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Enabling large-scale bioinformatics data analysis with cloud computing

Enabling large-scale bioinformatics data analysis with cloud...

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2012 10th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2012

作者： Karlsson, J. Torreño, O. Ramet, Daniel Klambauer, Günter Cano, M. Trelles, O. Department of Computer Architecture Malaga University Malaga Spain Institute of Bioinformatics Linz Austria

ISBN: (纸本)9780769547015

The petabyte scale of the Big Data generation in bioinformatics requires the introduction of advanced computational techniques to enable efficient knowledge discovery from data. Many data analysis tools in bioinformatics have been developed but few have been adapted to take advantage of high performance computing (HPC) resources. For some of these tools, an attractive option is to employ a map/reduce strategy. On the other hand, Cloud computing could be an important platform to run such tools in parallel because it provides on-demand, elastic computational resources. This paper presents a software suite for Microsoft Azure which supports legacy software (without modifications of the algorithm). We demonstrate the feasibility of the approach by benchmarking a typical bioinformatics tool, namely dotplot. © 2012 IEEE.

关键词： Big data

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Grid framework for parallel investigations of spiking neural microcircuits

Grid framework for parallel investigations of spiking neural...

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2012 11th international symposium on parallel and distributed computing, ISPDC 2012

作者： Muntean, Ioan Lucian Joldos, Marius Computer Science Department Technical University of Cluj-Napoca Romania

ISBN: (纸本)9780769548050

Simulation of spiking neural networks is computationally expensive and the employment of multicore processors can boost the performance of such simulations. Designing parallelization strategies that work well for different characteristics of the microcircuits entails expensive computations, leading to increased development times. To speed up the design of multicore software for computational neuroscience, we have developed a framework that exploits multicore systems available in grid computing environments. Due to the use of Grid SFEA plugins, common operations such as evaluation of parallelization strategies can be undertaken with very little effort. We evaluated the plugins for the development of a synchronous multicore spiking neural simulator. This uses the spike response model combined with the phenomenological model of spike time dependent synapse plasticity. The parallelization uses OpenMP, the microcircuits have small world topologies and count up to 104 neurons and 107 synapses with biological details. With this novel framework more complex investigations in computational neuroscience such as analysis of the dynamics of neural microcircuits could be tackled. © 2012 IEEE.

关键词： Neural networks

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Fast and Efficient Graph Traversal Algorithm for CPUs: Maximizing Single-Node Efficiency

Fast and Efficient Graph Traversal Algorithm for CPUs: Maxim...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Chhugani, Jatin Satish, Nadathur Kim, Changkyu Sewall, Jason Dubey, Pradeep Intel Corp Parallel Comp Lab Santa Clara CA 95051 USA

ISBN: (纸本)9780769546759

Graph-based structures are being increasingly used to model data and relations among data in a number of fields. Graph-based databases are becoming more popular as a means to better represent such data. Graph traversal is a key component in graph algorithms such as reachability and graph matching. Since the scale of data stored and queried in these databases is increasing, it is important to obtain high performing implementations of graph traversal that can efficiently utilize the processing power of modern processors. In this work, we present a scalable Breadth-First Search Traversal algorithm for modern multi-socket, multi-core CPUs. Our algorithm uses lock- and atomic-free operations on a cache-resident structure for arbitrary sized graphs to filter out expensive main memory accesses, and completely and efficiently utilizes all available bandwidth resources. We propose a work distribution approach for multi-socket platforms that ensures load-balancing while keeping cross-socket communication low. We provide a detailed analytical model that accurately projects the performance of our single- and multi-socket traversal algorithms to within 5-10% of obtained performance. Our analytical model serves as a useful tool to analyze performance bottlenecks on modern CPUs. When measured on various synthetic and real-world graphs with a wide range of graph sizes, vertex degrees and graph diameters, our implementation on a dual-socket Intel (R) Xeon (R) X5570 (Intel microarchitecture code name Nehalem) system achieves 1.5X-13.2X performance speedup over the best reported numbers. We achieve around 1 Billion traversed edges per second on a scale-free R-MAT graph with 64M vertices and 2 Billion edges on a dual-socket Nehalem system. Our optimized algorithm is useful as a building block for efficient multi-node implementations and future exascale systems, thereby allowing them to ride the trend of increasing per-node compute and bandwidth resources.

关键词： bandwidth efficient Graph traversal multi-socket single node

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Simulating the Spread of Infectious Disease over Large Realistic Social Networks using Charm plus

Simulating the Spread of Infectious Disease over Large Reali...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Bisset, Keith R. Aji, Ashwin M. Bohm, Eric Kale, Laxmikant V. Kamal, Tariq Marathe, Madhav V. Yeom, Jae-Seung Virginia Tech Virginia Bioinformat Inst Blacksburg VA 24061 USA Aalto TKK FIN-00076 Espoo Finland

ISBN: (纸本)9780769546766

Preventing and controlling outbreaks of infectious diseases such as pandemic influenza is a top public health priority. EpiSimdemics is an implementation of a scalable parallel algorithm to simulate the spread of contagion, including disease, fear and information, in large (10(8) individuals), realistic social contact networks using individual-based models. It also has a rich language for describing public policy and agent behavior. We describe CharmSimdemics and evaluate its performance on national scale populations. Charm++ is a machine independent parallel programming system, providing high-level mechanisms and strategies to facilitate the task of developing highly complex parallel applications. Our design includes mapping of application entities to tasks, leveraging the efficient and scalable communication, synchronization and load balancing strategies of Charm++. Our experimental results on a 768 core system show that the Charm++ version achieves up to a 4-fold increase in performance when compared to the MPI version.

关键词： Computational Epidemiology parallel Efficiency and Scalability Agent Based Simulation Programming Models Charm plus MPI

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SDP as a service (SDPaaS): A new revenue stream for operators

SDP as a service (SDPaaS): A new revenue stream for operator...

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2012 10th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2012

作者： Sánchez, Luis Angel Galindo Rodríguez, Joaquín Salvachúa Department of Innovation 2.0 Telefonica Madrid Spain Universidad Carlos III de Madrid Spain Departamento de Ingeniería de Sistemas Telemáticos ETSIT Universidad Politecnica de Madrid Madrid Spain

ISBN: (纸本)9780769547015

Today, telcos and Internet players are obliged to define new business models sustainable. In the telcos, Service Deliver Platform (SDP) is a key logical entity to deliver services and is the point where mix Internet and telco assets. In parallel, Cloud computing has become a major issue to offer services on demand. In our approach, we tackle a step forward to build up a SDP in the cloud, which can be offered to those operators with lacks in the SDP infrastructure needed to deliver new services to the clients. © 2012 IEEE.

关键词： Cloud computing

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High Performance Non-uniform FFT on Modern x86-based Multi-core Systems

High Performance Non-uniform FFT on Modern x86-based Multi-c...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Kalamkar, Dhiraj D. Trzasko, Joshua D. Sridharan, Srinivas Smelyanskiy, Mikhail Kim, Daehyun Manduca, Armando Shu, Yunhong Bernstein, Matt A. Kaul, Bharat Dubey, Pradeep Intel Labs Parallel Comp Lab Bangalore Karnataka India Intel Labs Parallel Comp Lab Santa Clara CA 95052 USA Mayo Clin Dept Physiol & Biomed Engn Rochester MN 55905 USA Mayo Clin Dept Radiol Rochester MN 55905 USA

ISBN: (纸本)9780769546759

The Non-Uniform Fast Fourier Transform (NUFFT) is a generalization of FFT to non-equidistant samples. It has many applications which vary from medical imaging to radio astronomy to the numerical solution of partial differential equations. Despite recent advances in speeding up NUFFT on various platforms, its practical applications are still limited, due to its high computational cost, which is significantly dominated by the convolution of a signal between a non-uniform and uniform grids. The computational cost of the NUFFT is particularly detrimental in cases which require fast reconstruction times, such as iterative 3D non-Cartesian MRI reconstruction. We propose novel and highly scalable parallel algorithm for performing NUFFT on x86-based multi-core CPUs. The high performance of our algorithm relies on good SIMD utilization and high parallel efficiency. On convolution, we demonstrate on average 90% SIMD efficiency using SSE, as well up to linear scalability using a quad-socket 40-core Intel (R) Xeon (R) E7-4870 Processors based system. As a result, on dual socket Intel (R) Xeon (R) X5670 based server, our NUFFT implementation is more than 4x faster compared to the best available NUFFT3D implementation, when run on the same hardware. On Intel (R) Xeon (R) E5-2670 processor based server, our NUFFT implementation is 1.5X faster than any published NUFFT implementation today. Such speed improvement opens new usages for NUFFT. For example, iterative multichannel reconstruction of a 240x240x240 image could execute in just over 3 minutes, which is on the same order as contemporary non-iterative (and thus less-accurate) 3D NUFFT-based MRI reconstructions.

关键词： Non-uniform FFT parallelization Scalability Vectorization

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A scalable parallel debugging library with pluggable communication protocols 12

A scalable parallel debugging library with pluggable communi...

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12th IEEE/ACM international symposium on Cluster, Cloud and Grid computing, CCGrid 2012

作者： Jin, Chao Abramson, David Dinh, Minh Ngoc Gontarek, Andrew Moench, Robert DeRose, Luiz Faculty of Information Technology Monash University Caulfield VIC Australia Cray Inc. Cray Plaza 380 Jackson St St. Paul MN 55101 United States

ISBN: (纸本)9780769546919

parallel debugging faces challenges in both scalability and efficiency. A number of advanced methods have been invented to improve the efficiency of parallel debugging. As the scale of system increases, these methods highly rely on a scalable communication protocol in order to be utilized in large-scale distributed environments. This paper describes a debugging middleware that provides fundamental debugging functions supporting multiple communication protocols. Its pluggable architecture allows users to select proper communication protocols as plug-ins for debugging on different platforms. It aims to be utilized by various advanced debugging technologies across different computing platforms. The performance of this debugging middleware is examined on a Cray XE Supercomputer with 21,760 CPU cores. © 2012 IEEE.

关键词： Middleware

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Two-Dimensional Dynamic Loop Scheduling Schemes for Computer Clusters

Two-Dimensional Dynamic Loop Scheduling Schemes for Computer...

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11th IEEE international symposium on Network computing and Applications (NCA)

作者： Chronopoulos, Anthony T. Penmatsa, Satish Jayakumar, Naveen Ogharandukun, Eric Univ Texas San Antonio Dept Comp Sci San Antonio TX 78249 USA Univ Maryland Eastern Shore Dept Math & Comp Sci Princess Anne MD USA

ISBN: (纸本)9780769547732

Efficient scheduling of parallel loops in a network of computers can significantly reduce the total execution time of complex scientific applications. In this paper, we compare the performance of two-dimensional dynamic loop scheduling schemes for computer clusters with that of one-dimensional loop scheduling schemes. The loop scheduling schemes are implemented using the Message Passing Interface on a cluster of processors. Experimental results show that the two-dimensional scheduling schemes were found to significantly reduce the total execution time of tasks over the one-dimensional schemes. In addition, the two-dimensional schemes present a more balanced load distribution of the workload among the computers in the cluster.

关键词： Dynamic scheduling cluster computing parallel loops

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The Research and Analysis of Hungarian Algorithm in the Structure Index Reduction for DAE

The Research and Analysis of Hungarian Algorithm in the Stru...

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11th international symposium on distributed computing and Applications to Business, Engineering and Science (DCABES)

作者： Zeng, Yan Wu, Xuesong Cao, Jianwen Chinese Acad Sci Inst Software Lab Parallel Software & Computat Sci Software Beijing 100190 Peoples R China

ISBN: (纸本)9780769548180

Modeling of complex physical systems with Modelica usually leads to the high-index differential algebraic equation system (DAE), index reduction is an important part of solving the high-index DAE. The structure index reduction algorithm is one of the popular methods, but in special cases, it fails. Combinatorial relaxation algorithm can detect and correct the breakdown situation. And the maximum weight matching of bipartite graph is an important part of the combinatorial relaxation algorithm. In order to choose the proper method for the large-scale, dense bipartite graph, this paper provides three implementations of the Hungarian algorithm. The experiment results and the theory show that the BFS single-augmented method is better than others.

关键词： Modelica Bipartite Graph DAE Hungarian Algorithm Augmenting Path

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Adapting Matrix-Vector-Multiply Wavefront Reconstruction to SMP

Adapting Matrix-Vector-Multiply Wavefront Reconstruction to ...

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11th international symposium on distributed computing and Applications to Business, Engineering and Science (DCABES)

作者： Zhang, Haotian Li, Mei Zhou, Luchun Chinese Acad Sci Key Lab Adapt Opt Inst Opt & Elect Chengdu Peoples R China

ISBN: (纸本)9780769548180

In adaptive optics systems, the process time of wavefront controller is a critical parameter. For a fixed frame rate, decreasing the process time results in higher control bandwidth. Among the process steps of a wavefront controller, wavefront reconstruction is a time consuming task. In this paper, we parallelized wavefront reconstruction algorithm on a cutting edge shared-memory eight-core DSP to reduce process time. The conducted experiment shows that even using the most computation and memory intensive matrix-vector-multiply (MVM) reconstruction algorithm, performance requirements can be met with reconstruction latency around 130us in a 913 actuators AO system. With parallelization of the reconstruction algorithm, it's possible to apply high frame rate in the system and easy to scale up to larger systems with more actuators.

关键词： Adaptive Optics Wavefront reconstruction DSP parallel processing

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