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22nd IEEE international symposium on High-Performance Computer Architecture (HPCA)

作者： Chen, Sui Peng, Lu Louisiana State Univ Div Elect & Comp Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9781467392112

It has been proposed that Transactional Memory be added to Graphics processing Units (GPUs) in recent years. One proposed hardware design, Warp TM, can scale to 1000s of concurrent transactions. As a programming method that can atomicize an arbitrary number of memory access locations and greatly reduce the efforts to program parallel applications, transactional memory handles the complexity of interthread synchronization. However, when thousands of transactions run concurrently on a GPU, conflicts and resource contentions arise, causing performance loss. In this paper, we identify and analyze the cause of conflicts and contentions and propose two enhancements that try to resolve conflicts early: (1) Early-Abort global conflict resolution that allows conflicts to be detected before they reach the Commit Units so that contention in the Commit Units is reduced and (2) Pause-and-Go execution scheme that reduces the chance of conflict and the performance penalty of re-executing long transactions. These two enhancements are enabled by a single hardware modification. Our evaluation shows the combination of the two enhancements greatly improves overall execution speed while reducing energy consumption.

关键词： Graphics processing unit

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AN MPI-CUDA IMPLEMENTATION FOR THE COMPRESSION OF DEM 36

AN MPI-CUDA IMPLEMENTATION FOR THE COMPRESSION OF DEM

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36th IEEE international Geoscience and Remote Sensing symposium (IGARSS)

作者： Zeng, Fei Liang, Fahong Yang, Fan Kou, Cheng Xian Surveying & Mapping Technol Ctr Xian Shaanxi Peoples R China Univ Waterloo Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9781509033324

A high performance terrain data compression method is proposed based on discrete wavelet transform (DWT) and parallel run- length code. But the implementation of the schemes to solve these models in realistic scenarios imposes huge demands of computing power. Compute Unified Device Architecture (CUDA) programmed, Graphic processing Units (GPUs) are rapidly becoming a major choice in high performance computing. Hence, the number of applications ported to the CUDA platform is growing high. Message Passing Interface (MPI) has been the choice of high performance computing for more than a decade and it has proven its capability in delivering higher performance in parallel applications. CUDA and MPI use different programming approaches but both of them depend on the inherent parallelism of the application to be effective. In this approach, MPI functions as the data distributing mechanism between the GPU nodes and CUDA as the main computing engine. This allows the programmer to connect GPU nodes via high speed Ethernet without special technologies. We tackle the acceleration of the compression of digital elevation models (DEM) by exploiting the combined power of several CUDA-enabled GPUs in a GPU cluster. This implementation overlaps MPI communication with CPU-GPU memory transfers and GPU computation to increase efficiency. Several numerical experiments, performed on a cluster of modern CUDA-enabled GPUs, show the efficiency of the distributed solver. Our speed-up was over 20 compared to two thread CPU version.

关键词： CUDA GPUs DEM DWT

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SWAT: A programmable, in-memory, distributed, high-performance computing platform 16

SWAT: A programmable, in-memory, distributed, high-performan...

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25th ACM international symposium on High-Performance parallel and distributed Computing, HPDC 2016

作者： Grossman, Max Sarkar, Vivek Rice University 6100 Main St HoustonTX United States

ISBN: (纸本)9781450343145

The field of data analytics is currently going through a renaissance as a result of ever-increasing dataset sizes, the value of the models that can be trained from those datasets, and a surge in exible, distributed programming models. In particular, the Apache Hadoop [1] and Spark [5] programming systems, as well as their supporting projects (e.g. HDFS, SparkSQL), have greatly simplified the analysis and transformation of datasets whose size exceeds the capacity of a single machine. While these programming models facilitate the use of distributed systems to analyze large datasets, they have been plagued by performance issues. The I/O performance bottlenecks of Hadoop are partially responsible for the creation of Spark. Performance bottlenecks in Spark due to the JVM object model, garbage collection, interpreted/-managed execution, and other abstraction layers are responsible for the creation of additional optimization layers, such as Project Tungsten [4]. Indeed, the Project Tungsten issue tracker states that the "majority of Spark workloads are not bottlenecked by I/O or network, but rather CPU and memory" [20]. In this work, we address the CPU and memory performance bottlenecks that exist in Apache Spark by accelerating user-written computational kernels using accelerators. We refer to our approach as Spark With Accelerated Tasks (SWAT). SWAT is an accelerated data analytics (ADA) framework that enables programmers to natively execute Spark applications on high performance hardware platforms with co-processors, while continuing to write their applications in a JVM-based language like Java or Scala. Runtime code generation creates OpenCL kernels from JVM bytecode, which are then executed on OpenCL accelerators. In our work we emphasize 1) full compatibility with a modern, existing, and accepted data analytics platform, 2) an asynchronous, event-driven, and resource-aware runtime, 3) multi-GPU memory management and caching, and 4) ease-of-use and programmability. Ou

关键词： Graphics processing unit

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enerGyPU and enerGyPhi Monitor for Power Consumption and Performance Evaluation on Nvidia Tesla GPU and Intel Xeon Phi 16

enerGyPU and enerGyPhi Monitor for Power Consumption and Per...

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16th IEEE/ACM international symposium on Cluster, Cloud and Grid Computing (CCGrid)

作者： Garcia H, John A. Hernandez B, Esteban Montenegro, Carlos E. Navaux, Philippe O. Barrios H, Carlos J. Univ Ind Santander HIGH Performance & Sci Comp Ctr SC3 Bucaramanga Santander Colombia Univ Fed Rio Grande do Sul Parallel & Distributed Proc Grp GPPD BR-90046900 Porto Alegre RS Brazil Univ Dist Francisco Jose de Caldas UD Interoperabil Acad Networks Grp GIIRA Bogota Colombia

ISBN: (纸本)9781509024537

The evaluation of performance and power consumption is a key step in the design of applications for large computational systems as supercomputers and clusters (multicore and accelerator nodes, multicore and coprocessor nodes, manycore and accelerator nodes). In these systems the developers must design several experiments for workload characterization observing the architectural implications when using different combinations of computational resources such as number of GPU, number of cores for processing, number of cores for administration of GPU, number of MPI processes and thread affinity policy. It should also engage factors as the clock frequency and memory usage as well select the combination of computational resources that increases the performance and minimizes the power consumption. This research proposes an integrated energy-aware scheme called efficiently energetic acceleration (EEA) for large-scale scientific applications running on heterogeneous architectures. This paper shows the use of a monitoring tool with two components called enerGyPU and enerGyPhi to recording EEA control factors in runtime on two environments: one cluster with multicore and accelerator nodes (2-CPU/8-GPU) and one server with multiple cores and one coprocessor (2-CPU/1-MIC). These monitors allow to analyze multiple testing results under different parameter combinations to observe the EEA control factors that determine the energy efficiency.

关键词： Energy efficiency Energy-aware EEA scheme enerGyPU enerGyPhi Power capping technique Performance evaluation

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Social computing in open source community: A study of software reuse 2nd

Social computing in open source community: A study of softwa...

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2nd international Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016

作者： Chen, Mengwen Wang, Tao Yang, Cheng Fan, Qiang Yin, Gang Wang, Huaimin National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9789811020520

Software projects are not developed in isolation but often build upon other open source resources. These projects form a kind of reference ecosystem regarded as a software world. Most of social computing works focus on social networks such as Facebook and weibo to mine information. However, few previous works analyze Open Source Community which could help developers conduct collaborative development. In this paper, we model the Java reference ecosystem as a network based on the reuse relationships of GitHub-hosted Java projects and analyze the characteristics and the patterns of this reference ecosystem by using community detection and pattern discovery algorithms. Our study indicates that (1) Developers prefer to reuse software limited in only a small part of projects with cross cutting functionality or advanced applications. (2) Developers usually select software reused with similar function widely depending on different requirements, resulting to different patterns. Based on these collective intelligence, our study opens up several possible future directions of reuse recommendation, which are considered as guidance of collaborative development. © Springer Science+Business Media Singapore 2016.

关键词： Open source software

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Advances in Intelligent Systems and applications - Volume 2: Proceedings of the international Computer symposium ICS 2012 Held at Hualien, Taiwan, ...

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2016年

作者： Jeng Shyang Pan Ching Nung Yang Chia Chen Lin

ISBN: (纸本)9783662523315

The field of Intelligent Systems and applications has expanded enormously during the last two decades. Theoretical and practical results in this area are growing rapidly due to many successful applications and new theories derived from many diverse problems. This book is dedicated to the Intelligent Systems and applications in many different aspects. In particular, this book is to provide highlights of the current research in Intelligent Systems and applications. It consists of research papers in the following specific topics: l Authentication, Identification, and Signaturel Intrusion Detectionl Steganography, Data Hiding, and Watermarkingl Database, System, and Communication Securityl Computer Vision, Object Tracking, and Pattern Recognitionl Image processing, Medical Image processing, and Video Codingl Digital Content, Digital Life, and Human Computer Interactionl parallel, Peer-to-peer, distributed, and Cloud Computingl Software Engineering and Programming Language This book provides a reference to theoretical problems as well as practical solutions and applications for the state-of-the-art results in Intelligent Systems and applications on the aforementioned topics. In particular, both the academic community (graduate students, post-doctors and faculties) in Electrical Engineering, Computer Science, and Applied Mathematics; and the industrial community (engineers, engineering managers, programmers, research lab staffs and managers, security managers) will find this book interesting."

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Efficient Matricization of n-D Array with CUDA and Its Evaluation 19

Efficient Matricization of n-D Array with CUDA and Its Evalu...

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19th IEEE international Conference on Computational Science and Engineering, 14th IEEE international Conference on Embedded and Ubiquitous Computing and 15th international symposium on distributed Computing and applications to Business, Engineering and Science, CSE-EUC-DCABES 2016

作者： Shaikh, Md Abu Hanif Hasan, K.M. Azharul Ali, G.G. Md. Nawaz Chafii, Marwa Chong, Peter Han Joo Computer Science and Engineering Khulna University of Engineering and Technology Bangladesh School of Electrical and Electronic Engineering Nanyang Technological University Singapore CentraleSupélec IETR Campus de Rennes Cesson-Sévigné-Cedex35576 France Department of Electrical and Electronic Engineering Auckland University of Technology New Zealand

ISBN: (纸本)9781509035939

Scientific and engineering computing requires operation on flooded amount of data having very high number of dimensions. Traditional multidimensional array is widely popular for implementing higher dimensional data but its' performance diminishes with the increase of the number of dimensions. On the other side, traditional row-column view is facile for implementation, imagination and visualization. This paper details a representation scheme for higher dimensional array with row-column abstraction on parallel environment. Odd dimensions contribute along row-direction and even dimensions along column direction which gives lower cost of index computation, higher data locality and parallelism. Each 2-D block of size blockIdx.x × threadIdx.x is independent of each other. Theoretically, it has no limitation with the number of dimensions and mapping algorithm is unique for any number of dimensions. Performance of the proposed matricization is measured with matrix-matrix addition, subtraction and multiplication operation. Experimental results show promising performance improvement over Traditional Multidimensional Array (TMA) and Extended Karnaugh Map Representation (EKMR). Thus the scheme can be used for implementing higher dimensional array in both general purpose and scientific computing on GPU. © 2016 IEEE.

关键词： Graphics processing unit

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A Scalable, parallel Module for Overlapping Grids and Its applications

A Scalable, Parallel Module for Overlapping Grids and Its Ap...

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IEEE international Conference on Big Data Security on Cloud (BigDataSecurity), High Performance and Smart Computing (HPSC) and Intelligent Data and Security (IDS)

作者： Hong Guo Aiqing Zhang Zeyao Mo Ye Pu Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing China State Key Laboratory of Numerical Modeling Chinese Academy of Sciences Beijing China

A parallel module for applications based on overlapping grids has been devised and implemented in JASMIN (J parallel Adaptive Structured Mesh applications INfrastructure). In this module, a patch-based data structure, a grid mapping method and a unified communication schedule have been designed and adopted to overcome the communication bottleneck broadly existing in overlapping grids parallel computing. A grid mapping method library has been designed to make the module be adaptive to all kinds of structured grids, and an interpolator library has also been designed to gather interpolators. Meanwhile, by encapsulating parallel computing strategies, such as distributed storage, data communications, etc. and providing standard interfaces, this module can help users realize overlapping grids parallel computing conveniently. According to our test results, applications based on this module can be run efficiently on thousands of processors, which prove the module's satisfying parallel performance.

关键词： Interpolation Program processors Schedules Atmospheric modeling parallel processing Libraries Receivers

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2nd international Conference on Rheology and Modeling of Materials (IC-RMM2)

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Journal of Physics: Conference Series 2017年第1期790卷

Understanding the rheological properties of materials and their rheological behaviors during their manufacturing processes and in their applications in many cases can help to increase the efficiency and competitiveness not only of the finished goods and products but the organizations and societies also. The more scientific supported and prepared organizations develop more competitive products with better thermal, mechanical, physical, chemical and biological properties and the leading companies apply more competitive equipment and technology processes. The aims of the 2nd international Conference on Rheology and Modeling of Materials (ic-rmm2) and the parallel organized symposiums of the 1st international symposium on Powder Injection Molding (is-pim1) and the 1st international symposium on Rheology and Fracture of Solids (is-rfs1) are the followings: Promote new methods and results of scientific research in the fields of modeling and measurements of rheological properties and behavior of materials under processing and applications; Change information between the theoretical and applied sciences as well as technical and technological implantations. Promote the communication and collaboration between the scientists, researchers and engineers of different disciplines, different nations, countries and continents. The international conference ic-rmm2 and symposiums of is-pim1 and is-rfs1 provide a platform among the leading international scientists, researchers, PhD students and engineers for discussing recent achievements in measurement, modeling and application of rheology in materials technology and materials science of liquids, melts, solids, crystals and amorphous structures. Among thr major fields of interest are the influence of materials structures, mechanical stresses, temperatures, deformation speeds and shear rates on rheological and physical properties, phase transformation of foams, foods, polymers, plastics and other competitive materials like ceramics, na

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GraphPad: Optimized Graph Primitives for parallel and distributed Platforms

GraphPad: Optimized Graph Primitives for Parallel and Distri...

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international symposium on parallel and distributed processing (IPDPS)

作者： Michael J. Anderson Narayanan Sundaram Nadathur Satish Md. Mostofa Ali Patwary Theodore L. Willke Pradeep Dubey Intel Corporation Parallel Computing Laboratory

ISBN: (纸本)9781509021413

The duality between graphs and matrices means that many common graph analyses can be expressed with primitives such as generalized sparse matrix-vector multiplication (SpMSpV) and sparse matrix-matrix multiplication (SpGEMM). Achieving high performance on these primitives is challenging due to limited arithmetic intensity, irregular memory accesses, and significant network communication requirements in the distributed setting. In this paper we implement four graph applications using GraphPad, our optimized multinode implementations of generalized linear algebra primitives such as SpMSpV and SpGEMM. GraphPad is highly flexible to accommodate multiple data layouts, partitioning strategies, and incorporates communication optimizations. Our performance at scale can exceed that of CombBLAS by up to 40×. In addition to GraphPad's performance in a distributed setting, it is also within 2× the performance of GraphMat, a high performance graph framework on a single node for four out of five benchmarks. We also show our communication optimizations and flexibility are critical for good performance on both HPC clusters and commodity cloud platforms.

关键词： Sparse matrices Matrices Kernel Optimization Algorithm design and analysis Programming

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