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Highly Efficient Alltoall and Alltoallv Communication Algorithms for GPU Systems

Highly Efficient Alltoall and Alltoallv Communication Algori...

引用

IEEE international Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Chen-Chun Chen Kawthar Shafie Khorassani Quentin G. Anthony Aamir Shafi Hari Subramoni Dhabaleswar K. Panda Department of Computer Science and Engineering The Ohio State University Columbus Ohio

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

In recent years, High Performance Computing (HPC) and Deep Learning (DL) applications have been modified to run on top supercomputers and utilize the high compute power of GPUs. While GPUs provide high computational power, communication of data between GPUs and across a network continues to be a bottleneck. In particular, with the increasing amount of FFT compute and sparse matrix transpose operations in these applications, Alltoall MPI collective operations are heavily used. Alltoall communication is considered the heaviest communication pattern compared to other MPI collective calls. Few techniques and algorithms effectively help in optimizing Alltoall communication, much less improving the performance on a dense GPU cluster while exploiting the features of modern inter-connects and topologies. Despite the introduction of Inter-Process Communication (IPC) in CUDA 4.1 by NVIDIA, state-of-the-art MPI libraries have not utilized these IPC-based mechanisms to design novel Alltoall algorithms that exploit the capabilities of modern GPUs. In this paper, we propose hybrid IPC-advanced designs for Alltoall and Alltoallv communication on novel GPU systems. By utilizing zero-copy load-store IPC mechanisms for multi-GPU communication within a node, we are able to overlap the intra-node and inter-node communication, yielding improved performance on GPU systems. We evaluate the benefits of our designs at the benchmark and application layers on the ThetaGPU system at ALCF and the Lassen system at LLNL. Our designs provide up to 13.5x and 71% improvements on 128 GPUs and 64 GPUs at the benchmark-level over state-of-the-art MPI libraries on ThetaGPU and Lassen respectively. At the application level, our designs have up to 59x performance improvement for an HPC application, heFFTe, and 5.7x performance improvement for a Deep Learning application, DeepSpeed, on 64 GPUs on ThetaGPU and 256 GPUs on Lassen.

关键词： Deep learning High performance computing Graphics processing units Clustering algorithms Benchmark testing Libraries Supercomputers

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Data-Centric distributed Computing on Networks of Mobile Devices 26th

Data-Centric Distributed Computing on Networks of Mobile Dev...

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26th international conference on parallel and distributed Computing (Euro-Par)

作者： Sanches, Pedro Silva, Joao A. Teofilo, Antonio Paulino, Herve Univ NOVA Lisboa Fac Ciencias & Tecnol NOVA Lab Comp Sci & Informat Dept Informat Caparica Portugal Inst Politecn Lisboa ISEL ADEETC Lisbon Portugal

ISBN: (纸本)9783030576752;9783030576745

In the last few years, we have seen a significant increase both in the number and capabilities of mobile devices, as well as in the number of applications that need more and more computing and storage resources. Currently, in order to deal with this growing need for resources, applications make use of cloud services. This raises some problems, namely high latency, considerable use of energy and bandwidth, and the unavailability of connectivity infrastructures. Given this context, for some applications it makes sense to do part, or all, of the computations locally on the mobile devices themselves. In this paper we present OREGANO, a framework for distributed computing on mobile devices, capable of processing batches or streams of data generated on mobile device networks, without requiring centralized services. Contrary to current state-of-the-art, where computations and data are sent to worker mobile devices, OREGANO performs computations where the data is located, significantly reducing the amount of exchanged data.

关键词： Mobile devices distributed computing Edge computing

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A password-authentication scheme based on ciphertext random sampling transmission

A password-authentication scheme based on ciphertext random ...

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IEEE international Symposium on parallel and distributed processing with applications and IEEE international conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Lizhu Yang Yong Qin Xuwen Qin Dongcheng Zhang School of Computer Science and Technology Dongguan University of Technology Dongguan China School of Cyberspace Security Dongguan University of Technology Dongguan China G2 Grade Shenzhen College of International Education Shenzhen China

The traditional identity authentication approach of username and password has the security risk of password leakage in the transmission process. For the security of password transmission in the blockchain education architecture, an asymmetric encryption algorithm is used to encrypt the transmitted password. Then use an improved random sampling algorithm to randomly extract part of the ciphertext and transmit those selected ciphertexts. The authentication credentials are sampled ciphertext and the location index. At the same time, the authentication factor is generated through the Time-Stamp technology, and mutual authentication is realized based on the Response-Challenge protocol. Through security analysis and experimental analysis, the proposed scheme is proved to be secure.

关键词： Protocols Education Authentication Focusing Passwords Ubiquitous computing Blockchains

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Classification Of Human Facial Expressions For Emotion Recognition Using A distributed Computer System 5

Classification Of Human Facial Expressions For Emotion Recog...

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5th international conference on Computer Science and Engineering (UBMK)

作者： Korkmaz, Timucin Erol, Hamza Mersin Univ Grad Sch Nat & Appl Sci Dept Comp Engn Mersin Turkey Mersin Univ Engn Fac Dept Comp Engn Mersin Turkey

ISBN: (纸本)9781728175652

A computer system was developed to classify human facial expressions for emotion recognition using a distributed computer architecture within the scope of big data. Computers with normal standards and features were used in the distributed computer architecture. Necessary system software for the distributed computer architecture was established and mutual communication protocols were provided between the computers and databases in the computer network. Visual C# parallel programming was used as the software language on the distributed computer architecture. In the software prepared, face image files were processed and threads were created. The threads created later were processed in the processors of the computers. The threads were run on the processors in the distributed computer system, and facial expressions were classified for emotion recognition. In the distributed computer architecture: the number of image files, the volume of big data and the load of the threads to be processed arc taken into account;and databases and parallel programming were used and the classification of human face images was performed. Emotion analysis methods and facial expression recognition techniques were used in the classification process. The distributed computer system is in low cost and high processing speed. With the distributed computer system architecture, big data analytics has become convenient and feasible.

关键词： Big data distributed System Emotion analysis Image classification parallel Programing Face expression recognition

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Challenges of Reviews Scraped from Web Services Hosted on Edge Devices

Challenges of Reviews Scraped from Web Services Hosted on Ed...

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Current Development in Engineering and Technology (CCET), IEEE international conference on

作者： Rajdavinder Singh Boparai Rekha Bhatia Department of Computer Science and Engineering Punjabi University Patiala India Department of Applied Management Punjabi University Patiala India

Machine learning, deep learning, artificial intelligence, the internet of things, big data analytics and cloud computing came together to evolve a new age of computing i.e., edge computing, which is an emerging paradigm that helps in resolving the challenges faced by traditional storage and computing techniques and ensuring the future internet of things. To optimize access anywhere at the any-time time anywhere in a fraction of a second, the migration of stored data is being proposed on edge networks virtually or physically and also an enormous amount of data which is produced from IoT devices need to be processed by edge devices virtually and physically to make intelligent decisions faster. The deployment and execution of intelligent applications over heterogeneous resources are complicated by the geographical dispersion of edge devices and their resource constraints. This article is presenting a study of edge computing methodologies and management of storage and processing resources in edge environments; the positives and negatives of adopting data analytics along with distributed intelligence in edge environments; characterization of a distributed learning architecture; future services webservices in edge computing; and the challenges for deployment of web services containing a huge amount of data and for analytical purposes.

关键词： Deep learning Computer aided instruction Data analysis Distance learning distributed databases Computer architecture Service-oriented architecture

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Access control method for air ticket distribution system based on blockchain

Access control method for air ticket distribution system bas...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Lizhe Zhang Tong Wang Zhijun Wu School of Safety Science and Engineering Civil Aviation University of China Tianjin China School of Electronic Information and Automation Civil Aviation University of China Tianjin China

The air ticket distribution system is a platform to integrate the resources of ticket agents around the ticket sales. It is responsible for connecting ticket suppliers and passengers, and mainly undertakes the services of flight inquiries, air ticket reservation and ticket issuance. However, due to the insufficient access control authority and lax internal supervision and other reasons, passengers' privacy information is frequently leaked, which seriously damage the interests of passengers and airlines. Based on the analysis of ticket distribution process, this paper proposes a blockchain-based access control model for ticket distribution system, aiming at protecting passengers' privacy information and property security. The model is based on Hyperledger Fabric 1.0, which uses the SM2 cryptographic algorithm to replace the default algorithm of the ledger. Experimental results show that the access control method based on blockchain can realize distributed access decision and prevent passenger information from being tampered with illegally. Compared with RSA algorithm, SM2 algorithm is used in the test to generate employee transactions, generate PNR transaction and permission query transaction. The total time is decreased by 17.13%, which is more efficient in each single transaction. Therefore, it is feasible and necessary to the reform of the ledger cryptographic algorithm.

关键词： Access control Privacy Analytical models distributed ledger Atmospheric modeling Process control Control systems

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DECENTRALIZED MIN-MAX OPTIMIZATION: FORMULATIONS, ALGORITHMS AND applications IN NETWORK POISONING ATTACK

DECENTRALIZED MIN-MAX OPTIMIZATION: FORMULATIONS, ALGORITHMS...

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IEEE international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Tsaknakis, Ioannis Hong, Mingyi Liu, Sijia Univ Minnesota Twin Cities Dept Elect & Comp Engn Minneapolis MN 55455 USA MIT IBM Watson Lab IBM Res Cambridge MA 02142 USA

ISBN: (纸本)9781509066315

This paper discusses formulations and algorithms which allow a number of agents to collectively solve problems involving both (non-convex) minimization and (concave) maximization operations. These problems have a number of interesting applications in information processing and machine learning, and in particular can be used to model an adversary learning problem called network data poisoning. We develop a number of algorithms to efficiently solve these non-convex min-max optimization problems, by combining techniques such as gradient tracking in the decentralized optimization literature and gradient descent-ascent schemes in the min-max optimization literature. Also, we establish convergence to a first order stationary point under certain conditions. Finally, we perform experiments to demonstrate that the proposed algorithms are effective in the data poisoning attack.

关键词： min-max optimization poisoning attack distributed optimization

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Tight Bound of parallel Request Latency for Erasure-Coded distributed Storage System 20th

Tight Bound of Parallel Request Latency for Erasure-Coded Di...

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20th international conference on Algorithms and Architectures for parallel processing (ICA3PP)

作者： Zou, Xingshun Li, Wei Shandong Univ Jinan Peoples R China

ISBN: (纸本)9783030602451;9783030602444

With big data analysis and cloud storage improving at an astonishing rate in recent years, more and more parallel computing and data analysis techniques are invented and applied to accessing data from a distributed storage system, which has noticeable differences with accessing data from a separate dedicated storage system. The first and the last processes of a data analysis task in a shared filesystem may have a remarkable gap in latency. The latency of parallel file requests from these processes, however, lacks analytical model especially when erasure code is employed as storage strategy. The main contribution of this work is development of a tight bound of parallel file request latency to give a theoretical upper bound of lantency. Additionally, an exact batch file chunk request analytical model in distributed systems adopting erasure code is studied by the technique of two embedded Markov chains, performance measures such as queue length distribution, waiting time distribution, etc. are derived in closed form. Experimental evaluation verifies accuracy of the theoretical upper bound on latency.

关键词： parallel file requests distributed storage system Erasure code Queueing theory Latency Embedded Markov chain

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Blockchain-based distributed Storage System for Task Offloading in Vehicular Edge Computing

Blockchain-based Distributed Storage System for Task Offload...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Yutian Zhang Bing Tang Qing Yang Xiaoyuan Zhang Jincheng Luo Hunan Key Laboratory for Service Computing and Novel Software Technology School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China School of Information and Communication Engineering Guangzhou Maritime University Guangzhou China

With the deepening requirements of development for the Internet of Vehicles technology, intelligent vehicles need to complete the complex task in a fast response time to meet the needs, which brings great challenges to reliable vehicle service provision. In order to solve this problem, we propose a task offloading scheme into the Internet of Vehicles, which can reduce the execution time of tasks. In this paper, we introduce a location-aware distributed storage system called LDSS to support task offloading. Data can be written, stored, computed and read out through different mobile edge servers. Firstly, the identity of the vehicle is stored on the blockchain, and then the vehicle needs to offload the data to the nearest mobile edge server. Then, the storage node and computing node are selected based on the time optimization strategy. Finally, by predicting the location of the vehicle, the mobile edge server nearest to the predicted vehicle location is selected as the access node for result downloading. After validating the identity of vehicle based on blockchain technology, the output result is returned to the vehicle. The experiments show that our proposed task offloading scheme based on blockchain can effectively achieve the effect of low latency and faster task response, as well as ensure data security.

关键词： Blockchains Servers Reliability Time factors Task analysis Low latency communication Optimization

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Optimizing Complex OpenCL Code for FPGA: A Case Study on Finite Automata Traversal 26

Optimizing Complex OpenCL Code for FPGA: A Case Study on Fin...

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26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Nourian, Marziyeh Zarch, Mostafa Eghbali Becchi, Michela North Carolina State Univ Raleigh NC 27695 USA

ISBN: (纸本)9781728190747

While FPGAs have been traditionally considered hard to program, recently there have been efforts aimed to allow the use of high-level programming models and libraries intended for multi-core CPUs and GPUs to program FPGAs. For example, both Intel and Xilinx are now providing toolchains to deploy OpenCL code onto FPGA. However, because the nature of the parallelism offered by GPU and FPGA devices is fundamentally different, OpenCL code optimized for GPU can prove very inefficient on FPGA, in terms of both performance and hardware resource utilization. This paper explores this problem on finite automata traversal. In particular, we consider an OpenCL NFA traversal kernel optimized for GPU but exhibiting FPGA-friendly characteristics, namely: limited memory requirements, lack of synchronization, and SIMD execution. We explore a set of structural code changes, custom and best-practice optimizations to retarget this code to FPGA. We showcase the effect of these optimiz ations on an Intel Stratix V FPGA board using various NFA topologies from different application domains. Our evaluation shows that, while the resource requirements of the original code exceed the capacity of the FPGA in use, our optimizations lead to significant resource savings and allow the transformed code to fit the FPGA for all considered NFA topologies. In addition, our optimizations lead to speedups up to 4x over an already optimized code-variant aimed to fit the NFA traversal kernel on FPGA. Some of the proposed optimizations can be generalized for other applications and introduced in OpenCL-to-FPGA compiler.

关键词： OpenCL FPGA high-level synthesis automata processing NFA performance optimization

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