Superoptimization

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Superoptimization is the process where a compiler automatically finds the optimal sequence for a loop-free sequence of instructions. Real-world compilers generally cannot produce genuinely optimal code, and while most standard compiler optimizations only improve code partly, a superoptimizer's goal is to find the optimal sequence, the canonical form. Superoptimizers can be used to improve conventional optimizers by highlighting missed opportunities so a human can write additional rules.

Contents

History

The term superoptimization was first coined by Alexia Massalin in the 1987 paper Superoptimizer: A Look at the Smallest Program. [1] The label "program optimization" has been given to a field that does not aspire to optimize but only to improve. This misnomer forced Massalin to call her system a superoptimizer, which is actually an optimizer to find an optimal program. [2]

In 1992, the GNU Superoptimizer (GSO) was developed to integrate into the GNU Compiler Collection (GCC). [3] [4] Later work further developed and extended these ideas.

Techniques

Traditionally, superoptimizing is performed via exhaustive brute-force search in the space of valid instruction sequences. This is a costly method, and largely impractical for general-purpose compilers. Yet, it has been shown to be useful in optimizing performance-critical inner loops. It is also possible to use a SMT solver to approach the problem, vastly improving the search efficiency (although inputs more complex than a basic block remain out of reach). [5]

In 2001, goal-directed superoptimizing was demonstrated in the Denali project by Compaq research. [6] In 2006, answer set declarative programming was applied to superoptimization in the Total Optimisation using Answer Set Technology (TOAST) project [7] at the University of Bath. [8] [9]

Superoptimization can be used to automatically generate general-purpose peephole optimizers. [10]

Publicly available superoptimizers

Several superoptimizers are available for free download.

See also

References

  1. ↑ Massalin, Henry (1987). "Superoptimizer: A look at the smallest program" (PDF). ACM SIGARCH Computer Architecture News. 15 (5): 122–126. doi:10.1145/36177.36194 . Retrieved 2023-05-01. Given an instruction set, the superoptimizer finds the shortest program to compute a function. Startling programs have been generated, many of them engaging in convoluted bit-fiddling bearing little resemblance to the source programs which defined the functions. The key idea in the superoptimizer is a probabilistic test that makes exhaustive searches practical for programs of useful size.
  2. ↑ Joshi, Rajeev; Nelson, Greg; Randall, Keith (2002). "Denali: A Goal-directed Superoptimizer" . ACM SIGPLAN Notices. 37 (5): 304–314. doi:10.1145/543552.512566.
  3. 1 2 Granlund, Torbjörn; Kenner, Richard. "Eliminating branches using a superoptimizer and the GNU C compiler". Proceedings of the ACM SIGPLAN 1992 conference on Programming language design and implementation - PLDI '92. CiteSeerX   10.1.1.58.3509 . doi:10.1145/143095.14314 (inactive 2025-09-07). ISBN   978-0-89791475-8. S2CID   8825539.{{cite book}}: CS1 maint: DOI inactive as of September 2025 (link)
  4. 1 2 "Index of /gnu/superopt". GNU Operating System. Free Software Foundation, Inc. 1995-06-14. Retrieved 2023-05-01.
  5. 1 2 Jangda, Abhinav; Yorsh, Greta (2017-10-25). Unbounded superoptimization. Onward!’17, October 25–27, 2017, Vancouver, Canada. pp. 78–88. doi:10.1145/3133850.3133856.
  6. ↑ Joshi, Rajeev; Nelson, Greg; Randall, Keith (2001-07-30). "Denali: a goal-directed superoptimizer". Compaq Systems Research Center. HP Labs. Hewlett-Packard Co. Retrieved 2023-05-01.
  7. ↑ "TOAST – KRRwiki". Department of Computer Science, Mathematical Foundations Group. Knowledge Representation and Reasoning (KRR) group. University of Bath. 2007-08-07. Archived from the original on 2012-11-28. Retrieved 2016-09-03.
  8. ↑ Brain, Martin; Crick, Tom; De Vos, Marina; Fitch, John (2006-08-17). "TOAST: Applying Answer Set Programming to Superoptimisation". In Etalle, Sandro; Truszczyński, Mirosław (eds.). Logic Programming. Lecture Notes in Computer Science. Vol. 4079. Springer-Verlag. pp. 270–284. doi:10.1007/11799573_21. ISBN   978-3-540-36636-2.
  9. ↑ Crick, Tom (2009). Superoptimisation: Provably Optimal Code Generation using Answer Set Programming (PhD thesis). University of Bath. Retrieved 2024-11-15.
  10. ↑ Bansal, Sorav; Aiken, Alex (2006). "Automatic Generation of Peephole Superoptimizers" (PDF). Retrieved 2023-05-01.
  11. ↑ "GNU Superoptimizer".
  12. ↑ StanfordPL. "STOKE". GitHub .
  13. ↑ Bansal, Sorav; Aiken, Alex (2008). "Binary Translation Using Peephole Superoptimizers" (PDF). Retrieved 2023-05-01.
  14. ↑ Serpell, Daniel (2003). "SuperOptimizer for Microchip's PIC microcontrollers". Google Sites. Archived from the original on 2016-10-11. Retrieved 2016-09-06.
  15. ↑ Serpell, Daniel (2003-06-21). "PIC Microcontroller SuperOptimizer". Freecode. Slashdot Media. Archived from the original on 2016-09-17. Retrieved 2016-09-06.
  16. ↑ "A feasibility study by Embecosm".
  17. ↑ Superoptimization – Embecosm Source Code
  18. ↑ Hume, Tom (2012-08-21). "Clojure program to exhaustively search for optimal Java programs". GitHub. Archived from the original on 2018-06-10. Retrieved 2016-09-06.
  19. ↑ Sasnauskas, Raimondas; Chen, Yang; Collingbourne, Peter; Ketema, Jeroen; Lup, Gratian; Taneja, Jubi; Regehr, John (2017). "Souper: A Synthesizing Superoptimizer". arXiv: 1711.04422 [cs.PL]. GitHub source code
  20. ↑ Cabrera Arteaga, Javier; Donde, Shrinish; Gu, Jian; Floros, Orestis; Satabin, Lucas; Baudry, Benoit; Monperrus, Martin (2020-03-23). Superoptimization of WebAssembly bytecode. MoreVMs: Workshop on Modern Language Runtimes, Ecosystems, and VMs. pp. 36–40. arXiv: 2002.10213 . doi:10.1145/3397537.3397567. GitHub source code
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