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A code-based analytical approach for using separate device coprocessors in computing systems

Volker Hampel, Grigori Goronzy, Erik Maehle
Institute of Computer Engineering, University of Lubeck, Lubeck, Germany
Architecture of Computing Systems – ARCS 2011, Lecture Notes in Computer Science, 2011, Volume 6566/2011, 1-12

@article{hampel2011code,

   title={A code-based analytical approach for using separate device coprocessors in computing systems},

   author={Hampel, V. and Goronzy, G. and Maehle, E.},

   journal={Architecture of Computing Systems-ARCS 2011},

   pages={1–12},

   year={2011},

   publisher={Springer}

}

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Special hardware accelerators like FPGAs and GPUs are commonly introduced into a computing system as a separate device. Consequently, the accelerator and the host system do not share a common memory. Sourcing out the data to the additional hardware thus introduces a communication penalty. Based on a combination of a program’s source code and execution profiling we perform an analysis which evaluates the arithmetic intensity as a cost function to identify those parts most reasonable to source out to the accelerating hardware. The basic principles of this analysis are introduced and tested with a sample application. Its concrete results are discussed and evaluated based on the performance of a FPGA-based and a GPU-based implementation.
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