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An Approach to parallelize Kruskal's Algorithm Using Helper Threads

An Approach to Parallelize Kruskal's Algorithm Using Helper ...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Anastasios Katsigiannis Nikos Anastopoulos Konstantinos Nikas Nectarios Koziris School of Electrical and Computer Engineering Computing Systems Laboratory National and Technical University of Athens Greece

ISBN: (纸本)9781467309745

In this paper we present a Helper Threading scheme used to parallelize efficiently Kruskal's Minimum Spanning Forest algorithm. This algorithm is known for exhibiting inherently sequential characteristics. More specifically, the strict order by which the algorithm checks the edges of a given graph is the main reason behind the lack of explicit parallelism. Our proposed scheme attempts to overcome the imposed restrictions and improve the performance of the algorithm. The results show that for a wide range of graphs of varying structure, size and density the parallelization of Kruskal's algorithm is feasible. Observed speedups reach up to 5.5 for 8 running threads, revealing the potentials of our approach.

关键词： Partitioning algorithms Arrays parallel processing Synchronization Instruction sets Educational institutions Multicore processing

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Embodied computing: Self-adaptation in Bio-inspired Reconfigurable Architectures

Embodied Computing: Self-adaptation in Bio-inspired Reconfig...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Laurent Rodriguez Benoît Miramond Imen Kalbousi Bertrand Granado 8051 CNRS / ENSEA /UCP ETIS Laboratory UMR Cergy-Pontoise France

This paper describes a bio-inspired architectural approach to design highly adaptive and reconfigurable systems in the context of mobile robotics. The aim is to design the hardware architecture of an intelligent controller for a robot that exhibits several behaviors such as landscape learning, obstacle avoidance, path planning, sensory-motor control. The concerned robot evolves in an indoor unknown environment and uses the visual informations coming from its input sensors to reach its goal. The Embodied computing approach presented in this paper is employed in this context to integrate the reconfiguration management as a part of the behavior of the global system. Thus the controller will be able to self-organize its reconfigurable processing elements in order to adapt its architecture to the environment and to the robot actions. We propose in this paper a hardware implementation of the approach based on artificial neural networks. We present the results of our first prototype onto the last technology of FPGA.

关键词： Computer architecture Neurons Robot sensing systems Microprocessors Hardware Field programmable gate arrays

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A use of matrix with GVT computation in optimistic time warp algorithm for parallel simulation

A use of matrix with GVT computation in optimistic time warp...

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15th Communications and Networking symposium 2012, CNS 2012, Part of the 2012 Spring Simulation Multiconference, SpringSim 2012

作者： Potham, Shalini Rizvi, Syed S. Elleithy, Khaled M. Riasat, Aasia Computer Science and Engineering Department University of Bridgeport Bridgeport CT 06601 United States Electronics Engineering Technology Department ECPI University Virginia Beach VA 23462 United States Department of Computer Science Institute of Business Management Karachi Pakistan

ISBN: (纸本)9781618397850

One of the most common optimistic synchronization protocols for parallel simulation is the Time Warp algorithm proposed by Jefferson [12]. Time Warp algorithm is based on the virtual time paradigm that has the potential for greater exploitation of parallelism and, perhaps more importantly, greater transparency of the synchronization mechanism to the simulation programmer. It is widely believe that the optimistic Time Warp algorithm suffers from large memory consumption due to frequent rollbacks. In order to achieve optimal memory management, Time Warp algorithm needs to periodically reclaim the memory. In order to determine which event-messages have been committed and which portion of memory can be reclaimed, the computation of global virtual time (GVT) is essential. Mattern [2] uses a distributed snapshot algorithm to approximate GVT which does not rely on first in first out (FIFO) channels. Specifically, it uses ring structure to establish cuts C1 and C2 to calculate the GVT for distinguishing between the safe and unsafe event-messages. Although, distributed snapshot algorithm provides a straightforward way for computing GVT, more efficient solutions for message acknowledging and delaying of sending event messages while awaiting control messages are desired. This paper studies the memory requirement and time complexity of GVT computation. The main objective of this paper is to implement the concept of matrix with the original Mattern's GVT algorithm to speedups the process of GVT computation while at the same time reduce the memory requirement. Our analysis shows that the use of matrix in GVT computation improves the overall performance in terms of memory saving and latency.

关键词： Discrete event simulation

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Virtual Machine Resource Allocation for Service Hosting on Heterogeneous distributed Platforms

Virtual Machine Resource Allocation for Service Hosting on H...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Mark Stillwell Frédéric Vivien Henri Casanova Université de Lyon France Department of Engineering Computing Cranfield University Cranfield UK INRIA France LIP Ecole Normale Supérieure de Lyon France Department of Information and Computer Sciences University of Hawaii at Mānoa Honolulu USA

ISBN: (纸本)9781467309752

We propose algorithms for allocating multiple resources to competing services running in virtual machines on heterogeneous distributed platforms. We develop a theoretical problem formulation and compare these algorithms via simulation experiments based in part on workload data supplied by Google. Our main finding is that vector packing approaches proposed in the homogeneous case can be extended to provide high-quality solutions in the heterogeneous case, and combined to provide a single efficient algorithm. We also consider the case when there may be bounded errors in estimates of performance-related resource needs. We provide a heuristic for compensating for such errors that performs well in simulation, as well as a proof of the worst-case competitive ratio for the single-resource, single-node case when there is no bound on the error.

关键词： Resource management Vectors Aggregates Sorting Virtual machining Random access memory Greedy algorithms

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On the Correctness of Mixing Lazy and Eager Version Management in Transactions

On the Correctness of Mixing Lazy and Eager Version Manageme...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Lihang Zhao Jeff Draper Information Sciences Institute University of Southern California Marina del Rey CA USA

ISBN: (纸本)9781467309745

Transactional memory has been proposed as an optimistic concurrency-control construct to ease parallel programming. Hardware transactional memory (HTM) approaches implement version management and conflict detection in hardware to guarantee the correctness of transaction execution. Based on the style of version management and conflict detection, state-of-the-art HTM systems fall into two main types, namely lazy systems and eager systems. Neither system type is able to always perform better than the other over a wide range of applications due to the broad variations in the execution behaviors in typical parallel workloads. In this paper, we focus on the correctness of mixing lazy and eager version management in a log-based HTM. This hybrid type of version management is demonstrated to satisfy the requirement of atomicity and conflict serializability, which are critical for correctness. Furthermore, it is shown that the new approach does not violate the memory coherence formal model.

关键词： Coherence Memory management Buffer storage Hardware Concurrent computing Instruction sets

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Inducing Temporal parallel Properties into Time Dependent Problems

Inducing Temporal Parallel Properties into Time Dependent Pr...

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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： N.Kokulan C.-H.Lai School of Computing and Mathematical Sciences University of Greenwich London UK

This paper provides an overview of the current status of methods that may be used to induce parallel properties into the temporal axis for time dependent problems described by differential *** extension to problems wi... 详细信息

关键词： Temporal parallel methods time dependent problems

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Efficient Image Re-Ranking Computation on GPUs

Efficient Image Re-Ranking Computation on GPUs

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Daniel Carlos Guimarães Pedronette Ricardo da_S. Torres Edson Borin Mauricio Breternitz Institute of Computing (IC) State University of Campinas-UNICAMP Campinas Brazil Advanced Micro Devices Inc. Austin USA

The huge growth of image collections and multimedia resources available is remarkable. One of the most common approaches to support image searches relies on the use of Content-Based Image Retrieval (CBIR) systems. CBIR systems aim at retrieving the most similar images in a collection, given a query image. Since the effectiveness of those systems is very dependent on the accuracy of ranking approaches, re-ranking algorithms have been proposed to exploit contextual information and improve the effectiveness of CBIR systems. Image re-ranking algorithms typically consider the relationship among every image in a given dataset when computing the new ranking. This approach demands a huge amount of computational power, which may render it prohibitive on very large data sets. In order to mitigate this problem, we propose using the computational power of Graphics Processing Units (GPU) to speedup the computation of image re-ranking algorithms. GPUs are fast emerging and relatively inexpensive parallel processors that are becoming available on a wide range of computer systems. In this paper, we propose a parallel implementation of an image re-ranking algorithm designed to fit the computational model of GPUs. Experimental results demonstrate that relevant performance gains can be obtained by our approach.

关键词： Context Kernel Algorithm design and analysis Graphics processing unit Image processing Image retrieval

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Exploiting parallelism in a X-ray Tomography Reconstruction Algorithm on Hybrid Multi-GPU and Multi-core Platforms

Exploiting Parallelism in a X-ray Tomography Reconstruction ...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Ernesto Liria Daniel Higuero Monica Abella Claudia de Molina Manuel Desco Universidad Carlos III de Madrid Madrid Spain Hospital General Universitario Gregorio Marañón Madrid Spain

Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp et al. Currently there are a strong need to speed-up the reconstruction of XRay CT data in order to extend its clinical applications. We present an efficient modular implementation of an FDK-based reconstruction algorithm that takes advantage of the parallel computing capabilities and the efficient bilinear interpolation provided by general purpose graphic processing units (GPGPU). The proposed implementation of the algorithm is evaluated for a high-resolution micro-CT and achieves a speed-up of 46, while preserving the reconstructed image quality.

关键词： Graphics processing unit Computed tomography Image reconstruction parallel processing X-ray imaging Geometry Detectors

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AzureBench: Benchmarking the Storage Services of the Azure Cloud Platform

AzureBench: Benchmarking the Storage Services of the Azure C...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Dinesh Agarwal Sushil K. Prasad Department of Computer Science Georgia State University Atlanta USA

ISBN: (纸本)9781467309745

Cloud computing is becoming mainstream for High Performance computing (HPC) application development over the last few years. However, even though many vendors have rolled out their commercial cloud infrastructures, the service offerings are usually only best-effort based, without any performance guarantees. Cloud computing effectively saves the eScience developer the hassles of resource provisioning but utilization of these resources will be questionable if it can not meet the performance expectations of deployed applications. Furthermore, in order to make application design choices for a particular cloud offering, an eScience developer needs to understand the performance capabilities of the underlying cloud platform. Among all clouds, the emerging Azure cloud from Microsoft remains a challenge for HPC program development both due to lack of its support for traditional parallel programming support such as MPI and map-reduce and due to its evolving APIs. To aid the HPC developers, we present an open-source benchmark suite, Azure Bench, for Windows Azure cloud platform. We report comprehensive performance analysis of Azure cloud platform's storage services which are its primary artifacts for inter-processor coordination and communication. We also report on how much scalability Azure platform affords using up to 100 processors and point out various bottlenecks in parallel access of storage services. The paper also has pointers to overcome the steep learning curve for HPC application development over Azure. We also provide an open-source generic application framework that can be a starting point for application development for bag-of-task applications over Azure.

关键词： Cloud computing Throughput Synchronization Benchmark testing Programming Open source software Scalability

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The SPAS-UAH Cluster for the JEM-EUSO computing Model

The SPAS-UAH Cluster for the JEM-EUSO Computing Model

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： J.A. Morales de los Ríos G. Sáez-Cano H. Prieto L. del Peral J.H. Carretero K. Shinozaki M.D. Rodríguez-Frías SPace & AStroparticle (SPAS) Group UAH Madrid Spain RIKEN 2-1 Hirosawa Wako Saitama Japan

The JEM-EUSO space observatory will be launched and attached to the Japanese module of the international Space Station (ISS) in 2016. Its aims is to observe UV photon tracks produced by Ultra High Energy Cosmic Rays (UHECR) and Extremely High Energy Cosmic Rays (EHECR) developing in the atmosphere and producing Extensive Air Showers (EAS). JEM-EUSO will use our atmosphere as a huge calorimeter, to detect the electromagnetic and hadronic components of the EAS. For High Energy Physic (HEP) experiments the huge amount of data and complex analysis algorithms require the use of advanced GRID computational resources. Therefore a complete infrastructure is needed for the simulation and data analysis, in the frame of the GRID architecture, and computing infrastructure, intended for the JEM-EUSO space mission software. Moreover solutions to account for a complete installed cluster system, with the software and data repositories, as well as a many other details are pointed out.

关键词： Atmospheric modeling Software Data analysis Linux Data models Analytical models Terrestrial atmosphere

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