Using branch prediction information for near-optimal I-cache leakage

被引:0
|
作者
Chung, Sung Woo [1 ]
Skadron, Kevin
机构
[1] Korea Univ, Div Comp & Commun Engn, Seoul 136713, South Korea
[2] Univ Virginia, Dept Comp Sci, Charlottesville, VA 22904 USA
关键词
instruction cache; low power; leakage; drowsy cache; branch prediction;
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
This paper describes a new on-demand wakeup prediction policy for instruction cache leakage control that achieves better leakage savings than prior policies, and avoids the performance overheads of prior policies. The proposed policy reduces leakage energy by more than 92% with only less than 0.3% performance overhead on average. The key to this new on-demand policy is to use branch prediction information for the wakeup prediction. In the proposed policy, inserting an extra stage for wakeup between branch prediction and fetch, allows the branch predictor to be also used as a wakeup predictor without any additional hardware. Thus, the extra stage hides the wakeup penalty, not affecting branch prediction accuracy. Though extra pipeline stages typically add to branch misprediction penalty, in this case, the extra wakeup stage on the normal fetch path can be overlapped with misprediction recovery. With such consistently accurate wakeup prediction, all cache lines except the next expected cache line are in the leakage saving mode, minimizing leakage energy.
引用
收藏
页码:24 / 37
页数:14
相关论文
共 50 条
  • [21] Near-Optimal Location Tracking Using Sensor Networks
    Sharma, Gokarna
    Krishnan, Hari
    Busch, Costas
    Brandt, Steven R.
    PROCEEDINGS OF 2014 IEEE INTERNATIONAL PARALLEL & DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW), 2014, : 738 - 747
  • [22] Near-Optimal DAPSK Demodulation Using a PARAFAC Decomposition
    Sandell, Magnus
    Ismail, Amr
    Tosato, Filippo
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (03) : 2077 - 2083
  • [23] Near-Optimal Weather Routing by Using Improved A* Algorithm
    Shin, Yong Woo
    Abebe, Misganaw
    Noh, Yoojeong
    Lee, Sangbong
    Lee, Inwon
    Kim, Donghyun
    Bae, Jungchul
    Kim, Kyung Chun
    APPLIED SCIENCES-BASEL, 2020, 10 (17):
  • [24] On Optimal and Near-Optimal Turbo Decoding Using Generalized max* Operator
    Papaharalabos, Stylianos
    Mathiopoulos, P. Takis
    Masera, Guido
    Martina, Maurizio
    IEEE COMMUNICATIONS LETTERS, 2009, 13 (07) : 522 - 524
  • [25] THE VALUE OF INFORMATION CONCERNING NEAR-OPTIMAL NITROGEN-FERTILIZER SCHEDULING
    THORNTON, PK
    MACROBERT, JF
    AGRICULTURAL SYSTEMS, 1994, 45 (03) : 315 - 330
  • [26] Brief Announcement: Asynchronous Verifiable Information Dispersal with Near-Optimal Communication
    Alhaddad, Nicolas
    Das, Sourav
    Duan, Sisi
    Ren, Ling
    Varia, Mayank
    Xiang, Zhuolun
    Zhang, Haibin
    PROCEEDINGS OF THE 2022 ACM SYMPOSIUM ON PRINCIPLES OF DISTRIBUTED COMPUTING, PODC 2022, 2022, : 418 - 420
  • [27] Near-Optimal Learning of Extensive-Form Games with Imperfect Information
    Bai, Yu
    Jin, Chi
    Mei, Song
    Yu, Tiancheng
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162, 2022,
  • [28] Efficient Near-Optimal t-Closeness With Low Information Loss
    Gowda, Vikas Thammanna
    Bagai, Rajiv
    Spilinek, Gerald
    Vitalapura, Spandana
    PROCEEDINGS OF THE THE 11TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS'2021), VOL 1, 2021, : 494 - 498
  • [29] Near-Optimal Codes for Information Embedding in Gray-Scale Signals
    Zhang, Weiming
    Zhang, Xinpeng
    Wang, Shuozhong
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2010, 56 (03) : 1262 - 1270
  • [30] Near-optimal continuous patrolling with teams of mobile information gathering agents
    Stranders, R.
    Munoz de Cote, E.
    Rogers, A.
    Jennings, N. R.
    ARTIFICIAL INTELLIGENCE, 2013, 195 : 63 - 105