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Next Generation Cloud computing Reliability:Issues and Challenges

Next Generation Cloud Computing Reliability:Issues and Chall...

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The 7th International Symposium on parallel Architectures, Algorithms and Programming, PAAP2015(2015年第七届国际并行体系结构,算法和编程研讨会)

作者： Jemal Abawajy Parallel and Distributed Computing Lab School of Information Technology Deakin University Australia

Introduction Cloud computing is widely recognized for its cost savings,scaling and for accelerating business innovation.

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Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern parallel Systems

Exploring Shared-Memory Optimizations for an Unstructured Me...

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： Dheevatsa Mudigere Srinivas Sridharan Anand Deshpande Jongsoo Park Alexander Heinecke Mikhail Smelyanskiy Bharat Kaul Pradeep Dubey Dinesh Kaushik David Keyes Parallel Computing Lab Intel Corporation Bangalore India Parallel Computing Lab Intel Corporation Santa Clara CA Qatar Foundation Doha Qatar King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (纸本)9781479986507

In this work, we revisit the 1999 Gordon Bell Prize winning PETSc-FUN3D aerodynamics code, extending it with highly-tuned shared-memory parallelization and detailed performance analysis on modern highly parallel architectures. An unstructured-grid implicit flow solver, which forms the backbone of computational aerodynamics, poses particular challenges due to its large irregular working sets, unstructured memory accesses, and variable/limited amount of parallelism. This code, based on a domain decomposition approach, exposes tradeoffs between the number of threads assigned to each MPI-rank sub domain, and the total number of domains. By applying several algorithm- and architecture-aware optimization techniques for unstructured grids, we show a 6.9X speed-up in performance on a single-node Intel® XeonTM1 E5 2690 v2 processor relative to the out-of-the-box compilation. Our scaling studies on TACC Stampede supercomputer show that our optimizations continue to provide performance benefits over baseline implementation as we scale up to 256 nodes.

关键词： Optimization Kernel parallel processing Jacobian matrices Computational fluid dynamics Instruction sets Sparse matrices

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A Congestion Control Scheme Based on Fuzzy Logic in Wireless Body Area Networks

A Congestion Control Scheme Based on Fuzzy Logic in Wireless...

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IEEE International Symposium on Network computing and Applications

作者： Sara Ghanavati Jemal Abawaji Davood Izadi Parallel and Distributed Computing Lab Deakin University Geelong Australia Deakin University Burwood VIC AU

ISBN: (纸本)9781509018505

One of the major challenges in healthcare wireless body area network (WBAN) applications is to control congestion. Unpredictable traffic load, many-to-one communication nature and limited bandwidth occupancy are among major reasons that can cause congestion in such applications. Congestion has negative impacts on the overall network performance such as packet losses, increasing end-to-end delay and wasting energy consumption due to a large number of retransmissions. In life-critical applications, any delay in transmitting vital signals may lead to death of a patient. Therefore, in order to enhance the network quality of service (QoS), developing a solution for congestion estimation and control is imperative. In this paper, we propose a new congestion detection and control protocol for remote monitoring of patients health status using WBANs. The proposed system is able to detect congestion by considering local information such as buffer capacity and node rate. In case of congestion, the proposed system differentiates between vital signals and assigns priorities to them based on their level of importance. As a result, the proposed approach provides a better quality of service for transmitting highly important vital signs.

关键词： Wireless communication Body area networks Medical services Protocols Wireless sensor networks Quality of service Fuzzy logic

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One-Sided Interface for Matrix Operations Using MPI-3 RMA: A Case Study with Elemental

One-Sided Interface for Matrix Operations Using MPI-3 RMA: A...

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International Conference on parallel Processing (ICPP)

作者： Sayan Ghosh Jeff R. Hammond Antonio J. Peña Pavan Balaji Assefaw H. Gebremedhin Barbara Chapman School of Electrical Engineering and Computer Science Washington State University Pullman WA USA Parallel Computing Lab Intel Corp. Portland OR USA Centro Nacional de Supercomputacion Barcelona ES Mathematics and Computer Science Division Argonne National Laboratory Lemont IL USA Institute for Advanced Computational Science Stony Brook University Stony Brook NY USA

A one-sided programming model separates communication from synchronization, and is the driving principle behind partitioned global address space (PGAS) libraries such as Global Arrays (GA) and SHMEM. PGAS models expose a rich set of functionality that a developer needs in order to implement mathematical algorithms that require frequent multidimensional array accesses. However, use of existing PGAS libraries in application codes often requires significant development effort in order to fully exploit these programming models. On the other hand, a vast majority of scientific codes use MPI either directly or indirectly via third-party scientific computation libraries, and need features to support application-specific communication requirements (e.g., asynchronous update of distributed sparse matrices, commonly arising in machine learning workloads). For such codes it is often impractical to completely shift programming models in favor of special one-sided communication middleware. Instead, an elegant and productive solution is to exploit the one-sided functionality already offered by MPI-3 RMA (Remote Memory Access). We designed a general one-sided interface using the MPI-3 passive RMA model for remote matrix operations in the linear algebra library Elemental, we call the interface we designed RMAInterface. Elemental is an open source library for distributed-memory dense and sparse linear algebra and optimization. We employ RMAInterface to construct a Global Arrays-like API and demonstrate its performance scalability and competitivity with that of the existing GA (with ARMCI-MPI) for a quantum chemistry application.

关键词： Libraries Arrays Two dimensional displays Computational modeling Matrices Data models

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Scalable Bayesian optimization using deep neural networks 32

Scalable Bayesian optimization using deep neural networks

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32nd International Conference on Machine Learning, ICML 2015

作者： Snoek, Jasper Ripped, Oren Swersky, Kevin Kiros, Ryan Satish, Nadathur Sundaram, Narayanan Patwary, Md. Mostofa Ali Prabhat Adams, Ryan P. Harvard University School of Engineering and Applied Sciences United States Massachusetts Institute of Technology Department of Mathematics United States University of Toronto Department of Computer Science Canada Intel Labs Parallel Computing Lab Switzerland NERSC Lawrence Berkeley National Laboratory United States

ISBN: (纸本)9781510810587

Bayesian optimization is an effective methodology for the global optimization of functions with expensive evaluations. It relies on querying a distribution over functions defined by a relatively cheap surrogate model. An accurate model for this distribution over functions is critical to the effectiveness of the approach, and is typically fit using Gaussian processes (GPs). However, since GPs scale cubically with the number of observations, it has been challenging to handle objectives whose optimization requires many evaluations, and as such, massively parallelizing the optimization. In this work, we explore the use of neural networks as an alternative to GPs to model distributions over functions. We show that performing adaptive basis function regression with a neural network as the parametric form performs competitively with state-of-the-art GP-based approaches, but scales linearly with the number of data rather than cubically. This allows us to achieve a previously intractable degree of parallelism, which we apply to large scale hyperparameter optimization, rapidly finding competitive models on benchmark object recognition tasks using convolutional networks, and image caption generation using neural language models. © Copyright 2015 by International Machine Learning Society (IMLS). All rights reserved.

关键词： Global optimization

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Design Space Exploration for a Co-designed Accelerator Supporting Homomorphic Encryption

Design Space Exploration for a Co-designed Accelerator Suppo...

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International Conference on Control Systems and Computer Science (CSCS)

作者： Ghada Abozaid Ahmed El-Mahdy Parallel Computing Lab. Egypt-Japan University of Science and Technology (E-JUST) Alexandria Egypt (on-Leave) Faculty of Engineering Alexandria University Egypt

Fully Homomorphic Encryption is currently a sound theoretical approach for cloud security, it is currently not practically used due to the tremendous computation requirements of multiplying very large, million-bit, operands. In this paper, we explore the design space of software/hardware (SW/HW) co-designed accelerator relying on integrating fast software multiplication algorithms with a configurable hardware multiplier. The multiplier is based on a modified serial-parallel multiplier design, in which School-Book is a special case. The paper conducts an analytic performance study, exploring key design space parameters as well as comparing with other design approaches in the literature. Based on an actual FPGA implementation, we estimate a power consumption of 10, Watt, and area-time-power of 20.20 billion transistor-sec-Watt, potentially allowing for promising scalability.

关键词： Hardware Software Software algorithms Algorithm design and analysis parallel processing Space exploration Mathematical model

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Secure object tracking protocol for Networked RFID Systems

Secure object tracking protocol for Networked RFID Systems

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/Distributed computing (SNPD)

作者： Biplob Ray Morshed Howdhury Jemal Abawajy Monika Jesmin Parallel and Distributed Computing Lab School of Information Technology Deakin University Melbourne Australia Lincoln University College Petaling Jaya Selangor Darul Ehsan Malaysia

Networked systems have adapted Radio Frequency identification technology (RFID) to automate their business process. The Networked RFID Systems (NRS) has some unique characteristics which raise new privacy and security concerns for organizations and their NRS systems. The businesses are always having new realization of business needs using NRS. One of the most recent business realization of NRS implementation on large scale distributed systems (such as Internet of Things (IoT), supply chain) is to ensure visibility and traceability of the object throughout the chain. However, this requires assurance of security and privacy to ensure lawful business operation. In this paper, we are proposing a secure tracker protocol that will ensure not only visibility and traceability of the object but also genuineness of the object and its travel path on-site. The proposed protocol is using Physically Unclonable Function (PUF), Diffie-Hellman algorithm and simple cryptographic primitives to protect privacy of the partners, injection of fake objects, non-repudiation, and unclonability. The tag only performs a simple mathematical computation (such as combination, PUF and division) that makes the proposed protocol suitable to passive tags. To verify our security claims, we performed experiment on Security Protocol Description Language (SPDL) model of the proposed protocol using automated claim verification tool Scyther. Our experiment not only verified our claims but also helped us to eliminate possible attacks identified by Scyther.

关键词： Protocols Security Mathematical model Radiofrequency identification Supply chains Privacy

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A Redundancy-Based Protocol for Safety Message Dissemination in Vehicular Ad Hoc Networks

A Redundancy-Based Protocol for Safety Message Dissemination...

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IEEE Conference on Vehicular Technology (VTC)

作者： Imen Achour Tarek Bejaoui Anthony Busson Sami Tabbane Mediatron Lab. SupCom University of Carthage Tunisia Telnet Holding Telnet Innovation Labs. Tunisia Laboratory of Parallel Computing University of Lyon France

ISBN: (纸本)9781479980925

The diversity of applications' types in vehicular ad hoc networks (VANETs) has spawned a large variety of messages that need to be disseminated in a vehicle to vehicle (V2V) communication mode. The most critical messages are those dedicated for safety applications such as accident warning, road hazardous warning, signal violation warning, etc. The dissemination of this kind of messages is a challenging task in VANETs since they should be efficiently transmitted i.e. by achieving high packet delivery within a limited transmission delay and an acceptable overhead. In this work, we propose a robust and an original data dissemination protocol called ``Redundancy-based Protocol (RBP)''. Unlike most of density-based protocols, RBP is beaconless. It takes into account the surrounding vehicles' density during the broadcasting process through a specific metric, named ``Packet Redundancy Ratio'', calculated locally at each vehicular node. On the basis of this metric, each vehicle is able to dynamically define the probability of rebroadcast in order to mitigate the broadcast storm problem. The simulation results show that the proposed protocol outperforms the slotted 1-persistence scheme in terms of packet drop ratio, and network load while still maintaining a low End-to-End delay and high packet reachability. This scheme is suitable either for safety applications or for further kinds of applications by saving the network capacity consumption.

关键词： Vehicles Protocols Redundancy Delays Safety Vehicular ad hoc networks

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Madness: A multiresolution, adaptive numerical environment for scientific simulation

Madness: A multiresolution, adaptive numerical environment f...

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作者： Harrison, Robert J. Beylkin, Gregory Bischoff, Florian A. Calvin, Justus A. Fann, George I. Fosso-Tande, Jacob Galindo, Diego Hammond, Jeff R. Hartman-Baker, Rebecca Hill, Judith C. Jia, Jun Kottmann, Jakob S. Ou, M-J. Yvonne Pei, Junchen Ratcliff, Laura E. Reuter, Matthew G. Richie-Halford, Adam C. Romero, Nichols A. Sekino, Hideo Shelton, William A. Sundahl, Bryan E. Thornton, W. Scott Valeev, Edward F. Vázquez-Mayagoitia, Álvaro Vence, Nicholas Yanai, Takeshi Yokoi, Yukina Stony Brook University Stony BrookNY11794 United States University of Colorado at Boulder BoulderCO80309 United States Institut für Chemie Humboldt-Universität Zu Berlin Unter den Linden 6 Berlin10099 Germany Department of Chemistry Virginia Tech. BlacksburgVA24061 United States Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Chemistry and Biochemistry Florida State University TallahasseeFL32306 United States Parallel Computing Lab Intel Corporation PortlandOR97219 United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA94720 United States LinkedIn Mountain ViewCA94043 United States Department of Mathematical Sciences University of Delaware NewarkDE19716 United States State Key Laboratory of Nuclear Physics and Technology School of Physics Peking University Beijing100871 China Argonne Leadership Computing Facility Argonne National Laboratory ArgonneIL60439 United States Department of Physics University of Washington SeattleWA98195 United States Computer Science and Engineering Toyohashi University of Technology ToyohashiAichi441-8580 Japan Louisiana State University Baton RougeLA70803 United States Department of Physics LaSierra University RiversideCA92505 United States Theoretical and Computational Molecular Science Institute for Molecular Science OkazakiAichi444-8585 Japan

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision that are based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics. © 2016 Society for Industrial and Applied Mathematics.

关键词： Multiresolution analysis

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Towards a matrix-oriented strided interface in OpenSHMEM 14

Towards a matrix-oriented strided interface in OpenSHMEM

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8th International Conference on Partitioned Global Address Space Programming Models, PGAS 2014

作者： Hammond, Jeff R. Extreme Scalability Group Parallel Computing Lab Intel Corporation United States

New communication routines are proposed for OpenSHMEM to allow the efficient implementation of distributed matrix computations. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

ISBN: (纸本)9781450332477

关键词： Matrix algebra

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