Aergia: Exploiting Packet Latency Slack in On-Chip Networks

被引:0
|
作者
Das, Reetuparna [1 ]
Mutlu, Onur
Moscibroda, Thomas
Das, Chita R. [1 ]
机构
[1] Penn State Univ, University Pk, PA 16802 USA
来源
ISCA 2010: THE 37TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE | 2010年
关键词
On-chip networks; multi-core; arbitration; prioritization; memory systems; packet scheduling; slack; criticality;
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
Traditional Network-on-Chips (NoCs) employ simple arbitration strategies, such as round-robin or oldest-first, to decide which packets should be prioritized in the network. This is suboptimal since different packets can have very different effects on system performance due to, e.g., different level of memory-level parallelism (MLP) of applications. Certain packets may be performance-critical because they cause the processor to stall, whereas others may be delayed for a number of cycles with no effect on application-level performance as their latencies are hidden by other outstanding packets' latencies. In this paper, we define slack as a key measure that characterizes the relative importance of a packet. Specifically, the slack of a packet is the number of cycles the packet can be delayed in the network with no effect on execution time. This paper proposes new router prioritization policies that exploit the available slack of interfering packets in order to accelerate performance-critical packets and thus improve overall system performance. When two packets interfere with each other in a router, the packet with the lower slack value is prioritized. We describe mechanisms to estimate slack, prevent starvation, and combine slack-based prioritization with other recently proposed application-aware prioritization mechanisms. We evaluate slack-based prioritization policies on a 64-core CMP with an 8x8 mesh NoC using a suite of 35 diverse applications. For a representative set of case studies, our proposed policy increases average system throughput by 21.0% over the commonly-used round-robin policy. Averaged over 56 randomly-generated multiprogrammed workload mixes, the proposed policy improves system throughput by 10.3%, while also reducing application-level unfairness by 30.8%.
引用
收藏
页码:106 / 116
页数:11
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