ABSTRACT
In the past, evaluating the architectural innovation of parallel computing devices relied on a benchmark suite based on existing programs, e.g., EEMBC or SPEC. However, with the growing ubiquity of parallel computing devices, we argue that it is unclear how best to express parallel computation, and hence, a need exists to identify a higher level of abstraction for reasoning about parallel application requirements. Therefore, the goal of this combination "Work-in-Progress and Vision" paper is to delineate application requirements in a manner that is not overly specific to individual applications or the optimizations used for certain hardware platforms, so that we can draw broader conclusions about hardware requirements. Our initial effort, dubbed "OpenCL and the 13 Dwarfs" or OCD for short, realizes Berkeley's 13 computational dwarfs of scientific computing in OpenCL, where each dwarf captures a pattern of computation and communication that is common to a class of important applications.
- R. Anandakrishnan, T. Scogland, A. Fenley, J. Gordon, W. Feng, and A. Onufriev. Accelerating Electrostatic Surface Potential Calculation with Multi-Scale Approximation on Graphics Processing Units. J. Molecular Graphics and Modelling, June 2010.Google Scholar
- K. Asanovic, R. Bodik, B. Catanzaro, J. Gebis, P. Husbands, K. Keutzer, D. Patterson, W. Plishker, J. Shalf, S. Williams, and K. Yelick. The Landscape of Parallel Computing Research: A View from Berkeley. Technical Report UCB/EECS-2006-183, EECS Department, University of California, Dec. 2006.Google Scholar
Index Terms
- OpenCL and the 13 dwarfs: a work in progress
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