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Utility Aware Snoozy Caches for Energy Efficient Chip Multi-Processors

Published: 30 May 2018 Publication History

Abstract

Heavy leakage power consumption of on-chip last level caches (LLCs) has become the primary obstacle for architecting chip multi-processors (CMPs) in recent times. As leakage power has a direct relationship with the supply voltage, hence, periodic access profile based dynamic voltage scaling (DVS) in the LLC banks can be a promising option towards reducing this heavy cache leakage. A plethora of prior attempts have reduced this by anticipating working set size (WSS) of the applications and eventually putting some portions of the cache banks in low power mode. This proposed work aims to reduce leakage by putting a whole LLC bank into a low power (snoozy) mode through exploiting DVS at cache banks having minimal usages. Additionally, the resulting performance impacts of the low power snoozy mode are alleviated further by putting some snoozy banks in active mode on-demand. Experimental evaluations using full system simulation on a multi-banked 2MB 8-way set associative L2 cache show 10% more leakage savings on an average over a prior drowsy technique.

References

[1]
A. Bardine et al. . 2007 a. Analysis of Static and Dynamic Energy Consumption in NUCA Caches: Initial Results. ACM MEDEA (Septemeber . 2007), 105--112.
[2]
A. Mandke Dani et al. . 2011 a. Adaptive Power Optimization of On-chip SNUCA Cache on Tiled Chip Multicore Architecture using Remap Policy. Second Workshop on Architecture and Multi-Core Applications (2011), 12--17.
[3]
B. Fitzgerald et al. . 2013. Drowsy Cache Partitioning for Reduced Static and Dynamic Energy in the Cache Hierarchy. International Green Computing Conference (IGCC) (June . 2013), 1--6.
[4]
C Bienia et al. . 2008. The PARSEC Benchmark Suite: Characterization and Architectural Implications. Princeton University Tech. Rep. TR-811-08 (2008).
[5]
G. Keramidas et al. . 2007 b. Applying decay to reduce dynamic power in set-associative caches. HiPEAC (2007), 38--53.
[6]
Hang-Sheng Wang et al. . 2002 a. Orion: a power-performance simulator for interconnection networks MICRO-35. 294 -- 305.
[7]
K. Flautner et al. . 2002 b. Drowsy caches: simple techniques for reducing leakage power Proceedings of 29th Annual Int. Symp. on Comp. Arch. 148--157.
[8]
K. Inoue et al. . 1999. Way-predicting set-associative cache for high performance and low energy consumption. In Proceedings of Int. Symp. on Low power electronics and design. ACM, 273--275.
[9]
M. Loghi et al. . 2009. Tag overflow buffering: Reducing total memory energy by reduced-tag matching. IEEE Trans. on VLSI systems Vol. 17, 5 (2009), 728--732.
[10]
M. Powell et al. . 2000. Gated-Vdd: A Circuit Technique to Reduce Leakage in Deep-submicron Cache Memories Proceedings of Int. Symp. on Low Power Electronics and Design.
[11]
N. Binkert et al. . 2011 b. The Gem5 Simulator. ACM SIGARCH Computer Architure News Vol. 39, 2 (Aug. . 2011), 1--7.
[12]
S. Dropsho et al. . 2002 c. Integrating adaptive on-chip storage structures for reduced dynamic power Proceedings of Parallel Architectures and Compilation Techniques. IEEE, 141--152.
[13]
Y. Guo et al. . 2011 c. Energy-efficient hardware data prefetching. IEEE Trans. on VLSI Systems Vol. 19, 2 (2011), 250--263.
[14]
Z. Huiyang et al. . 2003. Adaptive Mode Control: A Static Power Efficient Cache Design. ACM Trans. on Embedded Comp. Syst. Vol. 2, 3 (August . 2003), 347--372.
[15]
H. K. Kapoor et al. . 2015. Static energy reduction by performance linked cache capacity management in Tiled CMPs ACM SAC.
[16]
G. H. Loh . 2008. 3D-stacked memory architectures for multi-core processors 35th Int. Symp. on Comp. Arch. IEEE, 453--464.
[17]
Naveen M. et al. . 2008. CACTI 6.0: A Tool to Understand Large Caches. (2008).
[18]
S. Mittal . 2014. A survey of architectural techniques for improving cache power efficiency. Sust. Comp.: Informatics and Systems Vol. 4, 1 (2014), 33 -- 43.
[19]
M. Rawlins and A. Gordon-Ross . 2011. On the interplay of loop caching, code compression, and cache configuration Proceedings of the 16th Asia and South Pacific Design Automation Conference. IEEE Press, 243--248.
[20]
W Zang and A Gordon-Ross . 2013. A Survey on Cache Tuning from a Power/Energy Perspective. ACM Comput. Surv. Vol. 45, 3 (July . 2013), 32:1--32:49.

Cited By

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  • (2018)Towards Analysing the Effect of Snoozy Caches on the Temperature of Tiled Chip Multi-Processors2018 8th International Symposium on Embedded Computing and System Design (ISED)10.1109/ISED.2018.8704045(230-235)Online publication date: Dec-2018

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cover image ACM Conferences
GLSVLSI '18: Proceedings of the 2018 Great Lakes Symposium on VLSI
May 2018
533 pages
ISBN:9781450357241
DOI:10.1145/3194554
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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Published: 30 May 2018

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Author Tags

  1. dynamic energy
  2. edp (energy delay product)
  3. ipc (instructions per cycle)
  4. leakage energy
  5. llcs
  6. multi-banked caches
  7. snoozy cache
  8. usage statistics

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GLSVLSI '18
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GLSVLSI '18: Great Lakes Symposium on VLSI 2018
May 23 - 25, 2018
IL, Chicago, USA

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GLSVLSI '18 Paper Acceptance Rate 48 of 197 submissions, 24%;
Overall Acceptance Rate 312 of 1,156 submissions, 27%

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View all
  • (2018)Towards Analysing the Effect of Snoozy Caches on the Temperature of Tiled Chip Multi-Processors2018 8th International Symposium on Embedded Computing and System Design (ISED)10.1109/ISED.2018.8704045(230-235)Online publication date: Dec-2018

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