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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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WPress: An Application-Driven Performance Benchmark for Cloud-Based Virtual Machines

WPress: An Application-Driven Performance Benchmark for Clou...

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International Conference on Enterprise Distributed Object computing (EDOC)

作者： Amir Hossein Borhani Philipp Leitner Bu-Sung Lee Xiaorong Li Terence Hung Institute of High-Performance Computing (IHPC) Singapore s.e.a.l. software evolution & architecture lab University of Zurich Switzerland Parallel and Distributed Computing Center (PDCC) Nanyang Technological University Singapore

ISBN: (纸本)9781479954711

Approaching a comprehensive performance benchmark for on-line transaction processing (OLTP) applications in a cloud environment is a challenging task. Fundamental features of clouds, such as the pay-as-you-go pricing model and unknown underlying configuration of the system, are contrary to the basic assumptions of available benchmarks such as TPC-W or RUBiS. In this paper, we introduce a systematic performance benchmark approach for OLTP applications on public clouds that use virtual machines(VMs). We propose WPress benchmark, which is based on the widespread blogging software, WordPress, as a representative OLTP application and implement an open source workload generator. Furthermore, we utilize a CPU micro-benchmark to investigate CPU performance of cloud-based VMs in greater detail. Average response time and total VM cost are the performance metrics measured by WPress. We evaluate small and large instance types of three real-life cloud providers, Amazon EC2, Microsoft Azure and Rackspace cloud. Results imply that Rackspace cloud has better average response times and total VM cost on small instances. However, Microsoft Azure is preferable for large instance type.

关键词： Benchmark testing Cloud computing Time factors Servers Databases Blogs Publishing

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The stability performances improvement through kinematic and dynamic modeling of the hopping robots 10

The stability performances improvement through kinematic and...

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10th UKACC International Conference on Control, CONTROL 2014

作者： Bruja, Adrian Vladareanu, Luige Yu, Hongnian Wang, Hongbo Liu, Jingjing Bucharest Romania School of Design Engineering and Computing Bournemouth University Poole DorsetBH12 5BB United Kingdom Parallel Robot and Mechatronic System Laboratory of Hebei Province Key Lab. of Adv. Forging and Stamping Technol. and Sci. of Ministry of Education Yanshan University Qinhuangdao China

ISBN: (纸本)9781479950119

The paper presents an innovative design for a wheeled hopping robot. Our main objective was to obtain a stable and efficient robot, which can jump over obstacles and has the ability to reach a certain ledge. The innovative design of our robot has the capability to jump to a certain distance even with a zero initial velocity provided by the wheels movement. Also, we took into consideration the wind speed which can prevent our robot to reach the desired destination, and compensated with an initial velocity on the direction of movement. For testing we designed a simulation which had as inputs different initial conditions to test and present the jumping capability of our robot in different jumping conditions. In the end we provide a jump area which the robot can reach for certain initial conditions, so we can later chose the optimal one for reaching the target position. © 2014 IEEE.

关键词： Machine design

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An online service-oriented performance profiling tool for cloud computing systems

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Frontiers of Computer Science 2013年第3期7卷 431-445页

作者： Haibo MI Huaimin WANG Yangfan ZHOU Michael Rung-Tsong LY~ Hua CAI Gang YIN National Lab for Parallel & Distributed Processing National University of Defense Technology Changsha 410073 China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen 518000 China Computing Platform Alibaba Cloud Computing Company Hangzhou 310000 China

The growing scale and complexity of component interactions in cloud computing systems post great challenges for operators to understand the characteristics of system performance. Profiling has long been proved to be an effective approach to performance analysis; however, existing approaches confront new challenges that emerge in cloud computing systems. First, the efficiency of the profiling becomes of critical concern; second, service-oriented profiling should be considered to support separation-of-concerns performance analysis. To address the above issues, in this paper, we present P-Tracer, an online performance profiling tool specifically tailored for cloud computing systems. P-Tracer constructs a specific search engine that proactively processes performance logs and generates a particular index for fast queries; second, for each service, P-Tracer retrieves a statistical insight of performance characteristics from multi-dimensions and provides operators with a suite of web-based interfaces to query the critical information. We evaluate P- Tracer in the aspects of tracing overheads, data preprocessing scalability and querying efficiency. Three real-world case studies that happened in Alibaba cloud computing platform demonstrate that P-Tracer can help operators understand soft-ware behaviors and localize the primary causes of performance anomalies effectively and efficiently.

关键词： cloud computing performance profiling performance anomaly visual analytics

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WorkQ: A many-core producer/consumer execution model applied to PGAS computations

WorkQ: A many-core producer/consumer execution model applied...

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International Conference on parallel and Distributed Systems (ICPADS)

作者： David Ozog Allen Malony Jeff R. Hammond Pavan Balaji Dept. of Computer and Information Science University of Oregon Eugene Oregon Parallel Computing Lab Intel Corporation Hillsboro Oregon Math. and Computer Science Div. Argonne National Laboratory Lemont Illinois

ISBN: (纸本)9781479976164

Partitioned global address space (PGAS) applications, such as the Tensor Contraction Engine (TCE) in NWChem, often apply a one-process-per-core mapping in which each process iterates through the following work-processing cycle: (1) determine a work-item dynamically, (2) get data via one-sided operations on remote blocks, (3) perform computation on the data locally, (4) put (or accumulate) resultant data into an appropriate remote location, and (5) repeat the cycle. However, this simple flow of execution does not effectively hide communication latency costs despite the opportunities for making asynchronous progress. Utilizing nonblocking communication calls is not sufficient unless care is taken to efficiently manage a responsive queue of outstanding communication requests. This paper presents a new runtime model and its library implementation for managing tunable “work queues” in PGAS applications. Our runtime execution model, called WorkQ, assigns some number of on-node “producer” processes to primarily do communication (steps 1, 2, 4, and 5) and the other “consumer” processes to do computation (step 3); but processes can switch roles dynamically for the sake of performance. Load balance, synchronization, and overlap of communication and computation are facilitated by a tunable nodewise FIFO message queue protocol. Our WorkQ library implementation enables an MPI+X hybrid programming model where the X comprises SysV message queues and the user's choice of SysV, POSIX, and MPI shared memory. We develop a simplified software mini-application that mimics the performance behavior of the TCE at arbitrary scale, and we show that the WorkQ engine outperforms the original model by about a factor of 2. We also show performance improvement in the TCE coupled cluster module of NWChem.

关键词： Computational modeling Libraries Tensile stress Load modeling Electronics packaging Engines Runtime

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A new energy efficient cluster-head and backup selection scheme in WSN

A new energy efficient cluster-head and backup selection sch...

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2013 IEEE 14th International Conference on Information Reuse and Integration, IEEE IRI 2013

作者： Izadi, Davood Abawajy, Jemal Ghanavati, Sara Parallel and Distributed Computing Lab School of Information Technology Deakin University Geelong Australia

ISBN: (纸本)9781479910502

Despite significant advancements in wireless sensor networks (WSNs), energy conservation remains one of the most important research challenges. Proper organization of nodes (clustering) is one of the major techniques to expand the lifespan of the whole network through aggregating data at the cluster head. The cluster head is the backbone of the entire cluster. That means if a cluster head fails to accomplish its function, the received and collected data by cluster head can be lost. Moreover, the energy consumption following direct communications from sources to base stations will be increased. In this paper, we propose a type-2 fuzzy based self-configurable cluster head selection (SCCH) approach to not only consider the selection criterion of the cluster head but also present the cluster backup approach. Thus, in case of cluster failure, the system still works in an efficient way. The novelty of this protocol is the ability of handling communication uncertainty, which is an inherent operational aspect of sensor networks. The experiment results indicate SCCH performs better than other recently developed methods. © 2013 IEEE.

关键词： Wireless sensor networks

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Lattice QCD on Intel® Xeon Phi™ coprocessors

Lattice QCD on Intel® Xeon Phi™ coprocessors

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28th International Supercomputing Conference on Supercomputing, ISC 2013

作者： Joó, Bálint Kalamkar, Dhiraj D. Vaidyanathan, Karthikeyan Smelyanskiy, Mikhail Pamnany, Kiran Lee, Victor W. Dubey, Pradeep Watson III, William Thomas Jefferson National Accelerator Facility Newport News VA United States Parallel Computing Lab. Intel Corporation Bangalore India Parallel Computing Lab. Intel Corporation Santa Clara CA United States

ISBN: (纸本)9783642387494

Lattice Quantum Chromodynamics (LQCD) is currently the only known model independent, non perturbative computational method for calculations in the theory of the strong interactions, and is of importance in studies of nuclear and high energy physics. LQCD codes use large fractions of supercomputing cycles worldwide and are often amongst the first to be ported to new high performance computing architectures. The recently released Intel Xeon Phi architecture from Intel Corporation features parallelism at the level of many x86-based cores, multiple threads per core, and vector processing units. In this contribution, we describe our experiences with optimizing a key LQCD kernel for the Xeon Phi architecture. On a single node, using single precision, our Dslash kernel sustains a performance of up to 320 GFLOPS, while our Conjugate Gradients solver sustains up to 237 GFLOPS. Furthermore we demonstrate a fully 'native' multi-node LQCD implementation running entirely on KNC nodes with minimum involvement of the host CPU. Our multi-node implementation of the solver has been strong scaled to 3.9 TFLOPS on 32 KNCs. © 2013 Springer-Verlag.

关键词： Quantum theory

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parallel Bayesian Network Structure Learning for Genome-Scale Gene Networks

Parallel Bayesian Network Structure Learning for Genome-Scal...

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Supercomputing Conference

作者： Sanchit Misra Md. Vasimuddin Kiran Pamnany Sriram P. Chockalingam Yong Dong Min Xie Maneesha R. Aluru Srinivas Aluru Parallel Computing Lab Intel Corporation Bangalore India Dept. of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai India State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China School of Biology Georgia Institute of Technology Atlanta USA School of Computational Science and Engineering Georgia Institute of Technology Atlanta USA

Learning Bayesian networks is NP-hard. Even with recent progress in heuristic and parallel algorithms, modeling capabilities still fall short of the scale of the problems encountered. In this paper, we present a massively parallel method for Bayesian network structure learning, and demonstrate its capability by constructing genome-scale gene networks of the model plant Arabidopsis thaliana from over 168.5 million gene expression values. We report strong scaling efficiency of 75% and demonstrate scaling to 1.57 million cores of the Tianhe-2 supercomputer. Our results constitute three and five orders of magnitude increase over previously published results in the scale of data analyzed and computations performed, respectively. We achieve this through algorithmic innovations, using efficient techniques to distribute work across all compute nodes, all available processors and coprocessors on each node, all available threads on each processor and coprocessor, and vectorization techniques to maximize single thread performance.

关键词： Bayes methods Hypercubes Instruction sets Genomics Bioinformatics Coprocessors Vectors

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Modeling communication in cache-coherent SMP systems - A case study with Xeon Phi

Modeling communication in cache-coherent SMP systems - A cas...

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22nd ACM International Symposium on High-Performance parallel and Distributed computing, HPDC 2013

作者： Ramos, Sabela Hoefler, Torsten Computer Architecture Group University of A Coruña A Coruña Spain Scalable Parallel Computing Lab. ETH Zurich Zurich Switzerland

ISBN: (纸本)9781450319102

Most multi-core and some many-core processors implement cache coherency protocols that heavily complicate the design of optimal parallel algorithms. Communication is performed implicitly by cache line transfers between cores, complicating the understanding of performance properties. We developed an intuitive performance model for cache-coherent architectures and demonstrate its use with the currently most scalable cache-coherent many-core architecture, Intel Xeon Phi. Using our model, we develop several optimal and optimized algorithms for complex parallel data exchanges. All algorithms that were developed with the model beat the performance of the highly-tuned vendor-specific Intel OpenMP and MPI libraries by up to a factor of 4.3. The model can be simplified to satisfy the tradeoff between complexity of algorithm design and accuracy. We expect that our model can serve as a vehicle for advanced algorithm design. © 2013 ACM.

关键词： Electronic data interchange

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Profiling Phishing Email Based on Clustering Approach

Profiling Phishing Email Based on Clustering Approach

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Isredza Rahmi A. Hamid Jemal H. Abawajy Parallel and Distributed Computing Lab Deakin University Victoria Australia

In this paper, an approach for profiling email-born phishing activities is proposed. Profiling phishing activities are useful in determining the activity of an individual or a particular group of phishers. By generating profiles, phishing activities can be well understood and observed. Typically, work in the area of phishing is intended at detection of phishing emails, whereas we concentrate on profiling the phishing email. We formulate the profiling problem as a clustering problem using the various features in the phishing emails as feature vectors. Further, we generate profiles based on clustering predictions. These predictions are further utilized to generate complete profiles of these emails. The performance of the clustering algorithms at the earlier stage is crucial for the effectiveness of this model. We carried out an experimental evaluation to determine the performance of many classification algorithms by incorporating clustering approach in our model. Our proposed profiling email-born phishing algorithm (ProEP) demonstrates promising results with the RatioSize rules for selecting the optimal number of clusters.

关键词： Electronic mail Clustering algorithms Classification algorithms Data models Feature extraction Prediction algorithms Computational modeling

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