Jun 20, 2019 · Our experimental results demonstrate that PERKS can predict the performance of current workloads and RDPs with an accuracy above 95%. We also ...
Abstract—The next generation high-performance computing platforms will need to support exascale computing. A promising path in achieving exascale is to ...
This paper proposes PERKS, a novel performance estimation frame-work for reconfigurable dataflow platforms (RDPs). PERKS uses machine and application parameters ...
We evaluate the proposed method together with other popular machine learning based methods in estimating the latency and energy consumption of our implemented ...
Dive into the research topics of 'Performance Estimation for Exascale Reconfigurable Dataflow Platforms'. Together they form a unique fingerprint. Sort by ...
Performance Estimation for Exascale Reconfigurable Dataflow Platforms. Ryota Yasudo, José Gabriel F. Coutinho, Ana Lucia Varbanescu, Wayne Luk, ...
Aug 12, 2021 · Our experimental results show that PERKS can predict the performance of current workloads on reconfigurable dataflow platforms with an accuracy ...
Apr 27, 2024 · Our experimental results show that PERKS can predict the performance of current workloads on reconfigurable dataflow platforms with an accuracy ...
2018. Performance Estimation for Exascale Reconfigurable Dataflow Platforms. Ryota Yasudo, Jose G. F. Coutinho, Ana L. Varbanescu, Wayne Luk, Hideharu Amano ...
Analytical Performance Estimation for Large-Scale Reconfigurable Dataflow Platforms · Performance Estimation for Exascale Reconfigurable Dataflow Platforms ...