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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Changyou Zhang Kun Huang Xiang Cui Yifeng Chen |
| Copyright Year | 2012 |
| Abstract | On-chip parallelism with GPU accelerators is now ubiquitous and has received significant attention in the past few years. GPU is becoming an integral part of mainstream computing systems with highly parallel, multithreaded, many-core processors of great computational power and high memory bandwidth. Finding the best tradeoff between performance and power efficiency is more challenging than mere performance tuning. To find the principles of power-aware programming with GPU accelerators, we abstract a set of primitives from program statements. These power consumption values of primitives are helpful for power estimation during high-level program development. |
| Starting Page | 2443 |
| Ending Page | 2449 |
| File Size | 394866 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781467309745 |
| DOI | 10.1109/IPDPSW.2012.301 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-21 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Power demand Power measurement Primitive Power-aware Memory management Bandwidth Programming Hardware GPU Graphics processing unit Message systems |
| Content Type | Text |
| Resource Type | Article |
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