Prototyping Fortran-90 compilers for massively parallel machines

Chen, Marina; Cowie, J. M. G.

doi:10.1145/143095.143122

Cited by 14 publications

(2 citation statements)

References 5 publications

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“…Many people have recognized the need to fuse loops generated by the scalarization of Fortran 90 array statements [2,6,13,16]. However, all of these only consider fusion after array statements have been scalarized.…”

Section: Related Workmentioning

confidence: 99%

Advanced Scalarization of Array Syntax

Roth

2000

Lecture Notes in Computer Science

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One task of all Fortran 90 compilers is to scalarize the array syntax statements of a program into equivalent sequential code. Most compilers require multiple passes over the program source to ensure correctness of this translation, since their analysis algorithms only work on the scalarized form. These same compilers then make additional subsequent passes to perform loop optimizations such as loop fusion. In this paper we discuss a strategy that is capable of making advanced scalarization and fusion decisions at the array level. We present an analysis strategy that supports our advanced scalarizer, and we describe the benefits of this methodology compared to the standard practice. Experimental results show that our strategy can significantly improve the runtime performance of compiled code, while at the same time improving the performance of the compiler itself.

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Section: Related Workmentioning

confidence: 99%

Advanced Scalarization of Array Syntax

Roth

2000

Lecture Notes in Computer Science

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“…A CRAFT SIMD compiler for CM-5 has been implemented [32]. The front-end and the intermediate modules have been adopted for the CRAFT MIMD compiler.…”

Section: The Craft Compilermentioning

confidence: 99%

CRAFT: a framework for F90/HPF compiler optimizations

Chen

Cowie

1999

Concurrency: Pract. Exper.

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In this paper, we give an overview of the results of the CRAFT optimising compiler project (Fortran 90/HPF subset compilers). We start by describing the theoretical framework within which we designed program transformations for the optimization of inter‐ and intra‐procedural data motion, as well as the optimizations for parallel loops; we then describe the implementation of the CRAFT compilers for Thinking Machines' CM‐2 and CM‐5. We report results from experiments on the Connection Machine CM‐5, the IBM SP‐2 and a network of UltraSparc workstations. The results demonstrate that these optimizations can achieve significant object code performance improvement. Copyright © 1999 John Wiley & Sons, Ltd.

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