@article {10.3844/jcssp.2014.1811.1818,
article_type = {journal},
title = {HYBRID IMPLEMENTATION AND PERFORMANCE ANALYSIS FOR HIGH PERFORMANCE COMPUTATION WORKLOAD},
author = {Issa, Joseph},
volume = {10},
number = {9},
year = {2014},
month = {Apr},
pages = {1811-1818},
doi = {10.3844/jcssp.2014.1811.1818},
url = {https://thescipub.com/abstract/jcssp.2014.1811.1818},
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.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}