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基于任务映射的暗硅芯片功耗预算方法

李鑫 李智 周巍 吴瑞祺 唐浩然 陈业航

李鑫, 李智, 周巍, 等 . 基于任务映射的暗硅芯片功耗预算方法[J]. 北京航空航天大学学报, 2022, 48(7): 1115-1124. doi: 10.13700/j.bh.1001-5965.2021.0011
引用本文: 李鑫, 李智, 周巍, 等 . 基于任务映射的暗硅芯片功耗预算方法[J]. 北京航空航天大学学报, 2022, 48(7): 1115-1124. doi: 10.13700/j.bh.1001-5965.2021.0011
LI Xin, LI Zhi, ZHOU Wei, et al. A power budgeting method for dark silicon chips based on task mapping[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(7): 1115-1124. doi: 10.13700/j.bh.1001-5965.2021.0011(in Chinese)
Citation: LI Xin, LI Zhi, ZHOU Wei, et al. A power budgeting method for dark silicon chips based on task mapping[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(7): 1115-1124. doi: 10.13700/j.bh.1001-5965.2021.0011(in Chinese)

基于任务映射的暗硅芯片功耗预算方法

doi: 10.13700/j.bh.1001-5965.2021.0011
基金项目: 

国家自然科学基金 61501377

陕西省自然科学基础研究计划 2021JM-074

详细信息
    通讯作者:

    李鑫, E-mail: xinli@nwpu.edu.cn

  • 中图分类号: TN47

A power budgeting method for dark silicon chips based on task mapping

Funds: 

National Natural Science Foundation of China 61501377

Natural Science Basic Research Program of Shaanxi 2021JM-074

More Information
  • 摘要:

    暗硅系统功耗预算问题可被归类为一种NP-hard问题,针对其存在的提高芯片均温与降低通信成本2个对立优化目标,提出了一种基于任务映射的暗硅芯片功耗预算方法。为降低计算复杂度,基于率先映射高通信量并对后续映射影响较小的任务的规则建立模型,将任务图转换为最大生成树的形式,以优先级值的大小决定任务进行映射的先后顺序。在稳态情况下逐个进行核心寻优,将排序后的任务放置于合适的核心位置,并以凸二次规划问题形式对已确定映射核心位置的功耗预算进行求解。实验表明:针对12开启核心的36核心系统,与经典的热安全功耗预算方法相比,所提方法将总功耗预算提高了11.8%,通信能耗降低了38.2%。

     

  • 图 1  2D-Mesh拓扑结构

    Figure 1.  2D-Mesh topology structure

    图 2  平面版图设计

    Figure 2.  2D layout design

    图 3  任务映射示例

    Figure 3.  An example of task mapping

    图 4  任务映射方式

    Figure 4.  Task mapping method

    图 5  芯片的等效散热电路

    Figure 5.  Equivalent heat dissipation circuit of chip

    图 6  任务优先级排序流程

    Figure 6.  Flowchart of task priority ranking

    图 7  寻找第1个开启核心示意图

    Figure 7.  Diagram of finding the first active core

    图 8  本文功耗预算方法流程

    Figure 8.  Flowchart of the proposed power budgeting method

    图 9  相同暗硅比例系统功耗预算方法性能对比

    Figure 9.  Performance comparison of power budgeting methods under the same system of dark silicon percentages

    图 10  两种实际多媒体基准程序的通信任务图

    Figure 10.  Communication task graphs of two actual multimedia applications

    图 11  相同子任务数目的3种应用结果对比

    Figure 11.  Comparison of results of three applications with the same number of subtasks

    图 12  不同方法的代表性核心映射结果

    Figure 12.  Representative core mapping results using different methods

    图 13  不同方法的代表性核心映射所对应的温度分布

    Figure 13.  Temperature distribution corresponding to representative core mapping using different methods

    图 14  不同α值下MPEG-4功耗预算和AWMD变化趋势

    Figure 14.  Trends of power budget and AWMD for MPEG-4 with different α values

    表  1  三种方法总功耗预算与AWMD的计算结果

    Table  1.   Results of total power budget and AWMD using three methods

    核心数 开启核心数 TSP方法[5] GDP方法[7] 本文方法
    功耗预算/W AWMD 功耗预算/W AWMD 功耗预算/W AWMD
    9 2 82.00 1.00 86.01 2.00 83.89 1.00
    4 128.13 1.47 137.69 2.00 134.52 1.02
    8 179.04 2.03 188.53 2.26 187.50 1.30
    16 4 127.73 1.47 138.02 2.38 133.70 1.02
    8 179.78 2.17 199.80 2.70 193.94 1.41
    12 210.47 2.20 230.10 2.90 227.24 1.54
    25 8 179.17 2.27 198.97 2.82 196.63 1.27
    12 211.70 2.49 239.15 3.61 235.97 1.69
    18 241.39 2.74 268.72 3.60 267.45 1.91
    36 12 213.96 2.97 247.25 3.92 238.07 1.80
    18 242.30 3.29 281.56 4.21 276.37 2.27
    24 269.65 3.34 319.59 5.10 316.69 2.58
    64 18 254.57 3.68 297.45 5.99 291.76 2.36
    24 265.01 4.33 319.35 6.39 311.45 2.63
    46 313.88 5.02 361.22 6.92 357.12 2.77
    下载: 导出CSV

    表  2  本文方法与其他方法提升效果比较(36核心系统)

    Table  2.   Comparison of improved performance between the proposed method and other methods (36 core system)

    应用程序 功耗预算提升比例/% AWMD减少比例/%
    本文方法vs TSP方法 本文方法vs GDP方法 本文方法vs TSP方法 本文方法vs GDP方法
    tgff-12 11.27 -3.71 39.39 54.08
    MWD 11.71 -3.33 35.41 56.77
    MPEG-4 12.41 -2.72 39.86 59.08
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-01-11
  • 录用日期:  2021-05-09
  • 刊出日期:  2021-06-02

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