A code-based analytical approach for using separate device coprocessors in computing systems
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}
}
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.
September 7, 2011 by hgpu
