Semantics Of Original Program Research Articles

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.

Slicing programs in the presence of errors

Abstract Program slicing is a technique by which statements are deleted from a program in such a way as to preserve a projection of the original program's semantics. It is shown that slicing algorithms based upon traditional defined and referenced variable sets do not preserve a projection of strict semantics with respect to computations which cause errors. Rather, these approaches preserve a projection of the program's semantics which is lazy with respect to errors. A modified version of defined and referenced variable sets is introduced, which provides the freedom to choose the form of semantics to be preserved.