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05730057 Dietz, Henry G. Young, B.Dalton MIMD interpretation on a GPU. Gao, Guang R. (ed.) et al., Languages and compilers for parallel computing. 22nd international workshop, LCPC 2009, Newark, DE, USA, October 8--10, 2009. Revised selected papers. Berlin: Springer (ISBN 978-3-642-13373-2/pbk). Lecture Notes in Computer Science 5898, 65-79 (2010). 2010 Berlin: Springer EN

doi:10.1007/978-3-642-13374-9_5

Summary: Programming heterogeneous parallel computer systems is notoriously difficult, but MIMD models have proven to be portable across multi-core processors, clusters, and massively parallel systems. It would be highly desirable for GPUs (Graphics Processing Units) also to be able to leverage algorithms and programming tools designed for MIMD targets. Unfortunately, most GPU hardware implements a very restrictive multi-threaded SIMD-based execution model. This paper presents a compiler, assembler, and interpreter system that allows a GPU to implement a richly featured MIMD execution model that supports shared-memory communication, recursion, etc. Through a variety of careful design choices and optimizations, reasonable efficiency is obtained on NVIDIA CUDA GPUs. The discussion covers both the methods used and the motivation in terms of the relevant aspects of GPU architecture.