A heterogeneous platform with GPU and FPGA for power efficient high performance computing
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
Heterogeneous computing is gaining attention from both industry and academia nowadays. One driving factor for heterogeneous computing is the power efficiency. GPU and FPGA have been reported to achieve much higher power efficiency over CPU on many applications. Comparisons between GPU and FPGA show different characteristics of GPU and FPGA in accelerated computing. Some tasks run better on GPU, some run better on FPGA. Combining GPU and FPGA in one heterogeneous computing platform may provide us the advantages from both sides. This paper presents a heterogeneous computing platform with GPU and FPGA that we have built for power efficient high performance computing. The experimental results of 4 application examples show that different applications have different favorite computing architectures, which suggests a matching of the characteristics between the computation task and the computing architecture is the key to the power efficient high performance computing on heterogeneous computing platforms.
Details
Originalsprache | Englisch |
---|---|
Titel | Proceedings of the 14th International Symposium on Integrated Circuits, ISIC 2014 |
Herausgeber (Verlag) | IEEE, New York [u. a.] |
Seiten | 220-223 |
Seitenumfang | 4 |
ISBN (elektronisch) | 9781479948338 |
Publikationsstatus | Veröffentlicht - 2 Feb. 2015 |
Peer-Review-Status | Ja |
Extern publiziert | Ja |
Publikationsreihe
Reihe | International Symposium on Integrated Circuits (ISIC) |
---|
Konferenz
Titel | 14th International Symposium on Integrated Circuits |
---|---|
Kurztitel | ISIC 2014 |
Veranstaltungsnummer | 14 |
Dauer | 10 - 12 Dezember 2014 |
Bekanntheitsgrad | Internationale Veranstaltung |
Ort | Sands Expo and Convention Centre |
Stadt | Singapore |
Land | Singapur |
Schlagworte
Forschungsprofillinien der TU Dresden
ASJC Scopus Sachgebiete
Schlagwörter
- FPGA, GPU, Heterogeneous Computing, High Performance Computing, Power Efficiency