Abstract
We propose a new universal High-Level Information (HLI) format to effectively integrate front-end and back-end compilers by passing front-end information to the back-end compiler. Importing this information into an existing back-end leverages the state-of-the-art analysis and transformation capabilities of existing front-end compilers to allow the back-end greater optimization potential than it has when relying on only locally-extracted information. A version of the HLI has been implemented in the SUIF parallelizing compiler and the GCC back-end compiler. Experimental results with the SPEC benchmarks show that HLI can provide GCC with substantially more accurate data dependence information than it can obtain on its own. Our results show that the number of dependence edges in GCC can be reduced by an average of 48% for the integer benchmark programs and an average of 54% for the floating-point benchmark programs studied, which provides greater flexibility to GCC's code scheduling pass. Even with the scheduling optimization limited to basic blocks, the use of HLI produces moderate speedups compared to using only GCC's dependence tests when the optimized programs are executed on MIPS R4600 and R10000 processors.
Original language | English (US) |
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Title of host publication | Proceedings - 1998 International Conference on Parallel Processing, ICPP 1998 |
Editors | Ten H. Lai |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 346-355 |
Number of pages | 10 |
ISBN (Electronic) | 0818686502 |
DOIs | |
State | Published - 1998 |
Event | 1998 International Conference on Parallel Processing, ICPP 1998 - Minneapolis, United States Duration: Aug 10 1998 → Aug 14 1998 |
Publication series
Name | Proceedings of the International Conference on Parallel Processing |
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ISSN (Print) | 0190-3918 |
Other
Other | 1998 International Conference on Parallel Processing, ICPP 1998 |
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Country/Territory | United States |
City | Minneapolis |
Period | 8/10/98 → 8/14/98 |
Bibliographical note
Funding Information:This work was supported in part by the National Science Foundation under grant nos. MIP-9610379 and CDA-9502979; by the U.S. Army Intelligence Center and Fort Huachuca under contract DABT63-95-C-0127 and ARPA order no. D346, and a gift from the Intel Corporation. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Army Intelligence Center and Fort Huachuca, or the U.S. Government. Stephen Schwinn is currently with the IBM Corp., Rochester, MN.
Publisher Copyright:
© 1998 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.