Dataflow graph partitioning for high level synthesis

This paper presents a dataflow graph (DFG) partitioning methodology for effective high level synthesis in the presence of constraints like data initiation interval (II) and area. It also focuses on handling large DFGs for high level synthesis with area reduction as a requirement. An algorithm for da...

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Main Authors: Sinha, Sharad, Srikanthan, Thambipillai
Other Authors: School of Computer Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Online Access:https://hdl.handle.net/10356/96749
http://hdl.handle.net/10220/13098
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-967492020-05-28T07:17:27Z Dataflow graph partitioning for high level synthesis Sinha, Sharad Srikanthan, Thambipillai School of Computer Engineering International Conference on Field Programmable Logic and Applications (22nd : 2012 : Oslo, Norway) This paper presents a dataflow graph (DFG) partitioning methodology for effective high level synthesis in the presence of constraints like data initiation interval (II) and area. It also focuses on handling large DFGs for high level synthesis with area reduction as a requirement. An algorithm for dataflow graph partitioning is presented that aims to reduce area utilization as well as ensure that data initiation interval constraint is met. The algorithm works so as to fit a design into the design space between fully pipelined design and fully resource shared design in order to meet the initiation interval constraint and reduce area only as much as required compared to a fully pipelined design where the area is wasted in the presence of II constraint and a fully resource shared design where the extreme reduction in area puts additional unnecessary constraint on data initiation interval. 2013-08-15T06:14:07Z 2019-12-06T19:34:30Z 2013-08-15T06:14:07Z 2019-12-06T19:34:30Z 2012 2012 Conference Paper https://hdl.handle.net/10356/96749 http://hdl.handle.net/10220/13098 10.1109/FPL.2012.6339265 en
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
description This paper presents a dataflow graph (DFG) partitioning methodology for effective high level synthesis in the presence of constraints like data initiation interval (II) and area. It also focuses on handling large DFGs for high level synthesis with area reduction as a requirement. An algorithm for dataflow graph partitioning is presented that aims to reduce area utilization as well as ensure that data initiation interval constraint is met. The algorithm works so as to fit a design into the design space between fully pipelined design and fully resource shared design in order to meet the initiation interval constraint and reduce area only as much as required compared to a fully pipelined design where the area is wasted in the presence of II constraint and a fully resource shared design where the extreme reduction in area puts additional unnecessary constraint on data initiation interval.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Sinha, Sharad
Srikanthan, Thambipillai
format Conference or Workshop Item
author Sinha, Sharad
Srikanthan, Thambipillai
spellingShingle Sinha, Sharad
Srikanthan, Thambipillai
Dataflow graph partitioning for high level synthesis
author_sort Sinha, Sharad
title Dataflow graph partitioning for high level synthesis
title_short Dataflow graph partitioning for high level synthesis
title_full Dataflow graph partitioning for high level synthesis
title_fullStr Dataflow graph partitioning for high level synthesis
title_full_unstemmed Dataflow graph partitioning for high level synthesis
title_sort dataflow graph partitioning for high level synthesis
publishDate 2013
url https://hdl.handle.net/10356/96749
http://hdl.handle.net/10220/13098
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