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Vertex-Centric Graph processing on FPGA

Vertex-Centric Graph Processing on FPGA

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Annual ieee symposium on Field-Programmable Custom Computing Machines (FCCM)

作者： Nina Engelhardt Hayden Kwok-Hay So Department of Electrical and Electronic Engineering University of Hong Kong

ISBN: (纸本)9781509023578

Past research and implementation efforts have shown that FPGAs are efficient at processing many graph algorithms. However, they are notoriously hard to program, leading to impractically long development times even for simple applications. We propose a vertex-centric framework for graph processing on FPGAs, providing a base execution model and distributed architecture so that developers need only write very small application kernels.

关键词： Kernel Field programmable gate arrays Programming Electronic mail Computer architecture Optimization Memory

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Optimization of an Electromagnetics Code with Multicore Wavefront Diamond Blocking and Multi-dimensional Intra-Tile parallelization

Optimization of an Electromagnetics Code with Multicore Wave...

引用

international symposium on parallel and distributed processing (IPDPS)

作者： Tareq M. Malas Julian Hornich Georg Hager Hatem Ltaief Christoph Pflaum David E. Keyes Extreme Computing Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia Dept. of Comput. Sci. Friedrich-Alexander Univ. Erlangen-Nυrnberg Erlangen Germany Erlangen Regional Comput. Center Friedrich-Alexander Univ. Erlangen-Nυrnberg Erlangen Germany Erlangen Graduate School in Advanced Optical Technologies (SAOT) Friedrich-Alexander University Erlangen-Ntirnberg (FAU) Erlangen Germany

ISBN: (纸本)9781509021413

Understanding and optimizing the properties of solar cells is becoming a key issue in the search for alternatives to nuclear and fossil energy sources. A theoretical analysis via numerical simulations involves solving Maxwell's Equations in discretized form and typically requires substantial computing effort. We start from a hybrid-parallel (MPI+OpenMP) production code that implements the Time Harmonic Inverse Iteration Method (THIIM) with Finite-Difference Frequency Domain (FDFD) discretization. Although this algorithm has the characteristics of a strongly bandwidth-bound stencil update scheme, it is significantly different from the popular stencil types that have been exhaustively studied in the high performance computing literature to date. We apply a recently developed stencil optimization technique, multicore wavefront diamond tiling with multi-dimensional cache block sharing, and describe in detail the peculiarities that need to be considered due to the special stencil structure. Concurrency in updating the components of the electric and magnetic fields provides an additional level of parallelism. The dependence of the cache size requirement of the optimized code on the blocking parameters is modeled accurately, and an auto-tuner searches for optimal configurations in the remaining parameter space. We were able to completely decouple the execution from the memory bandwidth bottleneck, accelerating the implementation by a factor of three to four compared to an optimal implementation with pure spatial blocking on an 18-core Intel Haswell CPU.

关键词： Diamond Instruction sets Mathematical model Bandwidth Photovoltaic cells Maxwell equations Multicore processing

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Storage-Optimized Data-Atomic Algorithms for Handling Erasures and Errors in distributed Storage Systems

Storage-Optimized Data-Atomic Algorithms for Handling Erasur...

引用

international symposium on parallel and distributed processing (IPDPS)

作者： Kishori M. Konwar N. Prakash Erez Kantor Nancy Lynch Muriel Médard Alexander A. Schwarzmann Department of EECS MIT MA USA Departrnent of Computer Science NEU MA USA Department of CSE UConn. Storrs CT USA

ISBN: (纸本)9781509021413

Erasure codes are increasingly being studied in the context of implementing atomic memory objects in large scale asynchronous distributed storage systems. When compared with the traditional replication based schemes, erasure codes have the potential of significantly lowering storage and communication costs while simultaneously guaranteeing the desired resiliency levels. In this work, we propose the Storage-Optimized Data-Atomic (SODA) algorithm for implementing atomic memory objects in the multi-writer multi-reader setting. SODA uses Maximum Distance Separable (MDS) codes, and is specifically designed to optimize the total storage cost for a given fault-tolerance requirement. For tolerating f server crashes in an n-server system, SODA uses an [n, k] MDS code with k = n - f, and incurs a total storage cost of n/n-f. SODA is designed under the assumption of reliable point-to-point communication channels. The communication cost of a write and a read operation are respectively given by O(f 2 ) and n/n-f(δ w +1), where δ w denotes the number of writes that are concurrent with the particular read. In comparison with the recent CASGC algorithm [1], which also uses MDS codes, SODA offers lower storage cost while pays more on the communication cost. We also present a modification of SODA, called SODA err , to handle the case where some of the servers can return erroneous coded elements during a read operation. Specifically, in order to tolerate f server failures and e error-prone coded elements, the SODAerr algorithm uses an [n, k] MDS code such that k = n - 2e - f. SODAerr also guarantees liveness and atomicity, while maintaining an optimized total storage cost of n/n-f-2e.

关键词： Servers Algorithm design and analysis Computer crashes Fault tolerance Fault tolerant systems Spread spectrum communication

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GPU accelerated substructuring methods for sparse linear systems

GPU accelerated substructuring methods for sparse linear sys...

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第十五届分布式计算及其应用国际学术研讨会

作者： Abal-Kassim Cheik Ahamed Frédéric Magoulès CUDA Research Center & Applied Mathematics and Systems Laboratory CentraleSupélec Université Paris Saclay

ISBN: (纸本)9781509035946

In this paper,we present and analyze parallel substructuring methods based on conjugate gradient method,a iterative Krylov method,for solving sparse linear systems on *** experiments performed on a set of matrices coming from the finite element analysis of large scale engineering problems,show the efficiency and robustness of substructuring methods based on iterative Krylov method for solving sparse linear systems in a context of a hybrid multi-core-GPU.

关键词： Graphics processing units Computer architecture Instruction sets Linear systems Programming Central processing Unit Hardware

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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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Dynamic Reconfiguration of Data parallel Programs

Dynamic Reconfiguration of Data Parallel Programs

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international symposium on Computer Architecture and High Performance Computing (SBAC-PAD)

作者： Vinícius Dias Wagner Meira Dorgival Guedes Department of Computer Science Universidade Federal de Minas Gerais

ISBN: (纸本)9781509061099

Given the large amount of data from different sources that have become available to researchers in multiple fields, Data Science has emerged as a new paradigm for exploring and getting value from that data. In that context, new parallel processing environments with abstract programming interfaces, like Spark, were proposed to try to simplify the development of distributed programs. Although such solutions have become widely used, achieving the best performance with them is still not always straight-forward, despite the multiple run-time strategies they use. In this work we analyze some of the causes of performance degradation in such systems and, based on that analysis, we propose a tool to improve performance by dynamically adjusting data partitioning and parallelism degree in recurrent applications based on previous executions. Our results applying that methodology show consistent reductions in execution time for the applications considered, with gains of up to 50%.

关键词： Sparks parallel processing Partitioning algorithms Measurement Itemsets Algorithm design and analysis Data mining

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Approximate adder with output correction for error tolerant applications and Gaussian distributed inputs

Approximate adder with output correction for error tolerant ...

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international symposium on Circuits and Systems

作者： Darjn Esposito Gerardo Castellano Davide De Caro Ettore Napoli Nicola Petra Antonio G. M. Strollo Dept. of Electrical Engineering and Information Technology University of Napoli “Federico II” Italy

ISBN: (纸本)9781479953424

Approximate computing is emerging as a new paradigm to improve digital circuit performance by relaxing the requirement of performing exact calculations. Approximate adders rely on the idea that for uniformly distributed inputs, long carry-propagation chains are rarely activated. Unfortunately, however, the above assumption on input signal statistics is not always verified;in this paper we focus on the case (often encountered in practical signal processing applications) when the inputs have a Gaussian distribution. We show that for Gaussian inputs the error probability of previously proposed approximate adders approaches 25% for low sigma values, which is much larger than the uniform case. On the basis of this analysis, we propose an approximate adder with a correction circuit that drastically reduces the error rate for Gaussian distributed operand s. In order to investigate the performance of our approach in a real application, simulated results for a simple audio processing system are reported. Implementation results in 65nm technology are also presented.

关键词： Imprecise hardware Approximate computing Approximate adder Arithmetic circuits

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Distinct Random Sampling from a distributed Stream 29

Distinct Random Sampling from a Distributed Stream

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29th ieee international parallel and distributed processing symposium (IPDPS)

作者： Chung, Yung-Yu Tirthapura, Srikanta Iowa State Univ 2215 Coover Hall Ames IA 50011 USA

ISBN: (纸本)9781479986484

We consider continuous maintenance of a random sample of distinct elements from a massive data stream, whose input elements are observed at multiple distributed sites that communicate via a central coordinator. At any point, when a query is received at the coordinator, it responds with a random sample from the set of all distinct elements observed at the different sites so far. We present the first algorithms for distinct random sampling from a distributed stream. We also present a lower bound on the expected number of messages that must be transmitted by any distributed algorithm, showing that our algorithm is message optimal to within a factor of four. We present extensions to sliding windows, and experimental results showing the performance of our algorithm on real-world data sets.

关键词： Distinct Sampling Random Sampling distributed Stream Mining Distinct Elements

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Integrated QoS-aware Resource Provisioning for parallel and distributed applications 2015

Integrated QoS-aware Resource Provisioning for Parallel and ...

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19th ieee/ACM international symposium on distributed Simulation and Real Time applications (DS-RT)

作者： Li, Zengxiang Wang, Long Zhang, Yu Tram Truong-Huu Lim, En Sheng Mohan, Purnima Murali Chen, Shibin Ren, Shuqin Gurusamy, Mohan Qin, Zheng Goh, Rick Siow Mong ASTAR Inst High Performance Comp Singapore Singapore ASTAR Data Storage Inst Singapore Singapore Natl Univ Singapore Singapore Singapore

ISBN: (纸本)9781467378222

With more parallel and distributed applications moving to Cloud and data centers, it is challenging to provide predictable and controllable resources to multiple tenants, and thus guarantee application performance. In this paper, we propose an integrated QoS-aware resource provisioning platform based on virtualization technology for computing, storage and network resources. Coarse-grained CPU mapping and fine-grained CPU scheduling mechanisms are proposed to enable adjustable computing power. A hierarchical distributed scheduling mechanism is implemented on a scalable storage system to guarantee I/O throughput for individual tenants and applications. A network manager has also been developed to guarantee the data transmission rate. Web-based interface enables users to monitor realtime resource utilization and to adjust resource QoS levels on the fly. According to our experimental results, the resource cost can be saved up to 45% without degrading the performance of a distributed data processing benchmark;and the performance of a parallel agent-based simulation can be improved by 91% using the same amount of resources.

关键词： Cloud computing quality of service virtualization resource provisioning multi-tenant data centers

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distributed Conformal Anomaly Detection

Distributed Conformal Anomaly Detection

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international Conference on Machine Learning and applications (ICMLA)

作者： Ilia Nouretdinov Royal Holloway University of London

ISBN: (纸本)9781509061686

Conformal approach to anomaly detection was recently developed as a reliable framework of classifying examples into normal and abnormal groups based on a training data set containing only normal examples. Its validity property is that a normal example, generated by the same distribution as the examples from the training set, is classified as anomaly with probability bounded from above by a pre-selected significance level. parallel processing of big data may require a split of the training set into several sources. We also assume that the collection of data for two or more sources might be done in parallel and the data distribution may differ for these sources. The contribution of this work to conformal anomaly detection is studying the ways of keeping conformal validity when the training set is obtained from heterogeneous (differently distributed) sources.

关键词： Training Testing Reliability Big data Loss measurement Machine learning algorithms Data models

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