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https://dx.doi.org/10.48550/ar...
Article . 2019
License: arXiv Non-Exclusive Distribution
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Compiling a Calculus for Relaxed Memory: Practical constraint-based low-level concurrency

Authors: Sullivan, Michael J.; Crary, Karl; Joshi, Salil;

Compiling a Calculus for Relaxed Memory: Practical constraint-based low-level concurrency

Abstract

Crary and Sullivan's Relaxed Memory Calculus (RMC) proposed a new declarative approach for writing low-level shared memory concurrent programs in the presence of modern relaxed-memory multi-processor architectures and optimizing compilers. In RMC, the programmer explicitly specifies constraints on the order of execution of operations and on the visibility of memory writes. These constraints are then enforced by the compiler, which has a wide degree of latitude in how to accomplish its goals. We present rmc-compiler, a Clang and LLVM-based compiler for RMC-extended C and C++. In addition to using barriers to enforce ordering, rmc-compiler can take advantage of control and data dependencies, something that is beyond the abilities of current C/C++ compilers. In rmc-compiler, RMC compilation is modeled as an SMT problem with a cost term; the solution with the minimum cost determines the compilation strategy. In testing on ARM and POWER devices, RMC performs quite well, with modest performance improvements relative to C++11 on most of our data structure benchmarks and (on some architectures) dramatic improvements on a read-mostly list test that heavily benefits from use of data dependencies for ordering.

Keywords

FOS: Computer and information sciences, Computer Science - Programming Languages, Programming Languages (cs.PL)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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