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  4. Resource Sharing in Dataflow Circuits
 
conference paper

Resource Sharing in Dataflow Circuits

Josipovic, Lana  
•
Marmet, Axel
•
Guerrieri, Andrea  
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January 1, 2022
2022 Ieee 30Th International Symposium On Field-Programmable Custom Computing Machines (Fccm 2022)
IEEE 30th International Symposium on Field-Programmable Custom Computing Machines (FCCM)

To achieve resource-efficient hardware designs, HLS tools share (i.e., time-multiplex) functional units among operations of the same type. This optimization is typically performed together with operation scheduling to ensure the best possible unit usage at each point in time. Dataflow circuits have emerged as an alternative HLS approach to efficiently handle irregular and control-dominated code. Yet, these circuits do not have a predetermined schedule-in its absence, it is challenging to determine which operations can share a functional unit without a performance penalty. Furthermore, although sharing seems to imply only some trivial circuitry, time-multiplexing units in dataflow circuits may cause deadlock by blocking certain data transfers and preventing operations from executing. In this paper, we present a technique to automatically identify performance-acceptable resource sharing opportunities in dataflow circuits and we describe a sharing mechanism that achieves deadlock-free dataflow designs. On benchmarks obtained from C code, we show that our approach effectively implements resource sharing: it results in significant area savings (i.e., a DSP reduction of up to 81%) compared to dataflow circuits which do not support this feature and matches the sharing capabilities of a state-of-the-art HLS tool.

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Type
conference paper
DOI
10.1109/FCCM53951.2022.9786084
Web of Science ID

WOS:000856347400001

Author(s)
Josipovic, Lana  
Marmet, Axel
Guerrieri, Andrea  
Ienne, Paolo  
Date Issued

2022-01-01

Publisher

IEEE

Publisher place

New York

Published in
2022 Ieee 30Th International Symposium On Field-Programmable Custom Computing Machines (Fccm 2022)
ISBN of the book

978-1-6654-8332-2

Series title/Series vol.

Annual IEEE Symposium on Field-Programmable Custom Computing Machines

Start page

1

End page

9

Subjects

Computer Science, Hardware & Architecture

•

Engineering, Electrical & Electronic

•

Computer Science

•

Engineering

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LAP  
Event nameEvent placeEvent date
IEEE 30th International Symposium on Field-Programmable Custom Computing Machines (FCCM)

New York, NY

May 15-18, 2022

Available on Infoscience
October 10, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/191333
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