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...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/96749 http://hdl.handle.net/10220/13098 |
| _version_ | 1811684628868628480 |
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| author | Sinha, Sharad Srikanthan, Thambipillai |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Sinha, Sharad Srikanthan, Thambipillai |
| author_sort | Sinha, Sharad |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T04:31:39Z |
| format | Conference Paper |
| id | ntu-10356/96749 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:31:39Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-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 |
| spellingShingle | Sinha, Sharad Srikanthan, Thambipillai Dataflow graph partitioning for high level synthesis |
| title | 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_short | Dataflow graph partitioning for high level synthesis |
| title_sort | dataflow graph partitioning for high level synthesis |
| url | https://hdl.handle.net/10356/96749 http://hdl.handle.net/10220/13098 |
| work_keys_str_mv | AT sinhasharad dataflowgraphpartitioningforhighlevelsynthesis AT srikanthanthambipillai dataflowgraphpartitioningforhighlevelsynthesis |