2012 International Conference for High Performance Computing, Networking, Storage and Analysis最新文献_第6页

Massively parallel X-ray scattering simulations 大规模平行x射线散射模拟

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.76

Abhinav Sarje, X. Li, S. Chourou, E. Chan, A. Hexemer

引用次数: 8

Toward real-time modeling of human heart ventricles at cellular resolution: Simulation of drug-induced arrhythmias 在细胞分辨率上实现人类心室的实时建模:药物性心律失常的模拟

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.108

A. Mirin, David F. Richards, J. Glosli, E. Draeger, B. Chan, J. Fattebert, W. D. Krauss, T. Oppelstrup, J. Rice, John A. Gunnels, V. Gurev, Changhoan Kim, J. Magerlein, M. Reumann, H. Wen

{"title":"Toward real-time modeling of human heart ventricles at cellular resolution: Simulation of drug-induced arrhythmias","authors":"A. Mirin, David F. Richards, J. Glosli, E. Draeger, B. Chan, J. Fattebert, W. D. Krauss, T. Oppelstrup, J. Rice, John A. Gunnels, V. Gurev, Changhoan Kim, J. Magerlein, M. Reumann, H. Wen","doi":"10.1109/SC.2012.108","DOIUrl":"https://doi.org/10.1109/SC.2012.108","url":null,"abstract":"We have developed a highly efficient and scalable cardiac electrophysiology simulation capability that supports groundbreaking resolution and detail to elucidate the mechanisms of sudden cardiac death from arrhythmia. We can simulate thousands of heartbeats at a resolution of 0.1 mm, comparable to the size of cardiac cells, thereby enabling scientific inquiry not previously possible. Based on scaling results from the partially deployed Sequoia IBM Blue Gene/Q machine at Lawrence Livermore National Laboratory and planned optimizations, we estimate that by SC12 we will simulate 8 -- 10 heartbeats per minute -- a time-to-solution 400 -- 500 times faster than the state-of-the-art. Performance between 8 and 11 PFlop/s on the full 1,572,864 cores is anticipated, representing 40 -- 55 percent of peak. The power of the model is demonstrated by illuminating the subtle arrhythmogenic mechanisms of anti-arrhythmic drugs that paradoxically increase arrhythmias in some patient populations.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"445 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":"116563385","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: 18

Efficient data restructuring and aggregation for I/O acceleration in PIDX PIDX中用于I/O加速的有效数据重构和聚合

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.54

Sidharth Kumar, V. Vishwanath, P. Carns, J. Levine, R. Latham, G. Scorzelli, H. Kolla, R. Grout, R. Ross, M. Papka, Jacqueline H. Chen, Valerio Pascucci

{"title":"Efficient data restructuring and aggregation for I/O acceleration in PIDX","authors":"Sidharth Kumar, V. Vishwanath, P. Carns, J. Levine, R. Latham, G. Scorzelli, H. Kolla, R. Grout, R. Ross, M. Papka, Jacqueline H. Chen, Valerio Pascucci","doi":"10.1109/SC.2012.54","DOIUrl":"https://doi.org/10.1109/SC.2012.54","url":null,"abstract":"Hierarchical, multiresolution data representations enable interactive analysis and visualization of large-scale simulations. One promising application of these techniques is to store high performance computing simulation output in a hierarchical Z (HZ) ordering that translates data from a Cartesian coordinate scheme to a one-dimensional array ordered by locality at different resolution levels. However, when the dimensions of the simulation data are not an even power of 2, parallel HZ ordering produces sparse memory and network access patterns that inhibit I/O performance. This work presents a new technique for parallel HZ ordering of simulation datasets that restructures simulation data into large (power of 2) blocks to facilitate efficient I/O aggregation. We perform both weak and strong scaling experiments using the S3D combustion application on both Cray-XE6 (65,536 cores) and IBM Blue Gene/P (131,072 cores) platforms. We demonstrate that data can be written in hierarchical, multiresolution format with performance competitive to that of native data-ordering methods.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"18 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":"128154333","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: 23

Communication avoiding and overlapping for numerical linear algebra 数值线性代数中的通信避免与重叠

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.32

E. Georganas, J. González-Domínguez, Edgar Solomonik, Yili Zheng, J. Touriño, K. Yelick

引用次数: 41

Compass: A scalable simulator for an architecture for cognitive computing Compass:用于认知计算体系结构的可扩展模拟器

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.34

Robert Preissl, T. Wong, Pallab Datta, M. Flickner, Raghavendra Singh, Steven K. Esser, W. Risk, H. Simon, D. Modha

引用次数: 116

Code generation for parallel execution of a class of irregular loops on distributed memory systems 分布式存储系统上一类不规则循环并行执行的代码生成

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.30

Mahesh Ravishankar, John Eisenlohr, L. Pouchet, J. Ramanujam, A. Rountev, P. Sadayappan

引用次数: 40

A multi-objective auto-tuning framework for parallel codes 并行代码的多目标自动调优框架

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.7

Herbert Jordan, Peter Thoman, J. Durillo, Simone Pellegrini, P. Gschwandtner, T. Fahringer, H. Moritsch

引用次数: 86

T*: A data-centric cooling energy costs reduction approach for Big Data analytics cloud T*:为大数据分析云提供以数据为中心的冷却能源成本降低方法

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.103

Rini T. Kaushik, K. Nahrstedt

{"title":"T*: A data-centric cooling energy costs reduction approach for Big Data analytics cloud","authors":"Rini T. Kaushik, K. Nahrstedt","doi":"10.1109/SC.2012.103","DOIUrl":"https://doi.org/10.1109/SC.2012.103","url":null,"abstract":"Explosion in Big Data has led to a surge in extremely large-scale Big Data analytics platforms, resulting in burgeoning energy costs. Big Data compute model mandates strong data-locality for computational performance, and moves computations to data. State-of-the-art cooling energy management techniques rely on thermal-aware computational job placement/migration and are inherently data-placement-agnostic in nature. T* takes a novel, data-centric approach to reduce cooling energy costs and to ensure thermal-reliability of the servers. T* is cognizant of the uneven thermal-profile and differences in thermal-reliability-driven load thresholds of the servers, and the differences in the computational jobs arrival rate, size, and evolution life spans of the Big Data placed in the cluster. Based on this knowledge, and coupled with its predictive file models and insights, T* does proactive, thermal-aware file placement, which implicitly results in thermal-aware job placement in the Big Data analytics compute model. Evaluation results with one-month long real-world Big Data analytics production traces from Yahoo! show up to 42% reduction in the cooling energy costs with T* courtesy of its lower and more uniform thermal-profile and 9x better performance than the state-of-the-art data-agnostic cooling techniques.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"15 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":"124745190","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: 45

Characterizing output bottlenecks in a supercomputer 描述超级计算机的输出瓶颈

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.28

Bing Xie, J. Chase, D. Dillow, Oleg Drokin, S. Klasky, S. Oral, N. Podhorszki

引用次数: 101

Looking under the hood of the IBM Blue Gene/Q network 深入了解IBM蓝色基因/Q网络

2012 International Conference for High Performance Computing, Networking, Storage and Analysis Pub Date : 2012-11-10 DOI: 10.1109/SC.2012.72

Dong Chen, Noel Eisley, P. Heidelberger, Sameer Kumar, A. Mamidala, F. Petrini, R. Senger, Yutaka Sugawara, R. Walkup, B. Steinmacher-Burow, Anamitra R. Choudhury, Yogish Sabharwal, Swati Singhal, J. Parker

{"title":"Looking under the hood of the IBM Blue Gene/Q network","authors":"Dong Chen, Noel Eisley, P. Heidelberger, Sameer Kumar, A. Mamidala, F. Petrini, R. Senger, Yutaka Sugawara, R. Walkup, B. Steinmacher-Burow, Anamitra R. Choudhury, Yogish Sabharwal, Swati Singhal, J. Parker","doi":"10.1109/SC.2012.72","DOIUrl":"https://doi.org/10.1109/SC.2012.72","url":null,"abstract":"This paper explores the performance and optimization of the IBM Blue Gene/Q (BG/Q) five dimensional torus network on up to 16K nodes. The BG/Q hardware supports multiple dynamic routing algorithms and different traffic patterns may require different algorithms to achieve best performance. Between 85% to 95% of peak network performance is achieved for all-to-all traffic, while over 85% of peak is obtained for challenging bisection pairings. A new software-controlled algorithm is developed for bisection traffic that selects which hardware algorithm to employ and achieves better performance than any individual hardware algorithm. The benefit of dynamic routing is shown for a highly non-uniform \"transpose\" traffic pattern. To evaluate memory and network performance, the HPCC Random Access benchmark was tuned for BG/Q and achieved 858 Giga Updates per Second (GUPS) on 16K nodes. To further accelerate message processing, the message libraries on BG/Q enable the offloading of messaging overhead onto dedicated communication threads. Several applications, including Algebraic Multigrid (AMG), exhibit from 3 to 20% gain using communication threads.","PeriodicalId":217221,"journal":{"name":"2012 International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"10 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":"114923440","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: 79