TY - GEN
T1 - Run-time resource allocation for simultaneous multi-tasking in multi-core reconfigurable processors
AU - Ahmed, Waheed
AU - Shafique, Muhammad
AU - Bauer, Lars
AU - Hammerich, Manuel
AU - Henkel, Jrg
AU - Becker, Juergen
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - State-of-the-art multi-core reconfigurable processors do not exploit the full potential of simultaneous multi-tasking with run-time adaptive reconfigurable fabric allocation. We propose a novel run-time system for simultaneous multi-tasking in a multi-core reconfigurable processor that adaptively allocates the mixed-grained reconfigurable fabric resource at run time among different tasks considering their performance constraints. Our scheme employs the novel concept of refined task-criticality (based on the functional-block-level performance constraints) considering the computational properties of dependent tasks and their inherent potential for acceleration. Our scheme dynamically compensates the deadline misses at the functional block level. It thereby reduces the potential task-level deadline misses under competing scenarios. With the help of a secure video conferencing application (with 4 dependent tasks of diverse computational properties), we demonstrate that our scheme reduces the deadline misses by (on average) 6x under given performance constraints, when compared to state-of-the-art reconfigurable processors [1, 9, 12].
AB - State-of-the-art multi-core reconfigurable processors do not exploit the full potential of simultaneous multi-tasking with run-time adaptive reconfigurable fabric allocation. We propose a novel run-time system for simultaneous multi-tasking in a multi-core reconfigurable processor that adaptively allocates the mixed-grained reconfigurable fabric resource at run time among different tasks considering their performance constraints. Our scheme employs the novel concept of refined task-criticality (based on the functional-block-level performance constraints) considering the computational properties of dependent tasks and their inherent potential for acceleration. Our scheme dynamically compensates the deadline misses at the functional block level. It thereby reduces the potential task-level deadline misses under competing scenarios. With the help of a secure video conferencing application (with 4 dependent tasks of diverse computational properties), we demonstrate that our scheme reduces the deadline misses by (on average) 6x under given performance constraints, when compared to state-of-the-art reconfigurable processors [1, 9, 12].
UR - http://www.scopus.com/inward/record.url?scp=79958714078&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79958714078&partnerID=8YFLogxK
U2 - 10.1109/FCCM.2011.46
DO - 10.1109/FCCM.2011.46
M3 - Conference contribution
AN - SCOPUS:79958714078
SN - 9780769543017
T3 - Proceedings - IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2011
SP - 29
EP - 32
BT - Proceedings - IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2011
T2 - 19th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2011
Y2 - 1 May 2011 through 3 May 2011
ER -