Understanding the Impact of Multi-Core Architecture in Cluster Computing: A Case Study with Intel Dual-Core System Export

@inproceedings{citeulike:2361784, abstract = {Multi-core processors are growing as a new industry trend as single core processors rapidly reach the physical limits of possible complexity and speed. In the new Top500 supercomputer list, more than 20\% processors belong to the multi-core processor family. However, without an indepth study on application behaviors and trends on multicore clusters, we might not be able to understand the characteristics of multi-core cluster in a comprehensive manner and hence not be able to get optimal performance. In this paper, we take on these challenges and design a set of experiments to study the impact of multi-core architecture on cluster computing. We choose to use one of the most advanced multi-core servers, Intel Bensley system with Woodcrest processors, as our evaluation platform, and use benchmarks including HPL, NAMD, and NAS as the applications to study. From our message distribution experiments, we find that on an average about 50\% messages are transferred through intra-node communication, which is much higher than intuition. This trend indicates that optimizing intranode communication is as important as optimizing internode communication in a multi-core cluster. We also observe that cache and memory contention may be a potential bottleneck in multi-core clusters, and communication middleware and applications should be multi-core aware to alleviate this problem. We demonstrate that multi-core aware algorithm, e.g. data tiling, improves benchmark execution time by up to 70\%. We also compare the scalability of a multi-core cluster with that of a single-core cluster and find that the scalability of the multi-core cluster is promising.}, author = {Chai, Lei and Gao, Qi and Panda, Dhabaleswar K.}, booktitle = {Cluster Computing and the Grid, 2007. CCGRID 2007. Seventh IEEE International Symposium on}, citeulike-article-id = {2361784}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1251971.1252256}, citeulike-linkout-1 = {http://dx.doi.org/10.1109/CCGRID.2007.119}, citeulike-linkout-2 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4215413}, doi = {10.1109/CCGRID.2007.119}, journal = {Cluster Computing and the Grid, 2007. CCGRID 2007. Seventh IEEE International Symposium on}, keywords = {multi-core, panda}, pages = {471--478}, posted-at = {2008-09-15 03:19:23}, priority = {2}, title = {Understanding the Impact of Multi-Core Architecture in Cluster Computing: A Case Study with Intel Dual-Core System}, url = {http://dx.doi.org/10.1109/CCGRID.2007.119}, year = {2007} }

TY - CONF ID - citeulike:2361784 L3 - citeulike-article-id:2361784 N2 - Multi-core processors are growing as a new industry trend as single core processors rapidly reach the physical limits of possible complexity and speed. In the new Top500 supercomputer list, more than 20% processors belong to the multi-core processor family. However, without an indepth study on application behaviors and trends on multicore clusters, we might not be able to understand the characteristics of multi-core cluster in a comprehensive manner and hence not be able to get optimal performance. In this paper, we take on these challenges and design a set of experiments to study the impact of multi-core architecture on cluster computing. We choose to use one of the most advanced multi-core servers, Intel Bensley system with Woodcrest processors, as our evaluation platform, and use benchmarks including HPL, NAMD, and NAS as the applications to study. From our message distribution experiments, we find that on an average about 50% messages are transferred through intra-node communication, which is much higher than intuition. This trend indicates that optimizing intranode communication is as important as optimizing internode communication in a multi-core cluster. We also observe that cache and memory contention may be a potential bottleneck in multi-core clusters, and communication middleware and applications should be multi-core aware to alleviate this problem. We demonstrate that multi-core aware algorithm, e.g. data tiling, improves benchmark execution time by up to 70%. We also compare the scalability of a multi-core cluster with that of a single-core cluster and find that the scalability of the multi-core cluster is promising. JF - Cluster Computing and the Grid, 2007. CCGRID 2007. Seventh IEEE International Symposium on EP - 478 TI - Understanding the Impact of Multi-Core Architecture in Cluster Computing: A Case Study with Intel Dual-Core System T2 - Cluster Computing and the Grid, 2007. CCGRID 2007. Seventh IEEE International Symposium on SP - 471 KW - multi-core KW - panda AU - Chai, Lei AU - Gao, Qi AU - Panda, Dhabaleswar PY - 2007/// UR - http://dx.doi.org/10.1109/CCGRID.2007.119 ER -