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检索条件"任意字段=9th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1772 条记录，以下是401-410 订阅

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Security improvement in a modified merkle-tree computation and storage comparison between different cloud providers 19

Security improvement in a modified merkle-tree computation a...

引用

9th Balkan conference in Informatics, BCI 2019

作者： Chenchev, Ivaylo Computer Systems and Technologies Technical University Sofia Bulgaria

ISBN: (纸本)9781450371933

Two of the very well-known hash algorithms from SHA2 (SHA-2) family include SHA-256 and SHA-512. Nowadays, there exists another hash algorithms family - SHA3(SHA-3), which includes SHA3-256 and SHA3-512 algorithms, also known as Keccak algorithms. this paper provides a comparison of the empirical performance calculations with these 4 algorithms with different input volumes of sequential data (where every next slice of information is dependent of previous one) to make it impossible for parallel computation. For the purpose of calculations, 4 totally different environments are used but with exact number of CPUs and approximately similar amount of memory (using only standard instances types) - one personal computer from one side and 3 of the biggest public cloud providers from another - Amazon AWS (***), Microsoft Azure (Standard D2s v3) and Google Cloud (n1-standard-2). the purpose of the research is to compare these environments in terms of additional compute calculations and additional storage space (volumes and prices) for the presented new security improvement of the Merkle-root calculation. the Merkle-root is an integral part of the blockchain and therefore, security improvement of this component is a security improvement of the whole blockchain structure. © 2019 Association for computing Machinery.

关键词： Blockchain

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Comparison of Binary Rain Prediction on HIMAWARI using MPI and CUDA

Comparison of Binary Rain Prediction on HIMAWARI using MPI a...

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Aisya Nafiisyanti Computer Engineering and Applied Science Western Michigan University United States Atmospheric Science and Technology Center-National Institute of Aeronautic and Space Bandung Indonesia

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

Predictions of rainfall events are very important to determine the preventive steps needed to avoid adverse effects with climate change that slowly changing the impact of rain events in Indonesia's area. One way to calculate the prediction of rain events is to use the Lookup Table and Probability of Rain method. To perform that, parallel programming is conducted to help solve large and complex computational problems. In this study, CPU (Central Processing Unit) programming and GPU (Graphical Processing Unit) programming are done to see each performance where computation design and Lookup Table design are implemented on both programming. the results show that CPU programming is more effective for the given case and data rather than GPU programming. Meanwhile, non-ranged Lookup Table design in CPU programming gives more accurate predictions even though it takes more time in computation.

关键词： Rain Graphics processing units Central Processing Unit Programming Testing parallel processing

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IoV distributed architecture for real-time traffic data analytics 9th

IoV distributed architecture for real-time traffic data anal...

引用

9th international conference on Ambient Systems, Networks and technologies (ANT) / 8th international conference on Sustainable Energy Information Technology (SEIT)

作者： Nahri, Mohamed Boulmakoul, Azedine Karim, Lamia Lbath, Ahmed Hassan II Univ Casablanca FSTM LIM IOS BP 146 Mohammadia Morocco Hassan 1st Univ Higher Sch Technol EST Berrechid Beni Mellal Khenifra Morocco Univ Grenoble Alpes LIG MRIM CNRS Grenoble France

In this paper, we present necessary premises for the deployment of the Internet of Vehicles (IoV) integrating Big Data analytics of road network traffic measurements of the city of Mohammedia, Morocco. thus, we introduce an architecture based on three main layers such as IoV, Fog computing and Cloud computing Layer. We specifically put more focus on Fog computing layer in which we develop a framework for a real-time collecting and processing events generated by intelligent vehicles as well as visualizing traffic state on each road section. Furthermore, we consider deployment and test of the proposed framework using events retrieved from a Vanets-type micro simulation. Finally, we present and discuss the first obtained results as well as the advantages and limitations of the proposed architecture. (C) 2018 the Authors. Published by Elsevier B.V.

关键词： IoV Big Data analytics Fog computing Real-time data analytics Traffic control

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A Scalable parallel computing Framework for Large-Scale Astrophysical Fluid Dynamics Numerical Simulation

A Scalable Parallel Computing Framework for Large-Scale Astr...

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Igor Kulikov Igor Chernykh Andrei Tchernykh Supercomputing lab ICMMG SB RAS Novosibirsk Russia Computer Science Department CICESE Research Center Ensenada Mexico

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

the numerical simulation of complex astrophysical problems requires high-performance computing due to the large size of the problems and variety of simulated physical processes. In this paper, we present a new framework for the numerical simulation of astrophysical fluid dynamics. It is based on the mechanisms of combining distributed and parallel computing techniques, advanced vectorization for KNL, and Skylake-SP CPU architectures. Our new HydroBox3D framework uses large 3D meshes to solve problems such as the dynamics of stars or galaxies. In our framework, we use computational nodes with a large amount of memory (RAM or Intel Optane in memory mode) for mesh processing and typical computational nodes for the numerical simulation of astrophysical problems. We use MPI both for send/receive operations between computational nodes and for sending processed data for calculations from data nodes. For optimization of calculations, memory, and CPU usage, we use data vectorization, FMA3, and AVX-512 instructions for Intel Xeon Phi 72XX and Intel Xeon Scalable processors. Benchmark results on different CPU and MIC devices show the effectiveness of the proposed solution.

关键词： Hydrodynamics Mathematical model Poisson equations Carbon Numerical simulation Explosions three-dimensional displays

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parallel Tracking and Reconstruction of States in Heuristic Optimization Systems on GPUs

Parallel Tracking and Reconstruction of States in Heuristic ...

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Marcel Köster Julian Groß Antonio Krüger Saarland Informatics Campus Saarbrucken Saarbrucken Germany

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

Modern heuristic optimization systems leverage the parallel processing power of Graphics Processing Units (GPUs). Many states are maintained and evaluated in parallel to improve runtime by orders of magnitudes in comparison to purely CPUbased approaches. A well known example is the parallel Monte Carlo tree search, which is often used in combination with more advanced machine-learning methods these days. However, all approaches require different optimization states in memory to update or manipulate variables and observe their behavior over time. Large real-world problems often require a large number of states that are typically limited by the amount of available memory. this is particularly challenging in cases in which older states (that are not currently being evaluated) are still required for backtracking purposes. In this paper, we propose a new general high-level approach to track and reconstruct states in the scope of heuristic optimization systems on GPUs. Our method has a considerably lower memory consumption compared to traditional approaches and scales well with the complexity of the optimization problem.

关键词： Optimization Graphics processing units Indexes History Memory management parallel processing Informatics

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Transaction Finality through Ledger Checkpoints

Transaction Finality through Ledger Checkpoints

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international conference on parallel and distributed Systems (ICPADS)

作者： Ratul Antik Das Md. Muhaimin Shah Pahalovi Muhammad Nur Yanhaona Research and Development Kona Software Lab Dhaka Bangladesh

the reversal of transactions due to blockchain ledger reorganization has become a major hindrance for public blockchain technologies9; adoption in real-world business and financial applications. Since a typical rea... 详细信息

ISBN: (纸本)9781728125848

the reversal of transactions due to blockchain ledger reorganization has become a major hindrance for public blockchain technologies' adoption in real-world business and financial applications. Since a typical real-world product, service, or agreement cannot be reversed; associated transactions in the blockchain ledger must also be final. this paper describes and analyzes the transaction finality solution for our proof of work (PoW) mining based blockchain network, the Kona Blockchain Platform. the solution works even if 49% of the network's total mining power is compromised due to malicious attacks. Although designed for our specific platform, the ideas from the solution can be easily adapted to achieve transaction finality in existing public blockchain networks. this paper also discusses how this can be done. To the best of our knowledge, ours is the first solution for deterministic transaction finality for blockchain networks incentivized exclusively by PoW mining.

关键词： Computer networks Peer-to-peer computing distributed information systems Fault tolerance Protocols distributed information systems Peer to peer computing computer network Fault tolerance protocols Checkpoints mining Solutions self-reversal

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Tasking in Accelerators: Performance Evaluation

Tasking in Accelerators: Performance Evaluation

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Leonel Toledo Antonio J. Peña Sandra Catalán Pedro Valero-Lara Barcelona Supercomputing Center (BSC) Barcelona Spain Barcelona Supercomputing Center Barcelona Spain

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

In this work, we analyze the implications and results of implementing dynamic parallelism, concurrent kernels and CUDA Graphs to solve task-oriented problems. As a benchmark we propose three different methods for solving DGEMM operation on tiled-matrices; which might be the most popular benchmark for performance analysis. For the algorithms that we study, we present significant differences in terms of data dependencies, synchronization and granularity. the main contribution of this work is determining which of the previous approaches work better for having multiple task running concurrently in a single GPU, as well as stating the main limitations and benefits of every technique. Using dynamic parallelism and CUDA Streams we were able to achieve up to 30% speedups and for CUDA Graph API up to 25x acceleration outperforming state of the art results.

关键词： Graphics processing units Task analysis parallel processing Kernel Performance evaluation Synchronization Programming

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Concurrent Failure Recovery for Product Matrix Regenerating Code

Concurrent Failure Recovery for Product Matrix Regenerating ...

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Jingyao Zhang Chief Architect of Here Data Technology Shenzhen China

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

Regenerating codes can minimize the network bandwidth required to recover the lost data in case of node failure in distributed storage systems. Product Matrix (PM) code is an important kind of Minimum Storage Regenerating (MSR) code that can maximize the storage efficiency, meanwhile minimizing the repair bandwidth. the original Product Matrix (PM) code only addressed single node failure. In this work, we will propose an algorithm of recovering multiple failed nodes concurrently for PM code. the explicit construction of the Repair Matrix that is applicable to any reasonable combinations of coding parameters will be presented, and the lost data can be obtained by simply multiplying the helper data with the repair matrix, thus is very easy for implementation. Based on the proposed strategy, the needed bandwidth for two major repairing policies: centralized and distributed recovery will be given formally. Moreover, the impact of Repairing Degree (the number of surviving nodes from which the assistant data are downloaded) on the bandwidth cost will be studied, which can help make optimal decisions in practical storage systems.

关键词： Maintenance engineering Bandwidth distributed databases Encoding Symmetric matrices Matrices Redundancy

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GPU parallel Acceleration of Frequency Domain Algorithm for Calculating Radar Target Echoes

GPU Parallel Acceleration of Frequency Domain Algorithm for ...

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Zhao Naixuan Zhang Ge Wang Zijian Kuang Ling University of Electronic Science and Technology of China

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

After the radar detects the target by transmitting signal, the target returns echo signal, which contains the position and velocity of the target. To meet the demand of high-performance echo computing for real-time radar simulation, this paper proposes a frequency domain algorithm for calculating echoes based on GPU. the experiments are conducted to compare the execution time on CPU and GPU. Moreover, we do a lot of tests to contrast the traditional GPU acceleration time domain algorithm and the algorithm proposed in this paper. the results show that, compared with the traditional CPU-based simulator, the GPU-based simulator calculates the echo faster. And with the increase of the number of sampling points, speedup ratio rises. Compared with the existing GPU acceleration time domain algorithm, the GPU-based frequency domain algorithm for calculating echo improves the real-time performance, and with the increase of the number of the targets in the scene, the acceleration ratio promotes obviously. Furthermore, the phase offset due to the time delay is performed in the frequency domain directly, which improve the ranging accuracy.

关键词： Graphics processing units Frequency-domain analysis Radar Time-domain analysis Delay effects Radar antennas Acceleration

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A Hybrid parallel Implementation for the Maximum Flow Problem 26

A Hybrid Parallel Implementation for the Maximum Flow Proble...

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26th Euromicro international conference on parallel, distributed, and Network-Based Processing (PDP)

作者： Stefanes, Marco A. Alvino, Luiz F. Univ Fed Mato Grosso do Sul Comp Coll Campo Grande Brazil Univ Fed Mato Grosso do Sul Campo Grande Brazil

ISBN: (纸本)9781538649756

the maximum flow problem is a classical combinatorial problem with many applications. In this work a hybrid parallel algorithm using both multi-core and many-core technologies for computing the maximum flow in a network is presented. the proposed implementation is applicable in OpenMP/CUDA-enabled computing environment. To improve the performance two strategies were implemented: an adaptive approach where the algorithm alternate GPU/CPU processing according to the number of active nodes and implementations of the global relabeling and gap relabeling heuristics on multi-core approach. When compared against the best sequential implementation, the speedups range from 2.36 to 5.38 in several kinds of graph. Results show that the proposed algorithm is faster than previous parallel implementations on CPU/GPUs for all kinds of tested graphs.

关键词： Maximum flow Push-relabel method Hybrid parallel programming Multi/many-core architectures

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