The proceedings contain 47 papers. The special focus in this conference is on parallelarchitectures, algorithms and programming. The topics include: On a Coexisting Scheme for Multiple Flows in Multi-radio Multi-chan...
The proceedings contain 47 papers. The special focus in this conference is on parallelarchitectures, algorithms and programming. The topics include: On a Coexisting Scheme for Multiple Flows in Multi-radio Multi-channel Wireless Mesh Networks;Non-linear K-Barrier Coverage in Mobile Sensor Network;Interrupt Responsive Spinlock Mechanism Based on MCS for Multi-core RTOS;A Novel Speedup Evaluation for Multicore Architecture Based Topology of On-Chip Memory;Improving the Performance of Collective Communication for the On-Chip Network;A Survey of Multicast Communication in Optical Network-on-Chip (ONoC);Virtual Network Embedding Based on Core and Coritivity of Graph;Non-time-Sharing Full-Duplex SWIPT Relay System with Energy Access Point;Recent Developments in Content Delivery Network: A Survey;Weighted Mean Deviation Similarity Index for Objective Omnidirectional Video Quality Assessment;Tire X-ray Image Defects Detection Based on Adaptive Thresholding Method;Halftone Image Reconstruction Based on SLIC Superpixel Algorithm;Study on the Method of Extracting Diabetes History from Unstructured Chinese Electronic Medical Record;Deep Residual Optimization for Stereoscopic Image Color Correction;Old Man Fall Detection Based on Surveillance Video Object Tracking;Electric Bicycle Violation Automatic Detection in Unconstrained Scenarios;Building a Lightweight Container-Based Experimental Platform for HPC Education;Automatic Generation and Assessment of Student Assignments for parallelprogramming Learning;Heuristic Load Scheduling Algorithm for Stateful Cloud BPM Engine.
The proceedings contain 57 papers. The special focus in this conference is on parallelarchitectures, algorithms, and programming . The topics include: Ford motor side-view recognition system based on wavelet entropy ...
ISBN:
(纸本)9789811064418
The proceedings contain 57 papers. The special focus in this conference is on parallelarchitectures, algorithms, and programming . The topics include: Ford motor side-view recognition system based on wavelet entropy and back propagation neural network and levenberg-marquardt algorithm;intrusion detection based on self-adaptive differential evolution extreme learning machine with gaussian kernel;prediction for passenger flow at the airport based on different models;election based pose estimation of moving objects;a novel topology reconfiguration backtracking algorithm for 2d REmesh networks-on-chip;user behaviour authentication model based on stochastic petri net in cloud environment;performance prediction of spark based on the multiple linear regression analysis;exploration of heuristic-based feature selection on classification problems;anti-similarity group shilling attacks;the study of the seabed side-scan acoustic images recognition using bp neural network;node localization of wireless sensor network based on secondary correction error;optimizations of the whole function vectorization based on SIMD characteristics;a stacked denoising autoencoders based collaborative approach for recommender system;research on adaptive canny algorithm based on dual-domain filtering;a dynamic individual recommendation method based on reinforcement learning;research on the pre-distribution model based on seesaw model;an efficient filtration method based on variable-length seeds for sequence alignment;an optimized fusion method for double-wearable-wireless-band platform on cloud-health application;research on concept drift detection for decision tree algorithm in the stream of big data;review of various strategies for gateway discovery mechanisms for integrating internet-MANET.
The proceedings contain 37 papers. The special focus in this conference is on parallelarchitectures, algorithms and programming. The topics include: Analysing and Forecasting Electricity Demand and Price Using Deep L...
ISBN:
(纸本)9789811600098
The proceedings contain 37 papers. The special focus in this conference is on parallelarchitectures, algorithms and programming. The topics include: Analysing and Forecasting Electricity Demand and Price Using Deep Learning Model During the COVID-19 Pandemic;cross-database Micro Expression Recognition Based on Apex Frame Optical Flow and Multi-head Self-attention;GPS Intelligent Solution of Aerial Image Target in State Grid EIA Survey;Encryption and Decryption in Conic Curves Cryptosystem Over Finite Field GF(2n) Using Tile Self-assembly;optimizing Embedding-Related Quantum Annealing Parameters for Reducing Hardware Bias;a Behavioural Network Traffic Novelty Detection for the Internet of Things Infrastructures;a Fast Algorithm for Image Segmentation Based on Global Cosine Fitting Energy Model;household Garbage Classification: A Transfer Learning Based Method and a Benchmark;lightweight Neural Network Based Garbage Image Classification Using a Deep Mutual Learning;on the Decycling Problem in a Torus;VBSSR: Variable Bitrate Encoded Video Streaming with Super-Resolution on HPC Education Platform;An Investigation on the Performance of Highly Congested Home WiFi Networks During the COVID-19 Pandemic;using Feed-Forward Network for Fast Arbitrary Style Transfer with Contextual Loss;enhancing Underwater Image Using Multi-scale Generative Adversarial Networks;Inferring Prerequisite Relationships Among Learning Resources for HPC Education;research on Bank Knowledge Transaction Coverage Model Based on Innovation Capacity Analysis;deep Deterministic Policy Gradient Based Resource Allocation in Internet of Vehicles;a Pufferfish Privacy Mechanism for the Trajectory Clustering Task;a Novel Attention Model of Deep Learning in Image Classification;FDRA: Fully Distributed Routing Architecture for Private Virtual Network in Public Cloud.
AIAC algorithms (Asynchronous Iterations Asynchronous Communications) are a particular class of parallel iterative algorithms. Their asynchronous nature makes them more efficient than their synchronous counterparts in...
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AIAC algorithms (Asynchronous Iterations Asynchronous Communications) are a particular class of parallel iterative algorithms. Their asynchronous nature makes them more efficient than their synchronous counterparts in numerous cases as has already been shown in previous works. The first goal of this article is to compare several parallelprogramming environments in order to see if there is one of them which is best suited to efficiently implement AIAC algorithms. The main criterion for this comparison consists in the performances achieved in a global context of grid computing for two classical scientific problems. Nevertheless, we also take into account two secondary criteria which are the ease of programming and the ease of deployment. The second goal of this study is to extract from this comparison the important features that a parallelprogramming environment must have in order to be suited for the implementation of AIAC algorithms.
In the Big Data computing, improving performance with memory computing is one of hot spots. In the memory computing, the data deployment directly affects load balance and task efficiency. In the scene of memory comput...
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ISBN:
(纸本)9781467391160
In the Big Data computing, improving performance with memory computing is one of hot spots. In the memory computing, the data deployment directly affects load balance and task efficiency. In the scene of memory computing of electric power data, two unsolved problems are: (1) only memory space, without the CPU frequency and nuclear number, could be considered for load balance and improving performance;(2) there are so many manual operations that it is difficult to complete data deployment automatically. This paper provides an electric power data deployment solution for distributed memory computing to solve the above challenges. In the solution, according to business logic and hardware configuration of cluster nodes, the data deployment strategy can be established. Then, the deployment scheme can be implemented with interface operation. Lastly, cluster nodes load data according to the deployment scheme. The solution has been applied to the Objectification parallel Computing (OPC). The application result shows that OPC can achieve the best performance which can meet the demand of system efficiency and the operation of data deployment is simple.
In this paper, a parallel method for solving generalized eigenvalue problem based on multi-core platform is presented, which can provide parts of the eigenpairs in parallel. Compared with traditional numerical method,...
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ISBN:
(纸本)9780769548982;9781467345668
In this paper, a parallel method for solving generalized eigenvalue problem based on multi-core platform is presented, which can provide parts of the eigenpairs in parallel. Compared with traditional numerical method, the parallel method in this paper using numerical integration, numerical experiments are implemented with a quad-core computer under the programming environment of Matlab parallel toolbox. The problems of computing the frequencies of a plane wing and aircraft pylon are taken as examples, which show the efficiency and applicability of our scheme.
We discuss some performance issues of the tiled Cholesky factorization on non-uniform memory access-time (NUMA) shared memory machines. We show how to optimize thread placement and data placement in order to achieve p...
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ISBN:
(纸本)9780769548982;9781467345668
We discuss some performance issues of the tiled Cholesky factorization on non-uniform memory access-time (NUMA) shared memory machines. We show how to optimize thread placement and data placement in order to achieve performance gain up to 50% compared to state-of-the-art libraries such as Plasma or MKL.
In this study, we will parallelize the D&C algorithm with CUDA. In stead of recursive programming in D&C, the recursive stack is implemented on the host side (CPU) and the merge operation is executes on GPU in...
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ISBN:
(纸本)9780769548982;9781467345668
In this study, we will parallelize the D&C algorithm with CUDA. In stead of recursive programming in D&C, the recursive stack is implemented on the host side (CPU) and the merge operation is executes on GPU in parallel. Since the recursive stack is a fully binary tree in this algorithm, the merge operations on the nodes in each layer of the binary tree can be performed synchronously. In this data-parallel computation, with the careful management of data structure, the data of each node can be arranged in the same block and no need to share data between threads, so the parallelism is not broken.
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