.png){kind=icon}
.png){kind=icon}
Return
Multiobjective evaluation and optimization of CMT-bone on multiple CPU/GPU systems
.png){kind=icon}
OA
AI
DOI：10.1016/j.suscom.2017.10.005.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Hybrid multi-core processors are poised to dominate the landscape of next generation computing. By integrating several types of cores on a single chip, designers are anticipating sustained performance growth while depending less on raw circuit speed and decreasing power requirements per unit of performance. In this paper, we study the performance/energy tradeoffs for a heterogeneous platform consisting of Intel multicore processor with multiple nVidia GPU co-processors. Using CMT-bone, a proxy-app designed at the University of Florida, we explore load balancing strategies for a variety of architectural combinations of CPUs and GPUs to optimize for performance, power and energy measurements. (C) 2017 Elsevier Inc. All rights reserved.
Keywords:
Performance
Power and energy tradeoffs
Hybrid computing
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
S
IF:
5.7
Papers:
966
Citations:
2.9K
