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37th IEEE International parallel and Distributed Processing Symposium (IPDPS)

作者： Guo, Luanzheng Kestor, Gokcen Pacific Northwest Natl Lab Richland WA 99352 USA

ISBN: (纸本)9798350311990

Sparse tensor algebra has been an important tool in scientific research. However, there is limited study on sparse tensor transposition on its performance. To the best of our knowledge, sparse tensor transposition has been a critical performance bottleneck in sparse tensor algebra computations. In this work, we characterize the performance of sparse tensor transposition in a chain of distinct sparse tensor algebra operations and study sparse tensor transposition with, without sorting, and with various sort algorithms. We find that sparse tensor transposition with count sort performs best among other options. However, with the best performant count sort variant, sparse tensor transposition still becomes the performance bottleneck in tensor computations with mixed tensor operation types, such as Sparse-Tensor-Times-Vector (SpTTV). To resolve sparse tensor transpose as a bottleneck, we further investigate possible sparse tensor algorithm designs and propose an efficient new sparse tensor algorithm by integrating bucket sort and count sort. The evaluation results show that our algorithm is faster than the state-of-the-art (SOTA) approach, with 1.2x speedup on average and up to 2.3x speedup with multithreading. There is also potential to further improve the performance of sparse tensor transpose by selectively enabling the SOTA approach or ours on particular dimensions of coordinates with respect to the coordinate distribution.

关键词： parallel sorting algorithm sparse tensor algebra sparse tensor transposition

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Improving HPC Application Performance in Public Cloud

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IERI Procedia 2014年 10卷 169-176页

作者： Rashid Hassani Md Aiatullah Peter Luksch University of Rostock Rostock 18059 Germany

Improving as well as evaluating the performance of High Performance Computing (HPC) applications by migrating them to Cloud environments are widely considered as critical issues in the field of high performance and Cloud computing. However, poor network performance, heterogeneous and dynamic environments are some series of pitfalls for execution of HPC applications in Cloud. This paper proposes a new approach to improve the performance and scalability of HPC applications on Amazon's HPC Cloud. The evidence from our approach points a significant improvement in speed up and scale up with the response rate of more than 20 percent parallel efﬁciency on the Cloud in comparison to dedicated HPC cluster. We state that the EC2 Cloud system is a feasible platform for deploying on-demand, small sized HPC applications.

关键词： Cloud computing HPC applications parallel sorting algorithm MPI Amazon EC2

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Improving HPC Application Performance in Public Cloud

Improving HPC Application Performance in Public Cloud

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International Conference on Future Information Engineering(FIE 2014)

作者： Rashid Hassani Md Aiatullah Peter Luksch University of Rostock

Improving and evaluating the performance of HPC applications to realize the interchange intrinsic by migrating them to Cloud environments are widely considered as critical issues in the field of high performance and Cloud computing. However, poor network performance, heterogeneous and dynamic environments are some bottlenecks for execution of HPC applications on Cloud. This paper proposes a new approach to improve the performance and scalability of HPC applications on Amazon's HPC Cloud. The evidence from our approach points a significant improvement in speed up and scale up with the response rate of more than 20 percent parallel efficiency on the Cloud in comparison to dedicated HPC cluster. We state that the EC2 Cloud system is a feasible platform for deploying on-demand, small sized HPC applications.

关键词： Cloud computing HPC applications parallel sorting algorithm MPI Amazon EC2

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parallelIZATION OF BITONIC SORT AND RADIX SORT algorithmS ON MANY CORE GPUS

PARALLELIZATION OF BITONIC SORT AND RADIX SORT ALGORITHMS ON...

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10th International Conference on Electronics, Computer and Computation (ICECCO)

作者： Yildiz, Zehra Aydin, Musa Yilmaz, Guray Okan Univ Dept Informat Syst & Technol Istanbul Turkey Istanbul Aydin Univ Dept Elect & Elect Engn Istanbul Turkey Turkish Air Force Acad Dept Comp Engn Istanbul Turkey

ISBN: (纸本)9781479933433

Data sorting is used in many fields and plays an important role in defining the overall speed and performance. There are many sorting categories. In this study, two of these sorting algorithms that are bitonic sort and radix sort are dealt with. We have designed and developed Radix Sort and Bitonic Sort algorithms for many core Graphics Processing Units (GPUs). Although bitonic sort is a concurrent sorting algorithm, radix sort is a distribution sorting algorithm, i.e. both of these algorithms are not usual sorting algorithms. They can be parallelized on GPUs easily to get better performance than other sorting algorithms. We parallelized these sorting algorithms on many core GPUs using the Compute Unified Device Architecture (CUDA) platform, developed by NVIDIA Corporation and got some performance measurements.

关键词： Graphics Processing Unit radix sort bitonic sort parallel computing parallel sorting algorithm CUDA

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Optimized GPU sorting algorithms on Special Input Distributions

Optimized GPU Sorting Algorithms on Special Input Distributi...

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11th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)

作者： Yang, Quan Du, Zhihui Zhang, Sen Tsinghua Univ Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China State Univ Newyork Dept Math Comp Sci & Stat Albany NY 13820 USA

ISBN: (纸本)9780769548180

We present a high performance graphics processing unit (GPU) sorting algorithm ISSD (Improved sorting considering Special Distributions) implemented with the Compute Unified Device Architecture (CUDA). The ISSD focuses on two aspects to improve parallel sorting performance. One is how to decompose the sorting tasks into independent and balanced subtasks which can then be easily distributed to thousands of threads to realize the concept of "parallel sorting" as well as to efficiently explore the power of GPU. The other one is how to take advantage of special data distributions to further optimize the algorithms and improve their performance. The algorithm is redesigned based on our previous general data distribution version and optimized both on general implementation methods and special input distributions. Experimental results show that for the general data distribution inputs, the ISSD outperforms the existing parallel sorting algorithms by about 10% in performance due to its practical optimization in implementation;and for three special data distribution inputs, the ISSD outperforms the existing algorithms by more than 40% due to its special optimization based on the data distributions. Therefore, the algorithm is viable and efficient when dealing with specific data distributions.

关键词： GPU parallel sorting algorithm special data distribution

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Optimized GPU sorting algorithms on Special Input Distributions

Optimized GPU Sorting Algorithms on Special Input Distributi...

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The Eleventh International Symposium on Distributed Computing and Applications to Business,Engineering and Science(DCABES2012)(第十一届分布式计算及其应用国际学术研讨会)(原名:电子商务、工程及科学领域的分布式计算和应用国际学术研讨会)

作者： Quan Yang Zhihui Du Sen Zhang Tsinghua National Laboratory for Information Science and Technology Department of Computer Science a Department of Mathematics Computer Science and StatisticsState University of New YorkNY 13820U.S.

We present a high performance graphics processing unit(GPU)sorting algorithm ISSD(Improved sorting considering Special Distributions)implemented with the Compute Unified Device Architecture(CUDA).The ISSD focuses on two aspects to improve parallel sorting *** is how to decompose the sorting tasks into independent and balanced subtasks which can then be easily distributed to thousands of threads to realize the concept of “parallel sorting” as well as to efficiently explore the power of *** other one is how to take advantage of special data distributions to further optimize the algorithms and improve their *** algorithm is redesigned based on our previous general data distribution version and optimized both on general implementation methods and special input *** results show that for the general data distribution inputs,the ISSD outperforms the existing parallel sorting algorithms by about 10%in performance due to its practical optimization in implementation;and for three special data distribution inputs,the ISSD outperforms the existing algorithms by more than 40%due to its special optimization based on the data ***,the algorithm is viable and efficient when dealing with specific data distributions.

关键词： GPU parallel sorting algorithm special data distribution

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ROUTING NUMBERS OF CYCLES, COMPLETE BIPARTITE GRAPHS, AND HYPERCUBES

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SIAM JOURNAL ON DISCRETE MATHEMATICS 2010年第4期24卷 1482-1494页

作者： Li, Wei-Tian Lu, Linyuan Yang, Yiting Univ S Carolina Dept Math Columbia SC 29208 USA

The routing number rt(G) of a connected graph G is the minimum integer r so that every permutation of vertices can be routed in r steps by swapping the ends of disjoint edges. In this paper, we study the routing numbers of cycles, complete bipartite graphs, and hypercubes. We prove that rt(C(n)) = n - 1 (for n >= 3) and for s >= t, rt(K(s, t)) = [3s/2t] + O(1). We also prove n + 1 <= rt(Qn) = 2n - 2 for n >= 3. The lower bound rt(Qn) >= n + 1 was previously conjectured by Alon, Chung, and Graham [SIAM J. Discrete Math., 7 (1994), pp. 513- 530]. A variation, called fractional routing number, is also considered in this paper.

关键词： routing number parallel sorting algorithm

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A Fast and Flexible sorting algorithm with CUDA

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9th International Conference on algorithms and Architectures for parallel Processing

作者： Chen, Shifu Qin, Jing Xie, Yongming Zhao, Junping Heng, Pheng-Ann Chinese Univ Hong Kong Shenzhen Inst Adv Integrat Technol Chinese Acad Sci Hong Kong Hong Kong Peoples R China Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China Chinese Peoples Liberat Army Gen Hosp Postgrad Med Sch Inst Med Informat Beijing Peoples R China

ISBN: (纸本)9783642030949

In this paper, we propose a fast and flexible sorting algorithm with CUDA. The proposed algorithm is Much more practical than the previous GPU-based sorting algorithms, as it is able to handle the sorting of elements represented by integers, floats and structures. Meanwhile, our algorithm is optimized for the modern GPU architecture to obtain high performance. We use different strategies for sorting disorderly list and nearly-sorted list to make it adaptive. Extensive experiments demon- strate our algorithm has higher performance than previous GPU-based sorting algorithms and can support real-time applications.

关键词： parallel sorting algorithm CUDA GPU-based sorting algorithm

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Bulk synchronous parallel: practical experience with a model for parallel computing

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parallel COMPUTING 1999年第2期25卷 159-181页

作者： Krizanc, D Saarimaki, A Carleton Univ Sch Comp Sci Ottawa ON K1S 5B6 Canada

Valiant proposed the Bulk Synchronous parallel (BSP) model as a possible model for parallel computing. He refers to BSP as a "bridging" model, being applicable to both system and algorithm design. The model allows hardware and software design to proceed independently but ensures compatibility between parallel computers and parallel programs. This paper explores the practical use of BSP, focusing on the portability and predictability it offers, without incurring any significant loss in performance. A BSP algorithm for sorting proposed by Gerbessiotis and Valiant is implemented in a portable fashion on three different parallel computers, specifically an Intel iPSC/860, a Transtech Parastation and an Alex AVX Series 2. The program uses a standard library of communication functions designed and implemented for each machine to support the BSP model. The measured performance of the program is compared to the BSP predictions and to other sorting results on similar machines to provide evidence for the utility of the BSP model. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： Bulk Synchronous parallel (BSP) model bridging model parallel sorting algorithm prediction performance portability

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A parallel sorting algorithm FOR A NOVEL MODEL OF COMPUTATION

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INTERNATIONAL JOURNAL OF parallel PROGRAMMING 1991年第5期20卷 403-419页

作者： DAS, A MOSER, LE MELLIARSMITH, PM UNIV CALIF SANTA BARBARA DEPT ELECT & COMP ENGNSANTA BARBARACA 93106

The computational complexity of a parallel algorithm depends critically on the model of computation. We describe a simple and elegant rule-based model of computation in which processors apply rules asynchronously to pairs of objects from a global object space. Application of a rule to a pair of objects results in the creation of a new object if the objects satisfy the guard of the rule. The model can be efficiently implemented as a novel MIMD array processor architecture, the Intersecting Broadcast Machine. For this model of computation, we describe an efficient parallel sorting algorithm based on mergesort. The computational complexity of the sorting algorithm is O(n log2 n), comparable to that for specialized sorting networks and an improvement on the O(n1.5) complexity of conventional mesh-connected array processors.

关键词： parallel sorting algorithm RULE-BASED MODEL OF COMPUTATION MIMD ARRAY PROCESSOR ARCHITECTURE

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