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Practical issues in the flattening of nested parallelism with program transformations (1995).
| Content Provider | CiteSeerX |
|---|---|
| Author | Faith, Rickard E. Palmer, Daniel W. Prins, Jan F. Nyland, Lars S. |
| Abstract | ) Rickard E. Faith Daniel W. Palmer Jan F. Prins Lars S. Nyland February 10, 1995 Abstract The "flattening" of nested data-parallelism reduces a very broad class of data-parallel expressions to parallel vector operations. The technique can be understood as the application of a small set of program transformations. In this paper, we explore several practical issues involved in the implementation of these transformations, with an emphasis on the production of optimized vector code. 1 Introduction A notation supports the expression of data parallelism if it includes aggregate values such as arrays or sequences and an apply-to-all construct that applies operations to all elements of an aggregate. However, data-parallel languages such as HPF and C restrict aggregates to rectangular arrays, thereby limiting the ability to specify and execute the irregular and dynamic data-parallelism that is key to the efficient solution of many problems. With the introduction of nested aggregates, a fu... |
| File Format | |
| Publisher Date | 1995-01-01 |
| Access Restriction | Open |
| Subject Keyword | Program Transformation Practical Issue Nested Parallelism Data-parallel Language Broad Class Nyland February Many Problem Data Parallelism Dynamic Data-parallelism Nested Aggregate Small Set Apply-to-all Construct Aggregate Value Palmer Jan Efficient Solution Prins Lars Data-parallel Expression Nested Data-parallelism Reduces Vector Operation Several Practical Issue Optimized Vector Code Faith Daniel |
| Content Type | Text |
