Stochastic Theater: Stochastic Datapath Generation Framework for Fault-Tolerant IoT Sensors
Main Author: | |
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Publication Date: | 2018 |
Other Authors: | , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://doi.org/10.34629/ipl.isel.i-ETC.52 |
Summary: | 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 SensorsElectronics; ComputersIoT; FPGA; Fault-Tolerant Computing; Stochastic Bitstreams; Approximate ComputingStochastic 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.ISEL - High Institute of Engineering of Lisbon2018-12-21T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.34629/ipl.isel.i-ETC.52oai:i-ETC.journals.isel.pt:article/52i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers; Vol 4, No 1 (2018): IoT: Internet of Things as field revolution; ID-8i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers; Vol 4, No 1 (2018): IoT: Internet of Things as field revolution; ID-82182-4010reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAPenghttp://journals.isel.pt/index.php/i-ETC/article/view/52https://doi.org/10.34629/ipl.isel.i-ETC.52http://journals.isel.pt/index.php/i-ETC/article/view/52/54Copyright (c) 2018 Rui Policarpo Duarteinfo:eu-repo/semantics/openAccessDuarte, Rui PolicarpoVéstias, MárioCarvalho, CarlosCasaleiro, João2022-09-20T15:26:06Zoai:i-ETC.journals.isel.pt:article/52Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T10:14:05.175201Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
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 Electronics; Computers IoT; FPGA; Fault-Tolerant Computing; Stochastic Bitstreams; Approximate Computing |
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.author.fl_str_mv |
Duarte, Rui Policarpo Véstias, Mário Carvalho, Carlos Casaleiro, João |
dc.subject.por.fl_str_mv |
Electronics; Computers IoT; FPGA; Fault-Tolerant Computing; Stochastic Bitstreams; Approximate Computing |
topic |
Electronics; Computers IoT; FPGA; Fault-Tolerant Computing; Stochastic Bitstreams; Approximate Computing |
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 |
2018-12-21T00:00:00Z |
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 |
https://doi.org/10.34629/ipl.isel.i-ETC.52 oai:i-ETC.journals.isel.pt:article/52 |
url |
https://doi.org/10.34629/ipl.isel.i-ETC.52 |
identifier_str_mv |
oai:i-ETC.journals.isel.pt:article/52 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://journals.isel.pt/index.php/i-ETC/article/view/52 https://doi.org/10.34629/ipl.isel.i-ETC.52 http://journals.isel.pt/index.php/i-ETC/article/view/52/54 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Rui Policarpo Duarte info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Rui Policarpo Duarte |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
ISEL - High Institute of Engineering of Lisbon |
publisher.none.fl_str_mv |
ISEL - High Institute of Engineering of Lisbon |
dc.source.none.fl_str_mv |
i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers; Vol 4, No 1 (2018): IoT: Internet of Things as field revolution; ID-8 i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers; Vol 4, No 1 (2018): IoT: Internet of Things as field revolution; ID-8 2182-4010 reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
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FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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RCAAP |
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RCAAP |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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