Abstract

Abstract—Ocelot is a dynamic compilation framework designed to map the explicitly parallel PTX execution model used by NVIDIA CUDA applications onto diverse many-core architectures. Ocelot includes a dynamic binary translator from PTX to many-core processors that leverages the LLVM code generator to target x86. The binary translator is able to execute CUDA applications without recompilation and Ocelot can in fact dynamically switch between execution on an NVIDIA GPU and a many-core CPU. It has been validated against over 100 applications taken from the CUDA SDK [1], the UIUC Parboil benchmarks [2], the Virginia Rodinia benchmarks [3], the GPU-VSIPL signal and image processing library [4], and several domain specific applications. This paper presents a detailed description of the implementation of our binary translator highlighting design decisions and trade-offs, and showcasing their effect on application performance. We explore several code transformations that are applicable only when translating explicitly parallel applications and suggest additional optimization passes that may be useful to this class of applications. We expect this study to inform the design of compilation tools for explicitly parallel programming models (such as OpenCL) as well as future CPU and GPU architectures. I.

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