Realizing Complexity-Effective On-Chip Power Delivery for Many-Core Platforms by Exploiting Optimized Mapping

被引:0
|
作者
Tavana, Mohammad Khavan [1 ]
Pathak, Divya [2 ]
Hajkazemi, Mohammad Hossein [1 ]
Malik, Maria [1 ]
Savidis, Ioannis [2 ]
Homayoun, Houman [1 ]
机构
[1] George Mason Univ, Dept Elect & Comp Engn, Fairfax, VA 22030 USA
[2] Drexel Univ, Dept Elect & Comp Engn, Philadelphia, PA 19104 USA
关键词
on-chip voltage regulator; workload snapping; energy-efficiency; power management; real-time systems;
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
In the recent years, many-core platforms have emerged to boost performance while meeting tight power constraints. Per-core Dynamic Voltage and Frequency Scaling (DVFS) maximizes energy savings and meets the performance requirements of a given workload. Given a limited number of I/0 pins and the need for finer control of voltage and frequency settings per core, there is a substantial cost in using off-chip voltage regulators. Consequently, there has been increased attention on the use of on-chip voltage regulators (OCVR) in many-core systems. However, integrating OCVRs comes at a cost of reduced power conversion efficiency (PCE) and increased complexity in the power delivery network and management of the OCVRs. In this paper, the effect of PCE on the thread-to-core mapping algorithm is investigated and the importance of the PCE-aware mapping scheme to optimize energy-efficiency is highlighted. Based on the results, up to 38% more energy savings is achieved as compared to PCE-agnostic algorithms. Moreover, the impact of core clustering granularity and process variation on the total efficiency of the system is explored. When relaxing the energy constraints by just 10%, an effective mapping reduces the complexity of the power delivery system by allowing the use of a significantly smaller number of voltage regulators, as compared to per-core OCVR. The results provided in the paper indicate an important opportunity for system and circuit co-design to implement energy-efficient and complexity-effective platforms for a target workload.
引用
收藏
页码:581 / 588
页数:8
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