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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Xiaoyi Lu Jian Lin Li Zha Zhiwei Xu Chinese Academy and Sciences Beijing China Institute of Computing Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

In large organizations or IDCs, different departments always occupy and maintain dedicated resources to satisfy their or their customers' heterogeneous application loads. This situation easily makes the infrastructure management a repeated and inefficient work. Even worse, it is difficult to share the resources owned by different departments even when they are idle, because the application modes on these resources are quite different. This paper introduces a live system, Vega LingCloud, which provides a Resource Single Leasing Point System for consolidated renting physical and virtual machines to support heterogeneous application modes on shared infrastructure. Furthermore, we present the asset-leasing model and the architecture of Vega LingCloud. According to the evaluation, Vega LingCloud is better than other systems like Open Nebula and Enomaly ECP in the aspects of uniformity, flexibility, security, usability, and efficiency. The experimental result of management overhead shows that the deployment speed of virtual machine in Vega LingCloud is 4.1 times of that in the Open Nebula and VIDA hybrid system for deploying 64 virtual machines concurrently. From a representative micro-cloud example in a research group, we show that the consolidated way of leasing physical and virtual machine in Vega LingCloud is approbatory. Up to now, Vega LingCloud has been deployed in real world environments, which include a private cloud of large organization in Beijing and a public cloud in the Dongguan IDC of China. The resource scale of the Dongguan cloud reaches about 504 cores, 625 GB memory, and 156 TB storage. The number of supported real applications in Beijing and Dongguan clouds has exceeded 35, and their modes involve high performance computing, large scale data processing, virtual machine leasing, data storage, and so on.

关键词： Cloud computing Virtual machining Home appliances Engines Computer architecture Computational modeling Software

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Toolchain for Programming, Simulating and Studying the XMT Many-Core Architecture

Toolchain for Programming, Simulating and Studying the XMT M...

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

作者： Fuat Keceli Alexandros Tzannes George C. Caragea Rajeev Barua Uzi Vishkin University of Maryland College Park USA

The Explicit Multi-Threading (XMT) is a general-purpose many-core computing platform, with the vision of a 1000-core chip that is easy to program but does not compromise on performance. This paper presents a publicly available tool chain for XMT, complete with a highly configurable cycle-accurate simulator and an optimizing compiler. The XMT tool chain has matured and has been validated to a point where its description merits publication. In particular, research and experimentation enabled by the tool chain played a central role in supporting the ease-of-programming and performance aspects of the XMT architecture. The compiler and the simulator are also important milestones for an efficient programmer's workflow from PRAM algorithms to programs that run on the shared memory XMT hardware. This workflow is a key component in accomplishing the dual goal of ease-of-programming and performance. The applicability of our tool chain extends beyond specific XMT choices. It can be used to explore the much greater design space of shared memory many-cores by system researchers or by programmers. As the tool chain can practically run on any computer, it provides a supportive environment for teaching parallel algorithmic thinking with a programming component. Unobstructed by techniques such as decomposition-first and programming for locality, this environment may be useful in deferring the teaching of these techniques, when desired, to more advanced or platform-specific courses.

关键词： Computer architecture parallel processing Programming Program processors Phase change random access memory Algorithm design and analysis Assembly

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High-performance, power-aware computing - HPPAC

IEEE International Symposium on Parallel and Distributed Pro...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum 2011年 795-795页

作者： Ge, Rong Gioiosa, Roberto Bellosa, Frank Boku, Taisuke Chen, Yuan Cher, Chen-Yong Cesati, Marco De Supinski, Bronis Feng, Xizhou Feng, Wu-Chun Hsu, Chung-Hsing Isci, Canturk Knauerhase, Rob Lefevre, Laurent Lowenthal, David Nakashima, Hiroshi Nathuji, Ripal Schwan, Karsten Torres, Jordi Marquette University United States Barcelona Supercomputing Center Spain University of Karlsruhe Germany University of Tsukuba Japan HP Labs United States IBM United States University of Rome Tor Vergata Italy LLNL United States Virginia Tech. United States Oak Ridge National Laboratory United States Intel Labs United States INRIA France University of Arizona United States Kyoto University Japan Microsoft United States Georgia Tech. United States BSC Spain

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Toward a Cloud Architecture for Medical Imagery Grid applications : The Acigna-G Project

Toward a Cloud Architecture for Medical Imagery Grid applica...

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international symposium on Programming and Systems (ISPS)

作者： Tarik Zakaria Benmerar Fatima Oulebsir Boumghar Acigna Inc. ParIMed LRPE University of Sciences and Technology Houari Boumediene Algiers Algeria

Acigna-G is a new Grid computing platform we propose, for hosting and interacting with GNU/Linux Grid applications through a web portal, without or with a minimal API use. It aims to provide a convenient Cloud Service for Medical Imagery Grid applications. It extends our GIC architecture with an implementation of a light version of the Virtually-distribution parallel Architecture and the Multi-level Services architecture that permit the deployment of distributed Grid applications onto our platform. We propose these architecture as solutions to achieve both the convenience of PaaS Cloud services and the richness of Grid applications. We show how we deploy a MAS segmentation algorithm for Medical Imagery onto our Acigna-G platform.

关键词： Computer architecture Cloud computing Servers Biomedical imaging Grid computing Image segmentation Computational modeling

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NVCR: A Transparent Checkpoint-Restart Library for NVIDIA CUDA

NVCR: A Transparent Checkpoint-Restart Library for NVIDIA CU...

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

作者： Akira Nukada Hiroyuki Takizawa Satoshi Matsuoka CREST Japan Science and Technology Agency Japan Global Scientific Information and Computing Center Tokyo Institute of Technology Japan Graduate School of Information Sciences University of Tohoku Japan

Today, CUDA is the de facto standard programming framework to exploit the computational power of graphics processing units (GPUs) to accelerate various kinds of applications. For efficient use of a large GPU-accelerated system, one important mechanism is checkpoint-restart that can be used not only to improve fault tolerance but also to optimize node/slot allocation by suspending a job on one node and migrating the job to another node. Although several checkpoint-restart implementations have been developed so far, they do not support CUDA applications or have some severe limitations for CUDA support. Hence, we present a checkpoint-restart library for CUDA that first deletes all CUDA resources before check pointing and then restores them right after check pointing. It is necessary to restore each memory chunk at the same memory address. To this end, we propose a novel technique that replays memory related API calls. The library supports both CUDA runtime API and CUDA driver API. Moreover, the library is transparent to applications, it is not necessary to recompile the applications for check pointing. This paper demonstrates that the proposed library can achieve checkpoint-restart of various applications at acceptable overheads, and the library also works for MPI applications such as HPL.

关键词： Graphics processing unit Libraries Checkpointing Context Databases Instruction sets Arrays

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SPUN: A P2P Probabilistic Search Algorithm Based on Successful Paths in Unstructured Networks

SPUN: A P2P Probabilistic Search Algorithm Based on Successf...

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

作者： D.M. Rasanjalee Himali Sushil K. Prasad Department of Computer Science Georgia State University Atlanta GA USA

Efficient searching for information is an important goal in peer-to-peer (P2P) networks. Searching in an unstructured P2P network is particularly challenging due to the random nature of the P2P overlay links. In this paper, we propose a novel probabilistic search mechanism called SPUN, that increases the success ratio of queries while keeping the bandwidth consumption considerably low. SPUN is an informed search mechanism that improves upon state-of-art probabilistic mechanism, namely, the Adaptive Probabilistic Search (APS). The core principle of our algorithm is to exploit the successful query paths that develop during the lifetime of P2P network and converge toward the target objects. Our work introduces a new neighbor selection criterion which allows a peer to evaluate its neighbors based on the strength of successful paths the neighbor leads to. We also introduce a peer profile exchange mechanism that supports the reduction in uncertainty in peer selection decision. Our extensive simulation results confirm that our path-based algorithm performs 25% better than APS and several of its variants and is capable of achieving higher success ratios with fewer walkers each with an average message size of 71 bytes.

关键词： Indexes Peer to peer computing Probabilistic logic Search problems Heuristic algorithms History

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A Monitoring and Audit Logging Architecture for Data Location Compliance in Federated Cloud Infrastructures

A Monitoring and Audit Logging Architecture for Data Locatio...

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

作者： Philippe Massonet Syed Naqvi Christophe Ponsard Joseph Latanicki Benny Rochwerger Massimo Villari Centre dExcellence en Technologies de lInformation et de la Communication (CETIC) Belgium Thales Theresis France IBM Haifa Research Laboratory Israel University of Messina Italy

Current cloud infrastructures have opaque service offerings where customers cannot monitor the underlying physical infrastructure. This situation raises concerns for meeting compliance obligations by critical business applications with data location constraints that are deployed in a Cloud. When federated cloud infrastructures span across different countries where data can migrate from one country to another, it should be possible for data owners to monitor the location of their data. This paper shows how an existing federated Cloud monitoring infrastructure can be used for data location monitoring without compromising Cloud isolation. In the proposed approach collaboration is required between the cloud infrastructure provider (IP) and the user of the cloud, the service provider (SP): the IP monitors the virtual machines (VM) on the SP's behalf and makes the infrastructure level monitoring information available to him. With the monitoring information the SP can create the audit logs required for compliance auditing. The proposed logging architecture is validated by an e-Government case study with legal data location constraints.

关键词： Monitoring Security IP networks Cloud computing Legislation Electronic government Computer architecture

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Snap-Stabilizing Committee Coordination

Snap-Stabilizing Committee Coordination

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international symposium on parallel and distributed Processing (IPDPS)

作者： Borzoo Bonakdarpour Stephane Devismes Franck Petit Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada UMR 5104 VERIMAG Grenoble France LIP6 UPMC Paris 6 France

In this paper, we propose two snap-stabilizing distributed algorithms for the committee coordination problem. In this problem, a committee consists of a set of processes and committee meetings are synchronized, so that each process participates in at most one committee meeting at a time. Snap-stabilization is a versatile technique allowing to design algorithms that efficiently tolerate transient faults. Indeed, after a finite number of such faults (e.g. memory corruptions, message losses, etc), a snap-stabilizing algorithm immediately operates correctly, without any external intervention. We design snap-stabilizing committee coordination algorithms enriched with some desirable properties related to concurrency, (weak) fairness, and a stronger synchronization mechanism called 2-Phase Discussion Time. From previous papers, we know that (1) in the general case, (weak) fairness cannot be achieved in the committee coordination, and (2) it becomes feasible provided that each process waits for meetings infinitely often. Nevertheless, we show that even under this latter assumption, it is impossible to implement a fair solution that allows maximal concurrency. Hence, we propose two orthogonal snap-stabilizing algorithms, each satisfying 2-phase discussion time, and either maximal concurrency or fairness. The algorithm implementing fairness requires that every process waits for meetings infinitely often. Moreover, for this algorithm, we introduce and evaluate a new efficiency criterion called the degree of fair concurrency. This criterion shows that even if it does not satisfy maximal concurrency, our snap-stabilizing fair algorithm still allows a high level of concurrency.

关键词： Concurrent computing Algorithm design and analysis Synchronization Transient analysis Context distributed algorithms Communication networks

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Keynote address I: Programming the cloud

Keynote address I: Programming the cloud

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IEEE symposium on High-Performance Computer Architecture

作者： James Larus Microsoft Research Limited

Client + cloud computing is a disruptive, new computing platform, combining diverse client devices - PCs, smartphones, sensors, and single-function and embedded devices - with the unlimited, on-demand computation and data storage offered by cloud computing services such as Amazon's AWS or Microsoft's Windows Azure. As with every advance in computing, programming is a fundamental challenge as client + cloud computing combines many difficult aspects of software development. Systems built for this world are inherently parallel and distributed, run on unreliable hardware, and must be continually available - a challenging programming model for even the most skilled programmers. How then do ordinary programmers develop software for the Cloud? This talk presents one answer, Orleansis a software framework for building client + cloud applications. Orleans encourages use of simple concurrency patterns that are easy to understand and implement correctly, building on an actor-like model with declarative specification of persistence, replication, and consistency and using lightweight transactions to support the development of reliable and scalable client + cloud software.

关键词： Programming Cloud computing Computer languages Buildings Computational modeling Program processors

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Contention Modeling for Multithreaded distributed Shared Memory Machines: The Cray XMT 11

Contention Modeling for Multithreaded Distributed Shared Mem...

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IEEE/ACM international symposium on Cluster computing and the Grid (CCGRID)

作者： Simone Secchi Antonino Tumeo Oreste Villa High Performance Computing Pacific Northwest National Laboratory Richland WA USA

ISBN: (纸本)9780769543956

distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved towards the exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoiding network hot-spots and improving scalability. parallel simulation is a promising approach, which has been extensively used to model the performance of such large-scale machines. One of the most critical factors in coping with the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class. In this paper, we discuss the development of a network contention model for a full-system XMT simulator. We start by measuring the effects of network contention on a 128-processorXMT machine, we then investigate the trade-off that exists between simulation accuracy and speed, comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the actual machine, using three datasets that generate noticeably different contention patterns. Results prove that simulator accuracy in execution time remains within 10% of the real machine. We also show that the slowdown due to contention modeling is limited to 20%, when simulating a small number of processors, and becomes negligible for simulations with higher processor counts.

关键词： Instruction sets Accuracy Computational modeling Computer architecture Synchronization Hardware

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