Automatic parallelization in a binary rewriter

Abstract—Today, nearly all general-purpose computers are parallel, but nearly all software running on them is serial. However bridging this disconnect by manually rewriting source code in parallel is prohibitively expensive. Automatic paral-lelization technology is therefore an attractive alternative. We present a method to perform automatic parallelization in a binary rewriter. The input to the binary rewriter is the serial binary executable program and the output is a parallel binary executable. The advantages of parallelization in a binary rewriter versus a compiler include (i) compatibility with all compilers and languages; (ii) high economic feasibility from avoiding repeated compiler implementation; (iii) applicability to legacy binaries; and (iv) applicability to assembly-language programs. Adapting existing parallelizing compiler methods that work on source code to work on binary programs instead is a significant challenge. This is primarily because symbolic and array index information used in existing compiler parallelizers is not available in a binary. We show how to adapt existing parallelization methods to achieve equivalent parallelization from a binary without such information. Preliminary results using our x86 binary rewriter called SecondWrite on a suite of dense-matrix regular programs including the externally developed Polybench suite of benchmarks shows an average speedup of 5.1 from binary and 5.7 from source with 8 threads compared to the input serial binary on an x86 Xeon E5530 machine; and 14.7 from binary and 15.4 from source with 32 threads compared to the input serial binary on a SPARC T2. Such regular loops are an important component of scientific and multi-media workloads, and are even present to a limited extent in otherwise non-regular programs