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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Brian Van Essen Roger Pearce Sasha Ames Maya Gokhale Center for Applied Scientific Computing Lawrence Livemore National Laboratory Livermore CA USA Department of Computer Science and Engineering Texas A and M University USA

ISBN: (纸本)9781467309752

Data-intensive applications are best suited to high-performance computing architectures that contain large quantities of main memory. Creating these systems with DRAM-based main memory remains costly and power-intensive. Due to improvements in density and cost, non-volatile random access memories (NVRAM) have emerged as compelling storage technologies to augment traditional DRAM. This work explores the potential of future NVRAM technologies to store program state at performance comparable to DRAM. We have developed the PerMA NVRAM simulator that allows us to explore applications with working sets ranging up to hundreds of gigabytes per node. The simulator is implemented as a Linux device driver that allows application execution at native speeds. Using the simulator we show the impact of future technology generations of I/O-bus-attached NVRAM on an unstructured-access, level-asynchronous, Breadth-First Search (BFS) graph traversal algorithm. Our simulations show that within a couple of technology generations, a system architecture with local high performance NVRAM will be able to effectively augment DRAM to support highly concurrent data-intensive applications with large memory footprints. However, improvements will be needed in the I/O stack to deliver this performance to applications. The simulator shows that future technology generations of NVRAM in conjunction with an improved I/O runtime will enable parallel data-intensive applications to offload in-memory data structures to NVRAM with minimal performance loss.

关键词： Random access memory Nonvolatile memory Performance evaluation Delay computer architecture Flash memory Linux

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Reliability tradeoffs for energy efficient wireless networks

Reliability tradeoffs for energy efficient wireless networks

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International Conference on Selected Topics in Mobile and Wireless Networking (iCOST)

作者： Talmai Oliveira Fabíola Greve Anna Maria Vegni Dharma P. Agrawal School of Computing Sciences and Informatics Center for Distributed and Mobile Computing University of Cincinnati USA Computer Science Department (DCC) Federal University of Bahia Brazil Department of Applied Electronics University of Roma Tre Rome Italy

A complex wireless deployment under realistic scenario is prone to failures and it becomes very hard to determine when to stop retransmitting a message in order to ensure proper delivery. In this paper, a simple effective link-attribute estimator is proposed that is capable of identifying the quality of communication between neighboring mobile devices while maintaining the scalability. By relying on our link-quality estimator, a maximum number of attempts is computed which (probabilistically) ensures the message delivery while maintaining energy-efficiency. Through appropriate adjustments, our estimator is capable of obtaining the bounds on the number of retransmission attempts required to increase the message delivery ratio. This enables wireless devices to establish a threshold on the number of transmission attempts, thereby avoiding those retransmissions that would only result in wasted energy. Such dynamic threshold helps enforce at least a minimum number of transmission. Simulations prove the effectiveness of our LQ estimator with respect to energy efficiency and message delivery reliability. Results indicate that an acceptable message delivery ratio can be maintained while increasing the overall energy efficiency.

关键词： Reliability Network topology Wireless networks Protocols Topology Mobile handsets

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A simplified pipeline for motion correction in dual gated cardiac PET

A simplified pipeline for motion correction in dual gated ca...

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2012 - Workshop on Image Processing for Medicine: Algorithms - Systems - Applications, BVM 2012

作者： Ruthotto, Lars Gigengack, Fabian Burger, Martin Wolters, Carsten H. Jiang, Xiaoyi Schäfers, Klaus P. Modersitzki, Jan Institute of Mathematics and Image Computing University of Lübeck Germany European Insitute for Molecular Imaging University of Münster Germany Department of Mathematics and Computer Science University of Münster Germany Institute for Computational and Applied Mathematics University of Münster Germany Institute of Biomagnetism and Biosignalanalysis University of Münster Germany

ISBN: (纸本)9783642285011

Positron Emission Tomography (PET) is a nuclear imaging technique of increasing importance e.g. in cardiovascular investigations. However, cardiac and respiratory motion of the patient degrade the image quality due to acquisition times in the order of minutes. Reconstructions without motion compensation are prone to spatial blurring and affected attenuation correction. These effects can be reduced by gating, motion correction and finally summation of the transformed images. This paper describes a new and systematic approach for the correction of both cardiac and respiratory motion. Key contribution is the splitting of the motion into respiratory and cardiac components, which are then corrected individually. For the considered gating scheme the number of registration problems is reduced by a factor of 3, which considerably simplifies the motion correction pipeline compared to previous approaches. The subproblems are stabilized by averaging cardiac gates for respiratory motion estimation and vice versa. The potential of the novel pipeline is evaluated in a group study on data of 21 human patients. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Positron emission tomography

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Novel Views of Performance Data to Analyze Large-scale Adaptive Applications 12

Novel Views of Performance Data to Analyze Large-scale Adapt...

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ACM/IEEE International Conference for High Performance computing, Networking, Storage, and Analysis

作者： Abhinav Bhatele Todd Gamblin Katherine E. Isaacs Brian T. N. Gunney Martin Schulz Peer-Timo Bremer Bernd Hamann Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA 94551 USA Department of Computer Science University of California Davis CA 95616 USA

ISBN: (纸本)9781467308052

Performance analysis of parallel scientific codes is becoming increasingly difficult due to the rapidly growing complexity of applications and architectures. Existing tools fall short in providing intuitive views that facilitate the process of performance debugging and tuning. In this paper, we extend recent ideas of projecting and visualizing performance data for faster, more intuitive analysis of applications. We collect detailed per-level and per-phase measurements for a dynamically load-balanced, structured AMR library and project per-core data collected in the hardware domain on to the application's communication topology. We show how our projections and visualizations lead to a rapid diagnosis of and mitigation strategy for a previously elusive scaling bottleneck in the library that is hard to detect using conventional tools. Our new insights have resulted in a 22% performance improvement for a 65,536-core run of the AMR library on an IBM Blue Gene/P system.

关键词： performance debugging rapidly growing complexity IBM interacting boson model IBM Libraries Phase measurement View Amphiregulin Antimicrobial Drug Resistance automatic meter reading Visualization rapid diagnosis Intuitive performance boost EQUIPMENT

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A hierarchical approach for load balancing on parallel multi-core systems

A hierarchical approach for load balancing on parallel multi...

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41st International Conference on Parallel Processing, ICPP 2012

作者： Pilla, Laércio L. Ribeiro, Christiane Pousa Cordeiro, Daniel Mei, Chao Bhatele, Abhinav Navaux, Philippe O.A. Broquedis, François Méhaut, Jean-François Kale, Laxmikant V. Institute of Informatics Federal University of Rio Grande Do Sul Porto Alegre Brazil LIG Laboratory CEA/INRIA Grenoble University Grenoble France Department of Computer Science University of Illinois at Urbana-Champaign Urbana IL United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA United States

ISBN: (纸本)9780769547961

Multi-core compute nodes with non-uniform memory access (NUMA) are now a common architecture in the assembly of large-scale parallel machines. On these machines, in addition to the network communication costs, the memory access costs within a compute node are also asymmetric. Ignoring this can lead to an increase in the data movement costs. Therefore, to fully exploit the potential of these nodes and reduce data access costs, it becomes crucial to have a complete view of the machine topology (i.e. the compute node topology and the interconnection network among the nodes). Furthermore, the parallel application behavior has an important role in determining how to utilize the machine efficiently. In this paper, we propose a hierarchical load balancing approach to improve the performance of applications on parallel multi-core systems. We introduce NucoLB, a topology-aware load balancer that focuses on redistributing work while reducing communication costs among and within compute nodes. NucoLB takes the asymmetric memory access costs present on NUMA multi-core compute nodes, the interconnection network overheads, and the application communication patterns into account in its balancing decisions. We have implemented NucoLB using the Charm++ parallel runtime system and evaluated its performance. Results show that our load balancer improves performance up to 20% when compared to state-of-the-art load balancers on three different NUMA parallel machines. © 2012 IEEE.

关键词： Topology

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Heterogeneous Task Scheduling for Accelerated OpenMP

Heterogeneous Task Scheduling for Accelerated OpenMP

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Thomas R.W. Scogland Barry Rountree Wu-chun Feng Bronis R. de Supinski Department of Computer Science Virginia Polytechnic Institute and State University Blacksburg VA USA Center for Applied Scientific Computing Lawrence Livemore National Laboratory Livermore CA USA

Heterogeneous systems with CPUs and computational accelerators such as GPUs, FPGAs or the upcoming Intel MIC are becoming mainstream. In these systems, peak performance includes the performance of not just the CPUs but also all available accelerators. In spite of this fact, the majority of programming models for heterogeneous computing focus on only one of these. With the development of Accelerated Open MP for GPUs, both from PGI and Cray, we have a clear path to extend traditional Open MP applications incrementally to use GPUs. The extensions are geared toward switching from CPU parallelism to GPU parallelism. However they do not preserve the former while adding the latter. Thus computational potential is wasted since either the CPU cores or the GPU cores are left idle. Our goal is to create a runtime system that can intelligently divide an accelerated Open MP region across all available resources automatically. This paper presents our proof-of-concept runtime system for dynamic task scheduling across CPUs and GPUs. Further, we motivate the addition of this system into the proposed Open MP for Accelerators standard. Finally, we show that this option can produce as much as a two-fold performance improvement over using either the CPU or GPU alone.

关键词： Graphics processing unit Dynamic scheduling Integrated circuits Acceleration Schedules Programming Runtime

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Ecotoxicology data federation with SADI semantic web services 5

Ecotoxicology data federation with SADI semantic web service...

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5th International Workshop on Semantic Web Applications and Tools for Life sciences, SWAT4LS 2012

作者： Riazanov, Alexandre Hindle, Matthew M. Goudreau, E. Scott Martyniuk, Christopher J. Baker, Christopher J. O. Department of Computer Science and Applied Statistics University of New Brunswick Saint JohnNB Canada Canadian Rivers Institute Department of Biology University of New Brunswick Saint JohnNB Canada Canada Research in Molecular Ecology Edinburgh University United Kingdom SynthSys Edinburgh University United Kingdom School of Informatics Edinburgh University United Kingdom IPSNP Computing Inc. Canada

Biologists and biotechnologists need to draw information from numerous distributed and heterogeneous resources, such as online biomedical databases, nomenclatures and specialised bioinformatics tools. These tasks can benefit significantly from semantic data federation with SADI Semantic Web services where multiple resources exposed through SADI services are accessed as a single virtual SPARQL-queriable database. We provide evidence in support of this premise by creating and testing a kit of public SADI services for a number of bioinformatics databases and programs, and by demonstrating how it can be used to serve real information needs of ecotoxicology researchers, by using the services to answer some model queries.

关键词： Query processing

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DI-MMAP: A High Performance Memory-Map Runtime for Data-Intensive Applications

DI-MMAP: A High Performance Memory-Map Runtime for Data-Inte...

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High Performance computing, Networking, Storage and Analysis (SCC), SC Companion:

作者： Brian Van Essen Henry Hsieh Sasha Ames Maya Gokhale Lawrence Livermore National Laboratory Livermore CA US Department of Computer Science University of California Los Angeles USA Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA USA

ISBN: (纸本)9781467362184

We present DI-MMAP, a high-performance runtime that memory-maps large external data sets into an application's address space and shows significantly better performance than the Linux mmap system call. Our implementation is particularly effective when used with high performance locally attached Flash arrays on highly concurrent, latency-tolerant data-intensive HPC applications. We describe the kernel module and show performance results on a benchmark test suite and on a new bioinformatics metagenomic classification application. For the complex metagenomics classification application, DI-MMAP performs up to 4.88× better than standard Linux mmap.

关键词： Runtime Linux Benchmark testing Standards Databases Random access memory Instruction sets

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Abstract: Exploring Performance Data with Boxfish

Abstract: Exploring Performance Data with Boxfish

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High Performance computing, Networking, Storage and Analysis (SCC), SC Companion:

作者： Katherine E. Isaacs Aaditya G. Landge Todd Gamblin Peer-Timo Bremer Valerio Pascucci Bernd Hamann Institute for Data Analysis and Visualization Department of Computer Science University of California Davis CA USA Scientific Computing and Imaging Institute University of Utah Salt Lake UT USA Center for Applied Scientific Computing Lawrence Livermore National Laboratories Livermore CA USA

The growth in size and complexity of scaling applications and the systems on which they run pose challenges in analyzing and improving their overall performance. With metrics coming from thousands or millions of processes, visualization techniques are necessary to make sense of the increasing amount of data. To aid the process of exploration and understanding, we announce the initial release of Boxfish, an extensible tool for manipulating and visualizing data pertaining to application behavior. Combining and visually presenting data and knowledge from multiple domains, such as the application's communication patterns and the hardware's network configuration and routing policies, can yield the insight necessary to discover the underlying causes of observed behavior. Boxfish allows users to query, filter and project data across these domains to create interactive, linked visualizations.

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Lecture Notes in Computational science and Engineering: Preface

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Lecture Notes in Computational science and Engineering 2012年 87 LNCSE卷 v-vii页

作者： Forth, Shaun Hovland, Paul Phipps, Eric Utke, Jean Walther, Andrea Applied Mathematics and Scientific Computing Cranfield University Shrivenham Swindon United Kingdom Mathematics and Computer Science Division Argonne National Laboratory Argonne IL United States Sandia National Laboratory Albuquerque NM United States Department of Mathematics University of Paderborn Paderborn Germany

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