Association for Computing Machinery
Processing speed and energy efficiency are two of the most critical issues for computer systems. This paper presents a systematic approach for profiling the power and performance characteristics of application targeting heterogeneous multi-core computing platforms. The authors' approach enables rapid and automated design space exploration involving optimization of workload distribution for systems with accelerators such as FPGAs and GPUs. They demonstrate that, with minor modification to the design, it is possible to estimate performance and power efficiency trade off to identify optimized workload distribution.