G R code algorithm.

<div><p>Loss-less data compression becomes the need of the hour for effective data compression and computation in VLSI test vector generation and testing in addition to hardware AI/ML computations. Golomb code is one of the effective technique for lossless data compression and it becomes...

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Main Author: R. Sakthivel (2589547) (author)
Other Authors: Ch. Vijayalakshmi (19746609) (author), M. Vanitha (19746612) (author), Kareem M. AboRas (18599078) (author), Waleed Mohammed Abdelfattah (19746615) (author), Yazeed Yasin Ghadi (16667109) (author), Ch. Rami Reddy (18554720) (author)
Published: 2024
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_version_ 1852026357305835520
author R. Sakthivel (2589547)
author2 Ch. Vijayalakshmi (19746609)
M. Vanitha (19746612)
Kareem M. AboRas (18599078)
Waleed Mohammed Abdelfattah (19746615)
Yazeed Yasin Ghadi (16667109)
Ch. Rami Reddy (18554720)
author2_role author
author
author
author
author
author
author_facet R. Sakthivel (2589547)
Ch. Vijayalakshmi (19746609)
M. Vanitha (19746612)
Kareem M. AboRas (18599078)
Waleed Mohammed Abdelfattah (19746615)
Yazeed Yasin Ghadi (16667109)
Ch. Rami Reddy (18554720)
author_role author
dc.creator.none.fl_str_mv R. Sakthivel (2589547)
Ch. Vijayalakshmi (19746609)
M. Vanitha (19746612)
Kareem M. AboRas (18599078)
Waleed Mohammed Abdelfattah (19746615)
Yazeed Yasin Ghadi (16667109)
Ch. Rami Reddy (18554720)
dc.date.none.fl_str_mv 2024-09-26T17:38:39Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0308796.g001
dc.relation.none.fl_str_mv https://figshare.com/articles/figure/G_R_code_algorithm_/27113439
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Genetics
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
xlink "> loss
simulated using modelsim
show around 6
test vector compression
increase compression ratio
multiple data types
lossless data compression
area reduction varies
effective data compression
data compression
effective technique
data computation
work aims
unary part
modifications carried
ml computations
mainly focuses
golomb rice
different methods
case delays
bits used
becomes valid
8 %.
dc.title.none.fl_str_mv G R code algorithm.
dc.type.none.fl_str_mv Image
Figure
info:eu-repo/semantics/publishedVersion
image
description <div><p>Loss-less data compression becomes the need of the hour for effective data compression and computation in VLSI test vector generation and testing in addition to hardware AI/ML computations. Golomb code is one of the effective technique for lossless data compression and it becomes valid only when the divisor can be expressed as power of two. This work aims to increase compression ratio by further encoding the unary part of the Golomb Rice (GR) code so as to decrease the amount of bits used, it mainly focuses on optimizing the hardware for encoding side. The algorithm was developed and coded in Verilog and simulated using Modelsim. This code was then synthesised in Cadence Encounter RTL Synthesiser. The modifications carried out show around 6% to 19% reduction in bits used for a linearly distributed data set. Worst-case delays have been reduced by 3% to 8%. Area reduction varies from 22% to 36% for different methods. Simulation for Power consumption shows nearly 7% reduction in switching power. This ideally suggest the usage of Golomb Rice coding technique for test vector compression and data computation for multiple data types, which should ideally have a geometrical distribution.</p></div>
eu_rights_str_mv openAccess
id Manara_670486c044366f320f28ffc4b60f2bf1
identifier_str_mv 10.1371/journal.pone.0308796.g001
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/27113439
publishDate 2024
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling G R code algorithm.R. Sakthivel (2589547)Ch. Vijayalakshmi (19746609)M. Vanitha (19746612)Kareem M. AboRas (18599078)Waleed Mohammed Abdelfattah (19746615)Yazeed Yasin Ghadi (16667109)Ch. Rami Reddy (18554720)GeneticsBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedxlink "> losssimulated using modelsimshow around 6test vector compressionincrease compression ratiomultiple data typeslossless data compressionarea reduction varieseffective data compressiondata compressioneffective techniquedata computationwork aimsunary partmodifications carriedml computationsmainly focusesgolomb ricedifferent methodscase delaysbits usedbecomes valid8 %.<div><p>Loss-less data compression becomes the need of the hour for effective data compression and computation in VLSI test vector generation and testing in addition to hardware AI/ML computations. Golomb code is one of the effective technique for lossless data compression and it becomes valid only when the divisor can be expressed as power of two. This work aims to increase compression ratio by further encoding the unary part of the Golomb Rice (GR) code so as to decrease the amount of bits used, it mainly focuses on optimizing the hardware for encoding side. The algorithm was developed and coded in Verilog and simulated using Modelsim. This code was then synthesised in Cadence Encounter RTL Synthesiser. The modifications carried out show around 6% to 19% reduction in bits used for a linearly distributed data set. Worst-case delays have been reduced by 3% to 8%. Area reduction varies from 22% to 36% for different methods. Simulation for Power consumption shows nearly 7% reduction in switching power. This ideally suggest the usage of Golomb Rice coding technique for test vector compression and data computation for multiple data types, which should ideally have a geometrical distribution.</p></div>2024-09-26T17:38:39ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0308796.g001https://figshare.com/articles/figure/G_R_code_algorithm_/27113439CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/271134392024-09-26T17:38:39Z
spellingShingle G R code algorithm.
R. Sakthivel (2589547)
Genetics
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
xlink "> loss
simulated using modelsim
show around 6
test vector compression
increase compression ratio
multiple data types
lossless data compression
area reduction varies
effective data compression
data compression
effective technique
data computation
work aims
unary part
modifications carried
ml computations
mainly focuses
golomb rice
different methods
case delays
bits used
becomes valid
8 %.
status_str publishedVersion
title G R code algorithm.
title_full G R code algorithm.
title_fullStr G R code algorithm.
title_full_unstemmed G R code algorithm.
title_short G R code algorithm.
title_sort G R code algorithm.
topic Genetics
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
xlink "> loss
simulated using modelsim
show around 6
test vector compression
increase compression ratio
multiple data types
lossless data compression
area reduction varies
effective data compression
data compression
effective technique
data computation
work aims
unary part
modifications carried
ml computations
mainly focuses
golomb rice
different methods
case delays
bits used
becomes valid
8 %.