2012 International Conference for High Performance Computing, Networking, Storage and Analysis最新文献_第9页

Unleashing the high-performance and low-power of multi-core DSPs for general-purpose HPC 释放多核dsp的高性能和低功耗，用于通用HPC

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.109

Francisco D. Igual, Murtaza Ali, A. Friedmann, E. Stotzer, Timothy Wentz, R. V. D. Geijn

引用次数: 34

Novel views of performance data to analyze large-scale adaptive applications 新颖的性能数据视图，用于分析大规模自适应应用程序

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.80

A. Bhatele, T. Gamblin, Katherine E. Isaacs, B. Gunney, M. Schulz, P. Bremer, B. Hamann

引用次数: 19

Parallel geometric-algebraic multigrid on unstructured forests of octrees 八树非结构森林上的平行几何代数多重网格

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.91

H. Sundar, G. Biros, Carsten Burstedde, J. Rudi, O. Ghattas, G. Stadler

引用次数: 88

Application data prefetching on the IBM Blue Gene/Q supercomputer IBM Blue Gene/Q超级计算机上的应用程序数据预取

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.19

I. Chung, Changhoan Kim, H. Wen, Guojing Cong

引用次数: 21

Design of a scalable InfiniBand topology service to enable network-topology-aware placement of processes 设计一个可扩展的InfiniBand拓扑服务，以实现网络拓扑感知的进程放置

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.47

H. Subramoni, S. Potluri, K. Kandalla, B. Barth, Jérôme Vienne, J. Keasler, K. Tomko, K. Schulz, A. Moody, D. Panda

{"title":"Design of a scalable InfiniBand topology service to enable network-topology-aware placement of processes","authors":"H. Subramoni, S. Potluri, K. Kandalla, B. Barth, Jérôme Vienne, J. Keasler, K. Tomko, K. Schulz, A. Moody, D. Panda","doi":"10.1109/SC.2012.47","DOIUrl":"https://doi.org/10.1109/SC.2012.47","url":null,"abstract":"Over the last decade, InfiniBand has become an increasingly popular interconnect for deploying modern supercomputing systems. However, there exists no detection service that can discover the underlying network topology in a scalable manner and expose this information to runtime libraries and users of the high performance computing systems in a convenient way. In this paper, we design a novel and scalable method to detect the InfiniBand network topology by using Neighbor-Joining techniques (NJ). To the best of our knowledge, this is the first instance where the neighbor joining algorithm has been applied to solve the problem of detecting InfiniBand network topology. We also design a network-topology-aware MPI library that takes advantage of the network topology service. The library places processes taking part in the MPI job in a network-topology-aware manner with the dual aim of increasing intra-node communication and reducing the long distance inter-node communication across the InfiniBand fabric.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"1 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":"132299450","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: 58

Design and modeling of a non-blocking checkpointing system 非阻塞点检系统的设计与建模

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.46

Kento Sato, N. Maruyama, K. Mohror, A. Moody, T. Gamblin, B. Supinski, S. Matsuoka

引用次数: 103

Mapping applications with collectives over sub-communicators on torus networks 通过环面网络上的子通信器映射具有集合的应用程序

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.75

A. Bhatele, T. Gamblin, S. Langer, P. Bremer, E. Draeger, B. Hamann, Katherine E. Isaacs, Aaditya G. Landge, J. Levine, Valerio Pascucci, M. Schulz, C. Still

{"title":"Mapping applications with collectives over sub-communicators on torus networks","authors":"A. Bhatele, T. Gamblin, S. Langer, P. Bremer, E. Draeger, B. Hamann, Katherine E. Isaacs, Aaditya G. Landge, J. Levine, Valerio Pascucci, M. Schulz, C. Still","doi":"10.1109/SC.2012.75","DOIUrl":"https://doi.org/10.1109/SC.2012.75","url":null,"abstract":"The placement of tasks in a parallel application on specific nodes of a supercomputer can significantly impact performance. Traditionally, this task mapping has focused on reducing the distance between communicating tasks on the physical network. This minimizes the number of hops that point-to-point messages travel and thus reduces link sharing between messages and contention. However, for applications that use collectives over sub-communicators, this heuristic may not be optimal. Many collectives can benefit from an increase in bandwidth even at the cost of an increase in hop count, especially when sending large messages. For example, placing communicating tasks in a cube configuration rather than a plane or a line on a torus network increases the number of possible paths messages might take. This increases the available bandwidth which can lead to significant performance gains. We have developed Rubik, a tool that provides a simple and intuitive interface to create a wide variety of mappings for structured communication patterns. Rubik supports a number of elementary operations such as splits, tilts, or shifts, that can be combined into a large number of unique patterns. Each operation can be applied to disjoint groups of processes involved in collectives to increase the effective bandwidth. We demonstrate the use of Rubik for improving performance of two parallel codes, pF3D and Qbox, which use collectives over sub-communicators.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"1 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":"131204154","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: 56

Parametric flows: Automated behavior equivalencing for symbolic analysis of races in CUDA programs 参数流:用于CUDA程序中种族符号分析的自动行为等价

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.94

Peng Li, Guodong Li, G. Gopalakrishnan

{"title":"Parametric flows: Automated behavior equivalencing for symbolic analysis of races in CUDA programs","authors":"Peng Li, Guodong Li, G. Gopalakrishnan","doi":"10.1109/SC.2012.94","DOIUrl":"https://doi.org/10.1109/SC.2012.94","url":null,"abstract":"The growing scale of concurrency requires automated abstraction techniques to cut down the effort in concurrent system analysis. In this paper, we show that the high degree of behavioral symmetry present in GPU programs allows CUDA race detection to be dramatically simplified through abstraction. Our abstraction techniques is one of automatically creating parametric flows - control-flow equivalence classes of threads that diverge in the same manner - and checking for data races only across a pair of threads per parametric flow. We have implemented this approach as an extension of our recently proposed GKLEE symbolic analysis framework and show that all our previous results are dramatically improved in that (i) the parametric flow-based analysis takes far less time, and (ii) because of the much higher scalability of the analysis, we can detect even more data race situations that were previously missed by GKLEE because it was forced to downscale examples to limit analysis complexity. Moreover, the parametric flow-based analysis is applicable to other programs with SPMD models.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"23 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":"133993952","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: 32

Forward and adjoint simulations of seismic wave propagation on emerging large-scale GPU architectures 新兴大规模GPU架构上地震波传播的正演和伴随模拟

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.59

M. Rietmann, P. Messmer, T. Nissen‐Meyer, D. Peter, P. Basini, D. Komatitsch, O. Schenk, J. Tromp, L. Boschi, D. Giardini

{"title":"Forward and adjoint simulations of seismic wave propagation on emerging large-scale GPU architectures","authors":"M. Rietmann, P. Messmer, T. Nissen‐Meyer, D. Peter, P. Basini, D. Komatitsch, O. Schenk, J. Tromp, L. Boschi, D. Giardini","doi":"10.1109/SC.2012.59","DOIUrl":"https://doi.org/10.1109/SC.2012.59","url":null,"abstract":"Computational seismology is an area of wide sociological and economic impact, ranging from earthquake risk assessment to subsurface imaging and oil and gas exploration. At the core of these simulations is the modeling of wave propagation in a complex medium. Here we report on the extension of the high-order finite-element seismic wave simulation package SPECFEM3D to support the largest scale hybrid and homogeneous supercomputers. Starting from an existing highly tuned MPI code, we migrated to a CUDA version. In order to be of immediate impact to the science mission of computational seismologists, we had to port the entire production package, rather than just individual kernels. One of the challenges in parallelizing finite element codes is the potential for race conditions during the assembly phase. We therefore investigated different methods such as mesh coloring or atomic updates on the GPU. In order to achieve strong scaling, we needed to ensure good overlap of data motion at all levels, including internode and host-accelerator transfers. Finally we carefully tuned the GPU implementation. The new MPI/CUDA solver exhibits excellent scalability and achieves speedup on a node-to-node basis over the carefully tuned equivalent multi-core MPI solver. To demonstrate the performance of both the forward and adjoint functionality, we present two case studies run on the Cray XE6 CPU and Cray XK6 GPU architectures up to 896 nodes: (1) focusing on most commonly used forward simulations, we simulate seismic wave propagation generated by earthquakes in Turkey, and (2) testing the most complex seismic inversion type of the package, we use ambient seismic noise to image 3-D crust and mantle structure beneath western Europe.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"34 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":"114726960","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: 70

Extending the BT NAS Parallel Benchmark to exascale computing 将BT NAS并行基准扩展到百亿亿次计算

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.55

R. V. D. Wijngaart, Srinivas Sridharan, V. Lee

引用次数: 11