Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.21/9244 |
Resumo: | Stochastic Computing has emerged as a competitive computing paradigm that produces fast and simple implementations of arithmetic operations, while offering high levels of parallelism, and graceful degradation of the results when in the presence of errors. IoT devices are often operate under limited power and area constraints and subjected to harsh environments, for which, traditional computing paradigms struggle to provide high availability and fault-tolerance. Stochastic Computing is based on the computation of pseudo-random sequences of bits, hence requiring only a single bit per signal, rather than a data-bus. Notwithstanding, we haven’t witnessed its inclusion in custom computing systems. In this direction, this work presents Stochastic Theater, a framework to specify, simulate, and test Stochastic Datapaths to perform computations using stochastic bitstreams targeting IoT systems. In virtue of the granularity of the bitstreams, the bit-level specification of circuits, high-performance characteristics and reconfigurable capabilities, FPGAs were adopted to implement and test such systems. The proposed framework creates Stochastic Machines from a set of user defined arithmetic expressions, and then tests them with the corresponding input values and specific fault injection patterns. Besides the support to create autonomous Stochastic Computing systems, the presented framework also provides generation of stochastic units, being able to produce estimates on performance, resources and power. A demonstration is presented targeting KLT, typical method for data compression in IoT applications. |
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Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensorsIoTFPGAFault-tolerant computingStochastic bitstreamsApproximate computingComputação aproximadaStochastic Computing has emerged as a competitive computing paradigm that produces fast and simple implementations of arithmetic operations, while offering high levels of parallelism, and graceful degradation of the results when in the presence of errors. IoT devices are often operate under limited power and area constraints and subjected to harsh environments, for which, traditional computing paradigms struggle to provide high availability and fault-tolerance. Stochastic Computing is based on the computation of pseudo-random sequences of bits, hence requiring only a single bit per signal, rather than a data-bus. Notwithstanding, we haven’t witnessed its inclusion in custom computing systems. In this direction, this work presents Stochastic Theater, a framework to specify, simulate, and test Stochastic Datapaths to perform computations using stochastic bitstreams targeting IoT systems. In virtue of the granularity of the bitstreams, the bit-level specification of circuits, high-performance characteristics and reconfigurable capabilities, FPGAs were adopted to implement and test such systems. The proposed framework creates Stochastic Machines from a set of user defined arithmetic expressions, and then tests them with the corresponding input values and specific fault injection patterns. Besides the support to create autonomous Stochastic Computing systems, the presented framework also provides generation of stochastic units, being able to produce estimates on performance, resources and power. A demonstration is presented targeting KLT, typical method for data compression in IoT applications.ISELRCIPLDuarte, Rui PolicarpoVéstias, MárioCarvalho, CarlosCasaleiro, João2019-01-02T11:17:41Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/9244engDUARTE, Rui Policarpo; [et al] – Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors. i-ETC: ISEL Academic Journal of Electronics, Telecommunications and Computers. ISSN 2182-4010. Vol. 4, N.º 1 (2018), pp. 1-92182-4010info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-03T09:57:43Zoai:repositorio.ipl.pt:10400.21/9244Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:17:51.455480Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors |
title |
Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors |
spellingShingle |
Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors Duarte, Rui Policarpo IoT FPGA Fault-tolerant computing Stochastic bitstreams Approximate computing Computação aproximada |
title_short |
Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors |
title_full |
Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors |
title_fullStr |
Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors |
title_full_unstemmed |
Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors |
title_sort |
Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors |
author |
Duarte, Rui Policarpo |
author_facet |
Duarte, Rui Policarpo Véstias, Mário Carvalho, Carlos Casaleiro, João |
author_role |
author |
author2 |
Véstias, Mário Carvalho, Carlos Casaleiro, João |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Duarte, Rui Policarpo Véstias, Mário Carvalho, Carlos Casaleiro, João |
dc.subject.por.fl_str_mv |
IoT FPGA Fault-tolerant computing Stochastic bitstreams Approximate computing Computação aproximada |
topic |
IoT FPGA Fault-tolerant computing Stochastic bitstreams Approximate computing Computação aproximada |
description |
Stochastic Computing has emerged as a competitive computing paradigm that produces fast and simple implementations of arithmetic operations, while offering high levels of parallelism, and graceful degradation of the results when in the presence of errors. IoT devices are often operate under limited power and area constraints and subjected to harsh environments, for which, traditional computing paradigms struggle to provide high availability and fault-tolerance. Stochastic Computing is based on the computation of pseudo-random sequences of bits, hence requiring only a single bit per signal, rather than a data-bus. Notwithstanding, we haven’t witnessed its inclusion in custom computing systems. In this direction, this work presents Stochastic Theater, a framework to specify, simulate, and test Stochastic Datapaths to perform computations using stochastic bitstreams targeting IoT systems. In virtue of the granularity of the bitstreams, the bit-level specification of circuits, high-performance characteristics and reconfigurable capabilities, FPGAs were adopted to implement and test such systems. The proposed framework creates Stochastic Machines from a set of user defined arithmetic expressions, and then tests them with the corresponding input values and specific fault injection patterns. Besides the support to create autonomous Stochastic Computing systems, the presented framework also provides generation of stochastic units, being able to produce estimates on performance, resources and power. A demonstration is presented targeting KLT, typical method for data compression in IoT applications. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 2018-01-01T00:00:00Z 2019-01-02T11:17:41Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.21/9244 |
url |
http://hdl.handle.net/10400.21/9244 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
DUARTE, Rui Policarpo; [et al] – Stochastic theater: stochastic datapath generation framework for fault-tolerant IoT sensors. i-ETC: ISEL Academic Journal of Electronics, Telecommunications and Computers. ISSN 2182-4010. Vol. 4, N.º 1 (2018), pp. 1-9 2182-4010 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
ISEL |
publisher.none.fl_str_mv |
ISEL |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799133441876295680 |