HYBRID IMPLEMENTATION AND PERFORMANCE ANALYSIS FOR HIGH PERFORMANCE COMPUTATION WORKLOAD

Abstract

Given the need to achieve maximum performance possible, offloading intensive computation workload to GPU is a key to achieve this goal. Offloading most of the workload to GPU may not results in desired performance, so a middle approach is more suitable such as splitting the workload between the CPU and the GPU can be considered as an optimized approach. In this study, we used a popular high performance computation workload which can also be implemented using a hybrid approach in which part of the workload is offloaded to the CPU. We also present a performance estimation method which is verified to estimate performance with in 5% error margin.