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SUIF Criteria Conformance

Source code available

Source code is readily available via Internet anonymous FTP from Permission is explicitly granted in the copyright notice to modify the software for non-commercial purposes. No FSF-style ``copyleft'' conditions apply.

Widespread use.

SUIF is not in widespread use. Probably something on the order of several dozen sites have the SUIF compiler installed to play with it or to investigate possibly using it for a platform for research. SUIF's authors make it clear that they expect SUIF to remain a research platform; they assert that they do not plan to evolve SUIF into a production compiler --- it will never become a practical, general-purpose replacement for the native platform compiler.

Competitive performance.

The only backend code generator supplied with SUIF 1.0.1, for the MIPS architecture, achieves 70--90% of the performance of the commercial-available compilers on the MIPS platform for those SPEC92 benchmarks which it is able to compile with the scalar optimizer turned on. [] However, this statistic is obviated by the fact that I am using SUIF as a source-to-source compiler and compiling the resulting output with gcc. The run-time performance of gcc compiled code should be adequately competitive. (Also, a few incomplete trials suggest that the output source code of SUIF (used as a source-to-source compiler) when compiled by gcc performs only slightly worse than the original source code compiled by gcc.)


The SUIF 1.0.1 release does not explicitly delineate what platforms it is available for; however, the compiler and associated libraries appear to be quite portable. As mentioned previously, the only backend code generator is for the MIPS architecture; when used as a source-to-source compiler, the output from SUIF is ANSI C and thus quite portable.gif

Ease of modification.

Some of the features which SUIF has that makes it easy to modify and extend, and thus suitable for compiler research, include:

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Next: Profiling Mechanisms Up: Compiler Selection Details Previous: SUIF Output

Reinventing Computing, MIT AI Lab. Author: (Ping Huang)