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On fine-grained runtime power budgeting for networks-on-chip systems

On fine-grained runtime power budgeting for networks-on-chip systems
On fine-grained runtime power budgeting for networks-on-chip systems
Power budgeting is an essential aspect of networks-on-chip (NoC) to meet the power constraint for on-chip communications while assuring the best possible overall system performance. For simplicity and ease of implementation, existing NoC power budgeting schemes treat all the individual routers uniformly when allocating power to them. However, such homogeneous power budgeting schemes ignore the fact that the workloads of different NoC routers may vary significantly, and thus may provide excess power to routers with low workloads, whereas insufficient power to those with high workloads. In this paper, we formulate the NoC power budgeting problem in order to optimize the network performance over a power budget through per-router frequency scaling. We take into account of heterogeneous workloads across different routers as imposed by variations in traffic. Correspondingly, we propose a fine-grained solution using an agile algorithm with low time complexity. Frequency of each router is set individually according to its contribution to the average network latency while meeting the power budget. Experimental results have confirmed that with fairly low runtime and hardware overhead, the proposed scheme can help save up to 50 percent application execution time when compared with the latest proposed methods.
2780-2793
Wang, X.
976221d1-3004-409c-8640-715bedfc5d15
Zhao, B.
173c3078-5ba8-476a-aab2-df6e01e9559d
Mak, T.
0f90ac88-f035-4f92-a62a-7eb92406ea53
Yang, M.
10224d09-ea3b-40f9-8d15-513652d644b7
Jiang, Y.
8637ec0f-8af3-44b9-87e6-bec78a09e9fa
Daneshtalab, M.
7ea1b16c-4d73-4d30-a50a-6a9dc34d5288
Wang, X.
976221d1-3004-409c-8640-715bedfc5d15
Zhao, B.
173c3078-5ba8-476a-aab2-df6e01e9559d
Mak, T.
0f90ac88-f035-4f92-a62a-7eb92406ea53
Yang, M.
10224d09-ea3b-40f9-8d15-513652d644b7
Jiang, Y.
8637ec0f-8af3-44b9-87e6-bec78a09e9fa
Daneshtalab, M.
7ea1b16c-4d73-4d30-a50a-6a9dc34d5288

Wang, X., Zhao, B., Mak, T., Yang, M., Jiang, Y. and Daneshtalab, M. (2016) On fine-grained runtime power budgeting for networks-on-chip systems. IEEE Transactions on Computers, 65 (9), 2780-2793. (doi:10.1109/TC.2015.2506565).

Record type: Article

Abstract

Power budgeting is an essential aspect of networks-on-chip (NoC) to meet the power constraint for on-chip communications while assuring the best possible overall system performance. For simplicity and ease of implementation, existing NoC power budgeting schemes treat all the individual routers uniformly when allocating power to them. However, such homogeneous power budgeting schemes ignore the fact that the workloads of different NoC routers may vary significantly, and thus may provide excess power to routers with low workloads, whereas insufficient power to those with high workloads. In this paper, we formulate the NoC power budgeting problem in order to optimize the network performance over a power budget through per-router frequency scaling. We take into account of heterogeneous workloads across different routers as imposed by variations in traffic. Correspondingly, we propose a fine-grained solution using an agile algorithm with low time complexity. Frequency of each router is set individually according to its contribution to the average network latency while meeting the power budget. Experimental results have confirmed that with fairly low runtime and hardware overhead, the proposed scheme can help save up to 50 percent application execution time when compared with the latest proposed methods.

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More information

Accepted/In Press date: 25 November 2015
e-pub ahead of print date: 8 December 2015
Published date: September 2016
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 401854
URI: http://eprints.soton.ac.uk/id/eprint/401854
PURE UUID: d48cfa9b-5969-4a05-bd19-9a9f41d45935

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Date deposited: 24 Oct 2016 13:45
Last modified: 15 Mar 2024 02:56

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Contributors

Author: X. Wang
Author: B. Zhao
Author: T. Mak
Author: M. Yang
Author: Y. Jiang
Author: M. Daneshtalab

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