Thermal management of on-chip caches through power density minimization

被引:0
|
作者
Ku, JC [1 ]
Ozdemir, S [1 ]
Memik, G [1 ]
Ismail, Y [1 ]
机构
[1] Northwestern Univ, ECE Dept, Evanston, IL 60208 USA
来源
MICRO-38: PROCEEDINGS OF THE 38TH ANNUAL IEEE/ACM INTERNATIONAL SYMPOSIUMN ON MICROARCHITECTURE | 2005年
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Various architectural power reduction techniques have been proposed for on-chip caches in the last decade. However, these techniques mostly ignore the effects of temperature on the power consumption. In this paper, first we show that these power reduction techniques can be suboptimal when thermal effects are considered. Particularly, we propose a thermal-aware cache power-down technique that minimizes the power density of the active parts by turning off alternating rows of memory cells instead of entire banks. The decrease in the power density lowers the temperature, which in return, reduces the leakage of the active parts. Simulations based on SPEC2000 benchmarks in a 70nm technology show that the proposed thermal-aware architecture can reduce the total energy consumption by 53% compared to a conventional cache, and 14% compared to a cache architecture with thermal-unaware power reduction scheme. Second, we show a block permutation scheme that can be used during the design of caches to maximize the distance between blocks with consecutive addresses. By maximizing the distance between consecutively accessed blocks, we minimize the power density of the hot spots in the cache, and hence reduce the peak temperature. This, in return, results in an average leakage power reduction of 8.7% compared to a conventional cache without affecting the dynamic power and the latency. Overall, both of our architectures add no extra run-time penalty compared to the thermal-unaware power reduction schemes, yet they reduce the total energy consumption of a conventional cache by 53% and 5.6% on average, respectively.
引用
收藏
页码:283 / 293
页数:11
相关论文
共 50 条
  • [31] Enabling Power Efficiency through Dynamic Rerouting On-Chip
    Sem-Jacobsen, Frank Olaf
    Rodrigo, Samuel
    Strano, Alessandro
    Skeie, Tor
    Bertozzi, Davide
    Gilabert, Francisco
    ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2013, 12 (04)
  • [32] On-Chip Power Minimization Using Serialization-Widening with Frequent Value Encoding
    Mohammad, Khader
    Kabeer, Ahsan
    Taha, Tarek
    VLSI DESIGN, 2014,
  • [33] A Laser Power Management Method for On-Chip Photonic Interconnect
    Wang, Xiaolu
    Guo, Yiming
    Gu, Huaxi
    Wang, Kun
    2016 SEVENTH INTERNATIONAL GREEN AND SUSTAINABLE COMPUTING CONFERENCE (IGSC), 2016,
  • [34] Evaluating Design Tradeoffs in On-Chip Power Management for CMPs
    Sharkey, Joseph
    Buyuktosunoglu, Alper
    Bose, Pradip
    ISLPED'07: PROCEEDINGS OF THE 2007 INTERNATIONAL SYMPOSIUM ON LOW POWER ELECTRONICS AND DESIGN, 2007, : 44 - 49
  • [35] Scalable Power Management for On-Chip Systems with Malleable Applications
    Shafique, Muhammad
    Ivanov, Anton
    Vogel, Benjamin
    Henkel, Joerg
    IEEE TRANSACTIONS ON COMPUTERS, 2016, 65 (11) : 3398 - 3412
  • [36] Reducing memory penalty by a programmable prefetch engine for on-chip caches
    Chen, TF
    MICROPROCESSORS AND MICROSYSTEMS, 1997, 21 (02) : 121 - 130
  • [37] Applying Swarm Intelligence to Distributed On-Chip Power Management
    Pathak, Divya
    Savidis, Ioannis
    2019 IEEE 37TH INTERNATIONAL CONFERENCE ON COMPUTER DESIGN (ICCD 2019), 2019, : 532 - 540
  • [38] A Shared-Way Set Associative architecture for on-chip caches
    Hamkalo, JL
    Djordjalian, A
    Cernuschi-Frías, B
    COMPUTERS AND THEIR APPLICATIONS, 2001, : 125 - 128
  • [39] Microwatt power management: challenges of on-chip energy harvesting
    Schmickl, S.
    Faseth, T.
    Pretl, H.
    ELEKTROTECHNIK UND INFORMATIONSTECHNIK, 2021, 138 (01): : 31 - 36
  • [40] Data Allocation for Embedded Systems with Hybrid On-Chip Scratchpad and Caches
    Wang, Guanhua
    Ju, Lei
    Jia, Zhiping
    Li, Xin
    2013 IEEE 15TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2013 IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (HPCC_EUC), 2013, : 366 - 373