An ILP-Based Approach to Code Generation

Wilson, Thomas C.; Gréwal, Gary; Henshall, Shawn; Banerji, D.

doi:10.1007/978-1-4615-2323-9_6

Cited by 15 publications

(12 citation statements)

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“…This abstraction is exploited to generate spill code and register-to-register copies, and to select array addressing instructions. Unfortunately, the publications by Wilson et al [20,21] do not provide enough detail to determine to which extent alternative temporaries and alternative implementations are related.…”

Section: Related Workmentioning

confidence: 96%

Combinatorial spill code optimization and ultimate coalescing

Lozano

Carlsson

Blindell

et al. 2014

Proceedings of the 2014 SIGPLAN/SIGBED Conference on Languages, Compilers and Tools for Embedded Systems

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This paper presents a novel combinatorial model that integrates global register allocation based on ultimate coalescing, spill code optimization, register packing, and multiple register banks with instruction scheduling (including VLIW). The model exploits alternative temporaries that hold the same value as a new concept for ultimate coalescing and spill code optimization.The paper presents Unison as a code generator based on the model and advanced solving techniques using constraint programming. Thorough experiments using MediaBench and a processor (Hexagon) that are typical for embedded systems demonstrate that Unison: is robust and scalable; generates faster code than LLVM (up to 41% with a mean improvement of 7%); possibly generates optimal code (for 29% of the experiments); effortlessly supports different optimization criteria (code size on par with LLVM).Unison is significant as it addresses the same aspects as traditional code generation algorithms, yet is based on a simple integrated model and robustly can generate optimal code.

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Section: Related Workmentioning

confidence: 96%

Combinatorial spill code optimization and ultimate coalescing

Lozano

Carlsson

Blindell

et al. 2014

Proceedings of the 2014 SIGPLAN/SIGBED Conference on Languages, Compilers and Tools for Embedded Systems

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“…Alternative temporaries are related to Colombet et al's local equivalence classes [31] in their definition and targeted program transformations, and to Wilson et al's alternative implementations [101,102] in their way of extending the original program representation with implementation choices to be considered by a solver.…”

Section: Spilling Live Range Splitting and Coalescingmentioning

confidence: 99%

Combinatorial Register Allocation and Instruction Scheduling

Lozano

Carlsson

Blindell

et al. 2019

ACM Trans. Program. Lang. Syst.

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This paper introduces a combinatorial optimization approach to register allocation and instruction scheduling, two central compiler problems. Combinatorial optimization has the potential to solve these problems optimally and to exploit processor-specific features readily. Our approach is the first to leverage this potential in practice: it captures the complete set of program transformations used in state-of-the-art compilers, scales to mediumsized functions of up to 1000 instructions, and generates executable code. This level of practicality is reached by using constraint programming, a particularly suitable combinatorial optimization technique. Unison, the implementation of our approach, is open source, used in industry, and integrated with the LLVM toolchain.An extensive evaluation confirms that Unison generates better code than LLVM while scaling to mediumsized functions. The evaluation uses systematically selected benchmarks from MediaBench and SPEC CPU2006 and different processor architectures (Hexagon, ARM, MIPS). Mean estimated speedup ranges from 1.1% to 10% and mean code size reduction ranges from 1.3% to 3.8% for the different architectures. A significant part of this improvement is due to the integrated nature of the approach. Executing the generated code on Hexagon confirms that the estimated speedup results in actual speedup. Given a fixed time limit, Unison solves optimally functions of up to 946 instructions, nearly an order of magnitude larger than previous approaches.The results show that our combinatorial approach can be applied in practice to trade compilation time for code quality beyond the usual compiler optimization levels, identify improvement opportunities in heuristic algorithms, and fully exploit processor-specific features. This paper is partially based on preliminary work presented at the Principles and Practice of Constraint Programming (2012) [20]; Languages, Compilers, and Tools for Embedded Systems (2014) [21]; and Compiler Construction (2016) [22] conferences. Compared to the preliminary work, this paper is completely restructured and rewritten, completes the combinatorial model with rematerialization, proposes extensions to capture additional program transformations and processor-specific features, and contributes a more exhaustive evaluation. Additions to the evaluation include more benchmarks and processors, evidence of the fundamental benefit of the integrated approach, an in-depth study of scalability, and actual execution measurements.

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“…Wilson's ILP based code generator The Integer Linear Programming (ILP) approach by Wilson et al [190,191] aims at phase-coupled code generation for irregular architectures. The main idea is to transform the code generation problem as a whole into some well-known optimization problem, ILP, for which efficient solvers already exist.…”

Section: 15mentioning

confidence: 99%

Retargetable Compiler Technology for Embedded Systems

Leupers

Marwedel

2001

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An ILP-Based Approach to Code Generation

Cited by 15 publications

References 0 publications

Combinatorial spill code optimization and ultimate coalescing

Combinatorial spill code optimization and ultimate coalescing

Combinatorial Register Allocation and Instruction Scheduling

Retargetable Compiler Technology for Embedded Systems

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