Temporal Accelerators: Unleashing the Potential of Embedded FPGAs

Temporal Accelerators: Unleashing the Potential of Embedded FPGAs

When the complexity of a problem rises, its solution requires more hardware resources. A usual way to solve this is to use larger processors and add more memory. When using Field Programmable Gate-Arrays (FPGAs), which can instantiate arbitrary circuit designs, a larger, mo...

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Autores principales: Christopher Cichiwskyj, Gregor Schiele
Formato: article
Lenguaje:EN
Publicado: Graz University of Technology 2021
Materias:
IoT
Embedded
FPGA
Reconfigurable Hardware
Electronic computers. Computer science
QA75.5-76.95
Acceso en línea:https://doaj.org/article/24ff81af55b0430dbcd8f0816bee418a
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spelling oai:doaj.org-article:24ff81af55b0430dbcd8f0816bee418a2021-11-30T04:30:10ZTemporal Accelerators: Unleashing the Potential of Embedded FPGAs10.3897/jucs.772470948-6968https://doaj.org/article/24ff81af55b0430dbcd8f0816bee418a2021-11-01T00:00:00Zhttps://lib.jucs.org/article/77247/download/pdf/https://lib.jucs.org/article/77247/download/xml/https://lib.jucs.org/article/77247/https://doaj.org/toc/0948-6968When the complexity of a problem rises, its solution requires more hardware resources. A usual way to solve this is to use larger processors and add more memory. When using Field Programmable Gate-Arrays (FPGAs), which can instantiate arbitrary circuit designs, a larger, more costly and power hungry chip is used. In this paper we propose a different approach, namely to split the problem into a graph of interdependent smaller tasks and to reconfigure a small FPGA during runtime to execute each of these tasks efficiently sequentially. This can result in cheaper and more energy efficient systems that can execute very complex problems locally. We present a basic analytical model, evaluate its accuracy and discuss initial insight from it.Christopher CichiwskyjGregor SchieleGraz University of TechnologyarticleIoTEmbeddedFPGAReconfigurable HardwareElectronic computers. Computer scienceQA75.5-76.95ENJournal of Universal Computer Science, Vol 27, Iss 11, Pp 1174-1192 (2021)
institution DOAJ
collection DOAJ
language EN
topic IoT
Embedded
FPGA
Reconfigurable Hardware
Electronic computers. Computer science
QA75.5-76.95
spellingShingle IoT
Embedded
FPGA
Reconfigurable Hardware
Electronic computers. Computer science
QA75.5-76.95
Christopher Cichiwskyj
Gregor Schiele
Temporal Accelerators: Unleashing the Potential of Embedded FPGAs
description When the complexity of a problem rises, its solution requires more hardware resources. A usual way to solve this is to use larger processors and add more memory. When using Field Programmable Gate-Arrays (FPGAs), which can instantiate arbitrary circuit designs, a larger, more costly and power hungry chip is used. In this paper we propose a different approach, namely to split the problem into a graph of interdependent smaller tasks and to reconfigure a small FPGA during runtime to execute each of these tasks efficiently sequentially. This can result in cheaper and more energy efficient systems that can execute very complex problems locally. We present a basic analytical model, evaluate its accuracy and discuss initial insight from it.
format article
author Christopher Cichiwskyj
Gregor Schiele
author_facet Christopher Cichiwskyj
Gregor Schiele
author_sort Christopher Cichiwskyj
title Temporal Accelerators: Unleashing the Potential of Embedded FPGAs
title_short Temporal Accelerators: Unleashing the Potential of Embedded FPGAs
title_full Temporal Accelerators: Unleashing the Potential of Embedded FPGAs
title_fullStr Temporal Accelerators: Unleashing the Potential of Embedded FPGAs
title_full_unstemmed Temporal Accelerators: Unleashing the Potential of Embedded FPGAs
title_sort temporal accelerators: unleashing the potential of embedded fpgas
publisher Graz University of Technology
publishDate 2021
url https://doaj.org/article/24ff81af55b0430dbcd8f0816bee418a
work_keys_str_mv AT christophercichiwskyj temporalacceleratorsunleashingthepotentialofembeddedfpgas
AT gregorschiele temporalacceleratorsunleashingthepotentialofembeddedfpgas
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