in parallel indexing, we developed a randomized indexing that reduces concurrent reads w...
