research-article

A Distributed Energy-aware Task Mapping to Achieve Thermal Balancing and Improve Reliability of Many-core Systems

Authors:

Marcelo Mandelli,

Guilherme Castilhos,

Gilles Sassatelli,

Fernando G. MoraesAuthors Info & Claims

SBCCI '15: Proceedings of the 28th Symposium on Integrated Circuits and Systems Design

Article No.: 13, Pages 1 - 7

https://doi.org/10.1145/2800986.2800992

Published: 31 August 2015 Publication History

Abstract

Investigating novel techniques to improve many-core embedded systems lifetime, reliability, and thermal management is a fundamental challenge for the semiconductor industry. Imbalanced mapping of applications may considerably affect the system performance and lifetime due to thermal issues in an integrated circuit (e.g. hotspot zones). Traditional mapping techniques focus on local optimizations, e.g. minimize the number of hops between communicating tasks, which may lead to hotspot zones and underutilization of some processing resources. This paper proposes a runtime mapping heuristic whose cost function targets temporal workload and energy consumption balance in large scale systems. The proposed heuristic minimizes the occurrence of hotspots by distributing application workload onto the processing elements in a uniform way, which contributes to a balanced thermal distribution across the system. These features improve system reliability and postpone aging effects. Results with several benchmarks executing in a cycle-accurate platform model show a uniform system utilization when comparing the proposed heuristic to conventional mapping approaches.

References

[1]

Chantem, T.; Xiang Y.; Hu, X.; Dick, R. P. "Enhancing multicore reliability through wear compensation in online assignment and scheduling". In: DATE, 2013, pp. 1373--1378.

Digital Library

[2]

Wang, Z.; Chen, C.; Sharma, P.; Chattopadhyay, A. "System-level reliability exploration framework for heterogeneous MPSoC". In: GLSVLSI, 2014, pp 9--14.

Digital Library

[3]

Chandra, V. "Quantifying workload dependent reliability in embedded processors". In: ASP-DAC, 2014, pp. 474--477.

[4]

Coskun, A.; Rosing, T.; Whisnant, K. "Temperature Aware Task Scheduling in MPSoCs". In: DATE, 2007, 6p.

Digital Library

[5]

Coskun, A.; Ayala, J.; Atienza, D.; Rosing, T.; Leblebici, Y. "Dynamic thermal management in 3D multicore architectures". In: DATE, 2009, pp.1410--1415

Digital Library

[6]

Huang, L.; Yuan, F.; Xu, Q. "Lifetime reliability-aware task allocation and scheduling for MPSoC platforms". In: DATE, 2009, pp. 51--56.

Digital Library

[7]

Das, A.; Kumar, A.; Veeravalli, B. "Reliability-driven task mapping for lifetime extension of networks-on-chip based multiprocessor systems". In: DATE, 2013, pp. 689--694.

Digital Library

[8]

Das, A.; Kumar, A.; Veeravalli, B. "Temperature aware energy-reliability trade-offs for mapping of throughput-constrained applications on multimedia MPSoCs". In: DATE, 2014, 6p.

Digital Library

[9]

Bolchini, C.; Carminati, M.; Miele, A.; Das, A.; Kumar, A.; Veeravalli, B. "Run-time mapping for reliable many-cores based on energy/performance trade-offs". In: DFT, 2013, pp. 58--64.

[10]

Hartman, A. S.; Thomas, D. E. "Lifetime improvement through runtime wear-based task mapping". In: CODES+ISSS, 2012, pp. 13--22.

Digital Library

[11]

Rudi, A.; Bartolini, A.; Lodi, A.; Benini, L. "Optimum: Thermal-aware task allocation for heterogeneous many-core devices". In: HPCS, 2014, pp.82,87.

[12]

Cox, M.; Singh, A.; Kumar, A.; Corporaal, H. "Thermal-aware mapping of streaming applications on 3D Multi-Processor Systems". In: ESTIMedia, 2013, pp. 11--20.

[13]

Huang, W.; Ghosh, S.; Velusamy, S.; Sankaranarayanan, K.; Skadron, K.; Stan, M. "HotSpot: a compact thermal modeling methodology for early-stage VLSI design". IEEE Transactions on Very Large Scale Integration Systems, v.14(5), 2006, pp. 501--513.

Digital Library

[14]

Ge, Y.; Malani, P.; Qiu, Q. "Distributed task migration for thermal management in many-core systems". In: DAC, 2010, pp.579--584.

Digital Library

[15]

Wu, Y.-K.; Sharifi, S.; Rosing, T. "Distributed thermal management for embedded heterogeneous MPSoCs with dedicated hardware accelerators". In: ICCD, 2011, pp.183--189.

Digital Library

[16]

Liu, Z.; Tan, S.-D.; Huang, X.; Wang, H. "Task Migrations for Distributed Thermal Management Considering Transient Effects". IEEE Transactions on Very Large Scale Integration Systems, v.23(2), 2015, pp.397--401.

[17]

Villavieja, C; Etsion, Y.; Ramirez, A.; Navarro, N. "FELI: HW/SW Support for On-Chip Distributed Shared Memory in Multicores". In: Euro-Par, 2011, pp. 282--294.

Digital Library

[18]

Castilhos, G.; Mandelli, M.; Madalozzo, G.; Moraes, F. "Distributed Resource Management in NoC-Based MPSoCs with Dynamic Cluster Sizes". In: ISVLSI, 2013, pp. 153--158.

[19]

Jejurikar, R.; Pereira, C.; Gupta, R. "Leakage aware dynamic voltage scaling for real-time embedded systems". In: DAC, 2004, pp. 275--280.

Digital Library

[20]

Rosa, F.; Ost, L.; Raupp, T.; Moraes, F.; Reis, R. "Fast energy evaluation of embedded applications for many-core systems". In: PATMOS, 2014, 6p.

[21]

Tiwari, V.; Malik, S.; Wolfe, A. "Power analysis of embedded software: a first step towards software power minimization". IEEE Transactions Very Large Scale Integration Systems, v.2(4), 1994, pp. 437--445.

Digital Library

[22]

Murali, S.; Mutapcic, A.; Atienza, D.; Gupta, R.; Boyd, S.; De Micheli, G. "Temperature-aware processor frequency assignment for MPSoCs using convex optimization". In: CODES+ISSS, 2007, pp. 111--116.

Digital Library

[23]

Das, A.; Kumar, A.; Veeravalli, B. "Communication and migration energy aware task mapping for reliable multiprocessor systems". In: Future Generation Computer Systems, v.30, 2014, pp. 216--228.

Digital Library

[24]

Singh, A. K.; Kumar, A.; Srikanthan, T. "Accelerating throughput-aware runtime mapping for heterogeneous MPSoCs". In: ACM Transactions on Design Automation of Electronic Systems, v.18(1), 2012, pp. 1--29.

Digital Library

[25]

Carara, E.; Oliveira, R.; Calazans, N.; Moraes, F. "HeMPS - a Framework for NoC-based MPSoC Generation". In: ISCAS, 2009, pp. 1345--1348.

[26]

Mandelli, M.; Ost, L.; Amory, A.; Moraes, F. "Multi-Task Dynamic Mapping onto NoC-based MPSoCs". In: SBCCI, 2011, pp. 191--196.

Digital Library

Cited By

Gupta MBhargava LIndu S(2021)Mapping techniques in multicore processors: current and future trendsThe Journal of Supercomputing10.1007/s11227-021-03650-6Online publication date: 5-Feb-2021
https://doi.org/10.1007/s11227-021-03650-6
Akmal MSaeed MSardar MShafi HHasan OKhdr HHenkel J(2020)Comparative Framework for the Analysis of Thermal and Resource Management Algorithms for Multi-Core Architectures2020 21st International Symposium on Quality Electronic Design (ISQED)10.1109/ISQED48828.2020.9137038(421-425)Online publication date: Mar-2020
https://doi.org/10.1109/ISQED48828.2020.9137038
Wachter EFochi VBarreto FAmory AMoraes F(2018)A Hierarchical and Distributed Fault Tolerant Proposal for NoC-Based MPSoCsIEEE Transactions on Emerging Topics in Computing10.1109/TETC.2016.25936406:4(524-537)Online publication date: 1-Oct-2018
https://doi.org/10.1109/TETC.2016.2593640
Show More Cited By

Index Terms

A Distributed Energy-aware Task Mapping to Achieve Thermal Balancing and Improve Reliability of Many-core Systems
1. Hardware
  1. Emerging technologies
  2. Very large scale integration design

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Published In

cover image ACM Conferences

SBCCI '15: Proceedings of the 28th Symposium on Integrated Circuits and Systems Design

August 2015

279 pages

ISBN:9781450337632

DOI:10.1145/2800986

General Chair:
Robson Nunes de Lima
UFBA, Brazil
,
Program Chairs:
Ana Isabela Araújo Cunha
UFBA, Brazil
,
Calvin Plett
Carleton University, Canada
,
Publications Chair:
Wagner Luiz Alves de Oliveira
UFBA, Brazil

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SBC: Brazilian Computer Society
SIGDA: ACM Special Interest Group on Design Automation
SBMICRO: Brazilian Microelectronics Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 August 2015

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SBCCI '15

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SIGDA
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SBCCI '15: 28th Symposium on Integrated Circuits and Systems Design

August 31 - September 4, 2015

Salvador, Brazil

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SBCCI '15 Paper Acceptance Rate 43 of 98 submissions, 44%;

Overall Acceptance Rate 133 of 347 submissions, 38%

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Citations

Cited By

Gupta MBhargava LIndu S(2021)Mapping techniques in multicore processors: current and future trendsThe Journal of Supercomputing10.1007/s11227-021-03650-6Online publication date: 5-Feb-2021
https://doi.org/10.1007/s11227-021-03650-6
Akmal MSaeed MSardar MShafi HHasan OKhdr HHenkel J(2020)Comparative Framework for the Analysis of Thermal and Resource Management Algorithms for Multi-Core Architectures2020 21st International Symposium on Quality Electronic Design (ISQED)10.1109/ISQED48828.2020.9137038(421-425)Online publication date: Mar-2020
https://doi.org/10.1109/ISQED48828.2020.9137038
Wachter EFochi VBarreto FAmory AMoraes F(2018)A Hierarchical and Distributed Fault Tolerant Proposal for NoC-Based MPSoCsIEEE Transactions on Emerging Topics in Computing10.1109/TETC.2016.25936406:4(524-537)Online publication date: 1-Oct-2018
https://doi.org/10.1109/TETC.2016.2593640
Ma YChantem TDick RHu X(2017)Improving System-Level Lifetime Reliability of Multicore Soft Real-Time SystemsIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2017.266914425:6(1895-1905)Online publication date: Jun-2017
https://doi.org/10.1109/TVLSI.2017.2669144
Abich GMandelli MRosa FMoraes FOst LReis R(2016)Extending FreeRTOS to support dynamic and distributed mapping in multiprocessor systems2016 IEEE International Conference on Electronics, Circuits and Systems (ICECS)10.1109/ICECS.2016.7841301(712-715)Online publication date: Dec-2016
https://doi.org/10.1109/ICECS.2016.7841301
Madalozzo GIndrusiak LMoraes F(2016)Mapping of real-time applications on a packet switching NoC-based MPSoC2016 IEEE International Conference on Electronics, Circuits and Systems (ICECS)10.1109/ICECS.2016.7841283(640-643)Online publication date: Dec-2016
https://doi.org/10.1109/ICECS.2016.7841283

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