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| Content Provider | ACM Digital Library |
|---|---|
| Author | Jung, Jaehoon Kim, Junghyun Jo, Gangwon Kim, Jungwon Lee, Jaejin |
| Abstract | Applications written solely in OpenCL or CUDA cannot execute on a cluster as a whole. Most previous approaches that extend these programming models to clusters are based on a common idea: designating a centralized host node and coordinating the other nodes with the host for computation. However, the centralized host node is a serious performance bottleneck when the number of nodes is large. In this paper, we propose a scalable and distributed OpenCL framework called SnuCL-D for large-scale clusters. SnuCL-D's remote device virtualization provides an OpenCL application with an illusion that all compute devices in a cluster are confined in a single node. To reduce the amount of control-message and data communication between nodes, SnuCL-D replicates the OpenCL host program execution and data in each node. We also propose a new OpenCL host API function and a queueing optimization technique that significantly reduce the overhead incurred by the previous centralized approaches. To show the effectiveness of SnuCL-D, we evaluate SnuCL-D with a microbenchmark and eleven benchmark applications on a large-scale CPU cluster and a medium-scale GPU cluster. |
| Starting Page | 553 |
| Ending Page | 569 |
| Page Count | 17 |
| File Format | |
| ISSN | 03621340 15581160 |
| DOI | 10.1145/2980983.2908094 |
| Journal | ACM SIGPLAN Notices (SIGP) |
| Volume Number | 51 |
| Issue Number | 6 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1983-05-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Data replication Redundant computation Programming models Runtime systems Clusters Opencl Heterogeneous computing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Graphics and Computer-Aided Design Software |
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