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Compilation framework for code size reduction using reduced bit-width ISAs (rISAs)
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Source ACM Transactions on Design Automation of Electronic Systems (TODAES) archive
Volume 11 ,  Issue 1  (January 2006) table of contents
Pages: 123 - 146  
Year of Publication: 2006
ISSN:1084-4309
Authors
Aviral Shrivastava  University of California, Irvine, Irvine, CA
Partha Biswas  University of California, Irvine, Irvine, CA
Ashok Halambi  University of California, Irvine, Irvine, CA
Nikil Dutt  University of California, Irvine, Irvine, CA
Alex Nicolau  University of California, Irvine, Irvine, CA
Publisher
ACM  New York, NY, USA
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ABSTRACT

For many embedded applications, program code size is a critical design factor. One promising approach for reducing code size is to employ a “dual instruction set”, where processor architectures support a normal (usually 32-bit) Instruction Set, and a narrow, space-efficient (usually 16-bit) Instruction Set with a limited set of opcodes and access to a limited set of registers. This feature however, requires compilers that can reduce code size by compiling for both Instruction Sets. Existing compiler techniques operate at the routine-level granularity and are unable to make the trade-off between increased register pressure (resulting in more spills) and decreased code size. We present a compilation framework for such dual instruction sets, which uses a profitability based compiler heuristic that operates at the instruction-level granularity and is able to effectively take advantage of both Instruction Sets. We demonstrate consistent and improved code size reduction (on average 22%), for the MIPS 32/16 bit ISA. We also show that the code compression obtained by this “dual instruction set” technique is heavily dependent on the application characteristics and the narrow Instruction Set itself.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Aviral Shrivastava: colleagues
Partha Biswas: colleagues
Ashok Halambi: colleagues
Nikil Dutt: colleagues
Alex Nicolau: colleagues