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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kandalla, K. Subramoni, H. Santhanaraman, G. Koop, M. Panda, D.K. |
| Copyright Year | 2009 |
| Description | Author affiliation: Department of Computer Science and Engineering, The Ohio State University, USA (Kandalla, K.; Subramoni, H.; Santhanaraman, G.; Koop, M.; Panda, D.K.) |
| Abstract | The increasing demand for computational cycles is being met by the use of multi-core processors. Having large number of cores per node necessitates multi-core aware designs to extract the best performance. The Message Passing Interface (MPI) is the dominant parallel programming model on modern high performance computing clusters. The MPI collective operations take a significant portion of the communication time for an application. The existing optimizations for collectives exploit shared memory for intra-node communication to improve performance. However, it still would not scale well as the number of cores per node increase. In this work, we propose a novel and scalable multi-leader-based hierarchical Allgather design. This design allows better cache sharing for Non-Uniform Memory Access (NUMA) machines and makes better use of the network speed available with high performance interconnects such as InfiniBand. The new multi-leader-based scheme achieves a performance improvement of up to 58% for small messages and 70% for medium sized messages. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 166185 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424437511 |
| ISSN | 15302075 |
| DOI | 10.1109/IPDPS.2009.5160896 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-23 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Clustering algorithms High performance computing Multicore processing Sockets Libraries Bandwidth Message passing Parallel programming Kernel |
| Content Type | Text |
| Resource Type | Article |
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