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检索条件"任意字段=13th IEEE International Symposium on Parallel and Distributed Processing with Applications"

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Improving Communication Performance and Scalability of Native applications on Intel Xeon Phi Coprocessor Clusters

Improving Communication Performance and Scalability of Nativ...

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international symposium on parallel and distributed processing (IPDPS)

作者： Karthikeyan Vaidyanathan Kiran Pamnany Dhiraj D. Kalamkar Alexander Heinecke Mikhail Smelyanskiy Jongsoo Park Daehyun Kim Aniruddha Shet G. Bharat Kaul Balint Joo Pradeep Dubey Parallel Computing Lab Intel Corporation Bangalore India Department of Informatics Technische Universitiit Miinchen Munich Germany Intel Corp Santa Clara CA US Parallel Computing Lab Intel Corporation Santa Clara CA U.S.A Thomas Jefferson National Accelerator Facility Newport News VA U.S.A

ISBN: (纸本)9781479938018

Intel Xeon Phi coprocessor-based clusters offer high compute and memory performance for parallel workloads and also support direct network access. Many real world applications are significantly impacted by network characteristics and to maximize the performance of such applications on these clusters, it is particularly important to effectively saturate network bandwidth and/or hide communications latency. We demonstrate how to do so using techniques such as pipelined DMAs for data transfer, dynamic chunk sizing, and better asynchronous progress. We also show a method for, and the impact of avoiding serialization and maximizing parallelism during application communication phases. Additionally, we apply application optimizations focused on balancing computation and communication in order to hide communication latency and improve utilization of cores and of network bandwidth. We demonstrate the impact of our techniques on three well known and highly optimized HPC kernels running natively on the Intel Xeon Phi coprocessor. For the Wilson-Dslash operator from Lattice QCD, we characterize the improvements from each of our optimizations for communication performance, apply our method for maximizing concurrency during communication phases, and show an overall 48% improvement from our previously best published result. For HPL/LINPACK, we show 68.5% efficiency with 97 TFLOPs on 128 Intel Xeon Phi coprocessors, the first ever reported native HPL efficiency on a coprocessor-based supercomputer. For FFT, we show 10.8 TFLOPs using 1024 Intel Xeon Phi coprocessors on the TACC Stampede cluster, the highest reported performance on any Intel Architecture-based cluster and the first such result to be reported on a coprocessor-based supercomputer.

关键词： Message systems Coprocessors Bandwidth Lattices Optimization parallel processing Kernel

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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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Optimization of Multi-level Checkpoint Model for Large Scale HPC applications

Optimization of Multi-level Checkpoint Model for Large Scale...

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international symposium on parallel and distributed processing (IPDPS)

作者： Sheng Di Mohamed Slim Bouguerra Leonardo Bautista-Gomez Franck Cappello Argonne National Laboratory USA

ISBN: (纸本)9781479938018

HPC community projects that future extreme scale systems will be much less stable than current Petascale systems, thus requiring sophisticated fault tolerance to guarantee the completion of large scale numerical computations. Execution failures may occur due to multiple factors with different scales, from transient uncorrectable memory errors localized in processes to massive system outages. Multi-level checkpoint/restart is a promising model that provides an elastic response to tolerate different types of failures. It stores checkpoints at different levels: e.g., local memory, remote memory, using a software RAID, local SSD, remote file system. In this paper, we respond to two open questions: 1) how to optimize the selection of checkpoint levels based on failure distributions observed in a system, 2) how to compute the optimal checkpoint intervals for each of these levels. the contribution is three-fold. (1) We build a mathematical model to fit the multi-level checkpoint/restart mechanism with large scale applications regarding various types of failures. (2) We theoretically optimize the entire execution performance for each parallel application by selecting the best checkpoint level combination and corresponding checkpoint intervals. (3) We characterize checkpoint overheads on different checkpoint levels in a real cluster environment, and evaluate our optimal solutions using both simulation with millions of cores and real environment with real-world MPI programs running on hundreds of cores. Experiments show that optimized selections of levels associated with optimal checkpoint intervals at each level outperforms other state-of-the-art solutions by 5-50 percent.

关键词： Hardware Mathematical model Equations Transient analysis Computational modeling Iterative methods Optimization

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Enhancing availability of grid computational services to ubiquitous computing applications

Enhancing availability of grid computational services to ubi...

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international symposium on parallel and distributed processing (IPDPS)

作者： N. Roy S.K. Das K. Basu K. Kumar Center for Research Wireless Mobility and Networking (CReWMaN) Department of Computer Science and Engineering University of Texas Arlington Arlington TX USA

the grid is an integrated infrastructure that can play the dual roles of a coordinated resource consumer as well as a donator in distributed computing environments. In a mobile grid environment, the grid acts as a resource hungry consumer whereas in a ubiquitous computing environment, it has the inherent potential to provide services to applications. the enormous growth in the use of mobile and embedded devices in ubiquitous computing environment and their interaction with human beings, produces a huge amount of data that need to be processed efficiently anytime anywhere. However, such devices often have limited resources in terms of CPU, storage, battery power and communication bandwidth. thus, there is a need to transfer ubiquitous computing application services to more powerful computational resources. In this paper, we investigate the use of the grid as a candidate for provisioning computational services to applications in ubiquitous computing environments. In particular, we present a competitive model that describes the possible interaction between the competing resources in the grid infrastructure as service providers and ubiquitous applications as subscribers. the competition takes place in terms of quality of service (QoS) and cost offered by different grid service providers. the ubiquitous users' resource demands depend not only on the QoS parameters (e.g., response time and loss probability, i.e., loss of ubiquitous users experienced by a grid service provider in our context) offered by that service provider but also upon those of its competitors. We develop a stochastic equilibrium model for QoS assurance. Based upon those QoS parameters, we propose two types of demand models whose distribution functions are closely correlated with service level QoS parameters. We also present the equilibrium behavior of our model facing global competition under stochastic demand and estimate guaranteed QoS assurance level by efficiently satisfying the requirement of ubiq

关键词： Availability Grid computing Pervasive computing Ubiquitous computing Quality of service Mobile computing Computer applications Stochastic processes distributed computing Humans

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Exploiting Flow Graph of System of ODEs to Accelerate the Simulation of Biologically-Detailed Neural Networks

Exploiting Flow Graph of System of ODEs to Accelerate the Si...

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international symposium on parallel and distributed processing (IPDPS)

作者： Bruno R. C. Magalhães Michael Hines thomas Sterling Felix Schüermann Blue Brain Project École polytechnique fédérale de Lausanne Switzerland Yale University New Haven CT US CREST - Center for Research in Extreme Scale Technologies Indiana University Bloomington 47404 IN

Exposing parallelism in scientific applications has become a core requirement for efficiently running on modern distributed multicore SIMD compute architectures. the granularity of parallelism that can be attained is a key determinant for the achievable acceleration and time to solution. Motivated by a scientific use case that requires the simulation of long spans of time - the study of plasticity and learning in detailed models of brain tissue - we present a strategy that exposes and exploits multicore and SIMD micro-parallelism from unrolling flow dependencies and concurrent outputs in a large system of coupled ordinary differential equations (ODEs). An implementation of a parallel simulator is presented, running on the HPX runtime system for the ParalleX execution model, providing dynamic taskscheduling and asynchronous execution. the implementation was tested on different architectures using a previously published brain tissue model. Benchmark of single neurons on a single compute node present a speed-up of circa 4-7× when compared with the state of the art Single Instruction Multiple Data (SIMD) implementation and 13-40× over its Single Instruction Single Data (SISD) counterpart. Large scale benchmarks suggest almost ideal strong scaling and a speed-up of 2-8× on a distributed architecture of 128 Cray X6 compute nodes.

关键词： Computational modeling Neurons Mathematical model Biological system modeling Brain modeling parallel processing

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Optimizing Busy Time on parallel Machines

Optimizing Busy Time on Parallel Machines

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international symposium on parallel and distributed processing (IPDPS)

作者： George B. Mertzios Mordechai Shalom Ariella Voloshin Prudence W.H. Wong Shmuel Zaks School of Engineering and Computing Sciences Durham University Durham UK TelHai College Upper Galilee Israel Department of Computer Science Technion-Israel Institute of Technology Haifa Israel Department of Computer Science University of Liverpool Liverpool UK

We consider the following fundamental scheduling problem in which the input consists of n jobs to be scheduled on a set of identical machines of bounded capacity g (which is the maximal number of jobs that can be processed simultaneously by a single machine). Each job is associated with a start time and a completion time, it is supposed to be processed from the start time to the completion time (and in one of our extensions it has to be scheduled also in a continuous number of days, this corresponds to a two-dimensional version of the problem). We consider two versions of the problem. In the scheduling minimization version the goal is to minimize the total busy time of machines used to schedule all jobs. In the resource allocation maximization version the goal is to maximize the number of jobs that are scheduled for processing under a budget constraint given in terms of busy time. this is the first study of the maximization version of the problem. the minimization problem is known to be NP-Hard, thus the maximization problem is also NP-Hard. We consider various special cases, identify cases where an optimal solution can be computed in polynomial time, and mainly provide constant factor approximation algorithms for both minimization and maximization problems. Some of our results improve upon the best known results for this job scheduling problem. Our study has applications in power consumption, cloud computing and optimizing switching cost of optical networks.

关键词： Schedules Optimal scheduling Approximation algorithms Mercury (metals) Approximation methods parallel processing Minimization

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GPGPU-based data parallel region growing algorithm for cell nuclei detection

GPGPU-based data parallel region growing algorithm for cell ...

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international symposium on Computational Intelligence and Informatics

作者： Sándor Szénási Zoltán Vámossy Miklós Kozlovszky John von Neumann Faculty of Informatics Óbuda University Budapest Hungary Laboratory of Parallel and Distributed Computing MTA SZTAKI Budapest Hungary

Nowadays microscopic analysis of tissue samples is done more and more by using digital imagery and special immunodiagnostic software. these are typically specific applications developed for one distinct field, but some subroutines are commonly repeated, for example several applications contain steps that can detect cell nuclei in a sample image. the aim of our research is developing a new data parallel algorithm that can be implemented even in a GPGPU environment and that is capable of counting hematoxylin eosin (HE) stained cell nuclei and of identifying their exact locations and sizes (using a variation of the region growing method). Our presentation contains the detailed description of the algorithm, the peculiarity of the CUDA implementation, and the evaluation of the created application (regarding its accuracy and the decrease in the execution time).

关键词： Graphics processing unit Kernel Instruction sets Computer architecture Algorithm design and analysis Microprocessors Synchronization

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Optimization of applications with non-blocking neighborhood collectives via multisends on the Blue Gene/P supercomputer

Optimization of applications with non-blocking neighborhood ...

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international symposium on parallel and distributed processing (IPDPS)

作者： Sameer Kumar Philip Heidelberger Dong Chen Michael Hines IBM Thomas J. Watson Research Center Yorktown Heights NY USA Department of Computer Science Yale University New Heaven CT USA

ISBN: (纸本)9781424464425

We explore the multisend interface as a data mover interface to optimize applications with neighborhood collective communication operations. One of the limitations of the current MPI 2.1 standard is that the vector collective calls require counts and displacements (zero and non-zero bytes) to be specified for all the processors in the communicator. Further, all the collective calls in MPI 2.1 are blocking and do not permit overlap of communication with computation in the same thread of execution. However, multisends are non-blocking calls that permit overlap of computation and communication. We present the record replay persistent optimization to the multisend interface th at minimizes the processor overhead of initiating the collective. We present four different case studies with the multisend API on Blue Gene/P (i) 3D-FFT, (ii) 4D nearest neighbor exchange as used in Quantum Chromodynamics, (iii) NAMD and (iv) neural network simulator NEURON. Performance results show 1.9× speedup with 32 3 3D-FFTs, 1.9× speedup for 4D nearest neighbor exchange with the 2 4 problem, 1.6× speedup in NAMD and almost 3× speedup in NEURON with 256K cells and 1k connections/cell.

关键词： Supercomputers Neurons Neural networks Application software Communication standards Nearest neighbor searches Libraries Proposals Buffer storage Computer science

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Kernel Specialization for Improved Adaptability and Performance on Graphics processing Units (GPUs)

Kernel Specialization for Improved Adaptability and Performa...

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international symposium on parallel and distributed processing (IPDPS)

作者： Nicholas Moore Miriam Leeser Laurie Smith King Mathworks Company Natick MA USA Department of Electrical and Computer Engineering Northeastern University Boston MA USA Department of Mathematics and Computer Science College of Holy Cross Worcester MA USA

ISBN: (纸本)9781467360661

Graphics processing units (GPUs) offer significant speedups over CPUs for certain classes of applications. However, programming for GPUs is challenging. there are many parameters that affect performance and their values may change depending on both problem instance and GPU hardware specifics. In addition, most GPU kernels are compiled once; performance optimizations are applied at application compile time. As a result, many GPU libraries and programs have limited adaptability to variations among problem instances and hardware configurations. these factors limit code reuse and the applicability of GPU computing to a wider variety of problems. this paper introduces GPGPU kernel specialization, a technique used to describe highly adaptable kernels that exhibit high performance across a wide range of programmer variables as well as different generations of GPUs. We also introduce our GPU Prototyping Framework (GPU-PF) for dynamic runtime generation of customized GPU kernels incorporating both problem and implementation-specific parameters. GPU-PF fully separates the GPU and CPU code so the GPU code can be compiled during program execution once all the parameters are known. this work explores the implementation and parameterization of two real world applications targeting two generations of NVIDIA CUDA-enabled GPUs using kernel specialization and GPU-PF: large template matching and cone-beam image reconstruction via backprojection. Starting with high performance GPU kernels that compare favorably to multi-threaded reference implementations, kernel specialization is shown to increase adaptability while providing performance improvements including improved run time and reduction in resource usage. Kernel specialization offers productivity benefits, improved library code, and a means to increase the parameterizability of GPGPU implementations.

关键词： Kernel Graphics processing units Runtime Hardware Registers Optimization Libraries

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Massively parallel Model of Extended Memory Use in Evolutionary Game Dynamics

Massively Parallel Model of Extended Memory Use in Evolution...

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international symposium on parallel and distributed processing (IPDPS)

作者： Amanda Peters Randles David G. Rand Christopher Lee Greg Morrisett Jayanta Sircar Martin A. Nowak Hanspeter Pfister School of Engineering and Applied Sciences Harvard University Cambridge MA USA Program for Evolutionary Dynamics Harvard University Cambridge MA USA

ISBN: (纸本)9781467360661

To study the emergence of cooperative behavior, we have developed a scalable parallel framework for evolutionary game dynamics. this is a critical computational tool enabling large-scale agent simulation research. An important aspect is the amount of history, or memory steps, that each agent can keep. When six memory steps are taken into account, the strategy space spans 24096 potential strategies, requiring large populations of agents. We introduce a multi-level decomposition method that allows us to exploit both multi-node and thread-level parallel scaling while minimizing communication overhead. We present the results of a production run modeling up to six memory steps for populations consisting of up to 1018 agents, making this study one of the largest yet undertaken. the high rate of mutation within the population results in a non-trivial parallel implementation. the strong and weak scaling studies provide insight into parallel scalability and programmability trade-offs for large-scale simulations, while exhibiting near perfect weak and strong scaling on 16,384 tasks on Blue Gene/Q. We further show 99% weak scaling up to 294,912 processors 82% strong scaling efficiency up to 262,144 processors of Blue Gene/P. Our framework marks an important step in the study of game dynamics with potential applications in fields ranging from biology to economics and sociology.

关键词： Sociology Games Statistics Computational modeling thin film transistors Program processors History

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