Power Saving Analysis and Experiments for Large Scale Global Optimization
Green computing, an emerging field of research that seeks to reduce excess power consumption in high performance computing (HPC), is gaining popularity among researchers. Research in this field often relies on simulation or only uses a small cluster, typically 8 or 16 nodes, because of the lack of...
Main Author: | Cao, Zhenwei |
---|---|
Other Authors: | Computer Science |
Format: | Others |
Published: |
Virginia Tech
2014
|
Subjects: | |
Online Access: | http://hdl.handle.net/10919/33944 http://scholar.lib.vt.edu/theses/available/etd-07092009-200715/ |
Similar Items
-
Investigation of Improved Cooperative Coevolution for Large-Scale Global Optimization Problems
by: Aleksei Vakhnin, et al.
Published: (2021-04-01) -
Reducing Dynamic Power Consumption in Mixed-Critical Real-Time Systems
by: Ijaz Ali, et al.
Published: (2020-10-01) -
Proactive Scenario Characteristic-Aware Online Power Management on Mobile Systems
by: Sodam Han, et al.
Published: (2020-01-01) -
Power- and Time-Aware Deep Learning Inference for Mobile Embedded Devices
by: Woochul Kang, et al.
Published: (2019-01-01) -
GPU Energy Consumption Optimization With a Global-Based Neural Network Method
by: Yanhui Huang, et al.
Published: (2019-01-01)