2012 International Conference for High Performance Computing, Networking, Storage and Analysis最新文献

Optimization of geometric multigrid for emerging multi- and manycore processors 新兴多核和多核处理器的几何多网格优化

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.85

Samuel Williams, Dhiraj D. Kalamkar, Amik Singh, A. Deshpande, B. V. Straalen, M. Smelyanskiy, A. Almgren, P. Dubey, J. Shalf, L. Oliker

{"title":"Optimization of geometric multigrid for emerging multi- and manycore processors","authors":"Samuel Williams, Dhiraj D. Kalamkar, Amik Singh, A. Deshpande, B. V. Straalen, M. Smelyanskiy, A. Almgren, P. Dubey, J. Shalf, L. Oliker","doi":"10.1109/SC.2012.85","DOIUrl":"https://doi.org/10.1109/SC.2012.85","url":null,"abstract":"Multigrid methods are widely used to accelerate the convergence of iterative solvers for linear systems used in a number of different application areas. In this paper, we explore optimization techniques for geometric multigrid on existing and emerging multicore systems including the Opteron-based Cray XE6, Intel® Xeon® E5-2670 and X5550 processor-based Infiniband clusters, as well as the new Intel® Xeon Phi coprocessor (Knights Corner). Our work examines a variety of novel techniques including communication-aggregation, threaded wavefront-based DRAM communication-avoiding, dynamic threading decisions, SIMDization, and fusion of operators. We quantify performance through each phase of the V-cycle for both single-node and distributed-memory experiments and provide detailed analysis for each class of optimization. Results show our optimizations yield significant speedups across a variety of subdomain sizes while simultaneously demonstrating the potential of multi- and manycore processors to dramatically accelerate single-node performance. However, our analysis also indicates that improvements in networks and communication will be essential to reap the potential of manycore processors in large-scale multigrid calculations.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115225330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 75

Large-scale energy-efficient graph traversal: A path to efficient data-intensive supercomputing 大规模高能效图遍历:通往高效数据密集型超级计算的途径

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.70

N. Satish, Changkyu Kim, J. Chhugani, P. Dubey

{"title":"Large-scale energy-efficient graph traversal: A path to efficient data-intensive supercomputing","authors":"N. Satish, Changkyu Kim, J. Chhugani, P. Dubey","doi":"10.1109/SC.2012.70","DOIUrl":"https://doi.org/10.1109/SC.2012.70","url":null,"abstract":"Graph traversal is a widely used algorithm in a variety of fields, including social networks, business analytics, and high-performance computing among others. There has been a push for HPC machines to be rated not just in Petaflops, but also in \"GigaTEPS\" (billions of traversed edges per second), and the Graph500 benchmark has been established for this purpose. Graph traversal on single nodes has been well studied and optimized on modern CPU architectures. However, current cluster implementations suffer from high latency data communication with large volumes of transfers across nodes, leading to inefficiency in performance and energy consumption. In this work, we show that we can overcome these constraints using a combination of efficient low-overhead data compression techniques to reduce transfer volumes along with latency-hiding techniques. Using an optimized single node graph traversal algorithm [1], our novel cluster optimizations result in over 6.6X performance improvements over state-of-the-art data transfer techniques, and almost an order of magnitude in energy savings. Our resulting implementation of the Graph500 benchmark achieves 115 GigaTEPS on a 320-node/5120 core Intel® Endeavor cluster with Intel® Xeon® processors E5-2670, which matches the second ranked result in the recent November 2011 Graph500 list [2] with about 5.6X fewer nodes. Our cluster optimizations only have a 1.8X overhead in overall performance from the performance of the optimized single-node implementation, and allows for near-linear scaling with number of nodes. Our algorithm on 1024 nodes on Intel® Xeon® processor X5670-based systems (with lower per-node performance) for a large multi-Terabyte graph attained 195 GigaTEPS in performance, proving the high scalability of our algorithm. Our per-node performance is the highest in the top 10 of the Nov 2011 Graph500 list.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121088145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 54

GRAPE-8 -- An accelerator for gravitational N-body simulation with 20.5Gflops/W performance GRAPE-8——重力n体模拟加速器，性能为20.5Gflops/W

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.60

J. Makino, H. Daisaka

引用次数: 16

Design and implementation of an intelligent end-to-end network QoS system 智能端到端网络QoS系统的设计与实现

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.45

Sushant Sharma, D. Katramatos, Dantong Yu, Li Shi

引用次数: 21

Protocols for wide-area data-intensive applications: Design and performance issues 广域数据密集型应用的协议:设计和性能问题

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.98

Yufei Ren, Tan Li, Dantong Yu, Shudong Jin, T. Robertazzi, B. Tierney, Eric Pouyoul

引用次数: 27

High throughput software for direct numerical simulations of compressible two-phase flows 用于直接数值模拟可压缩两相流的高通量软件

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.66

B. Hejazialhosseini, D. Rossinelli, Christian Conti, P. Koumoutsakos

引用次数: 17

Heuristic static load-balancing algorithm applied to the fragment molecular orbital method 启发式静态负载平衡算法应用于片段分子轨道法

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.62

Y. Alexeev, Ashutosh Mahajan, S. Leyffer, G. Fletcher, D. Fedorov

引用次数: 26

Cost- and deadline-constrained provisioning for scientific workflow ensembles in IaaS clouds 为IaaS云中的科学工作流集成提供成本和期限限制的配置

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.38

M. Malawski, G. Juve, E. Deelman, J. Nabrzyski

引用次数: 501

Breaking the speed and scalability Barriers for Graph exploration on distributed-memory machines 打破分布式内存机器上图形探索的速度和可扩展性障碍

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.25

Fabio Checconi, F. Petrini, Jeremiah Willcock, A. Lumsdaine, Anamitra R. Choudhury, Yogish Sabharwal

引用次数: 70

Optimizing overlay-based virtual networking through optimistic interrupts and cut-through forwarding 通过乐观中断和直通转发优化基于覆盖的虚拟网络

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.88

Zheng Cui, Lei Xia, P. Bridges, P. Dinda, J. Lange

引用次数: 13