Polyhedral parallelization of binary code - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles ACM Transactions on Architecture and Code Optimization Year : 2012

Polyhedral parallelization of binary code


Many automatic software parallelization systems have been proposed in the past decades, but most of them are dedicated to source-to-source transformations. This paper shows that parallelizing executable programs is feasible, even if they require complex transformations, and in effect decouples parallelization from compilation, for example, for closed-source or legacy software, where binary code is the only available representation. We propose an automatic parallelizer, which is able to perform advanced parallelization on binary code. It first parses the binary code and extracts high-level information. From this information, a C program is generated. This program captures only a subset of the program semantics, namely, loops and memory accesses. This C program is then parallelized using existing, state-of-the-art parallelizers, including advanced polyhedral parallelizers. The original program semantics is then re-injected, and the transformed parallel loop nests are recompiled by a standard C compiler. We show on the PolyBench benchmark suite that our system successfully detects and parallelizes almost all the loop nests from the binary code, using a recent polyhedral loop parallelizer as a backend. The paper ends by elaborating a strategy to parallelize more complex programs, such as those containing non-linear accesses to memory, and provides a few example case-studies.

Dates and versions

hal-00664370 , version 1 (30-01-2012)



Benoit Pradelle, Alain Ketterlin, Philippe Clauss. Polyhedral parallelization of binary code. ACM Transactions on Architecture and Code Optimization, 2012, Special issue on high-performance and embedded architectures and compilers, 8 (4), pp.39:1--39:21. ⟨10.1145/2086696.2086718⟩. ⟨hal-00664370⟩


205 View
0 Download



Gmail Facebook X LinkedIn More