Wangdong Yang
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View article: cuFastTucker: A Novel Sparse FastTucker Decomposition For HHLST on Multi-GPUs
cuFastTucker: A Novel Sparse FastTucker Decomposition For HHLST on Multi-GPUs Open
High-order, high-dimension, and large-scale sparse tensors (HHLST) have found their origin in various real industrial applications, such as social networks, recommender systems, bioinformatics, and traffic information. To handle these comp…
View article: cuFastTuckerPlus: A Stochastic Parallel Sparse FastTucker Decomposition Using GPU Tensor Cores
cuFastTuckerPlus: A Stochastic Parallel Sparse FastTucker Decomposition Using GPU Tensor Cores Open
Sparse tensors are prevalent in real-world applications, often characterized by their large-scale, high-order, and high-dimensional nature. Directly handling raw tensors is impractical due to the significant memory and computational overhe…
View article: PaSTG: A Parallel Spatio-Temporal GCN Framework for Traffic Forecasting in Smart City
PaSTG: A Parallel Spatio-Temporal GCN Framework for Traffic Forecasting in Smart City Open
Predicting future traffic conditions from urban sensor data is crucial for smart city applications. Recent traffic forecasting methods are derived from Spatio-Temporal Graph Convolution Networks (STGCNs). Despite their remarkable achieveme…
View article: cuFasterTucker: A Stochastic Optimization Strategy for Parallel Sparse FastTucker Decomposition on GPU Platform
cuFasterTucker: A Stochastic Optimization Strategy for Parallel Sparse FastTucker Decomposition on GPU Platform Open
The amount of scientific data is currently growing at an unprecedented pace, with tensors being a common form of data that display high-order, high-dimensional, and sparse features. While tensor-based analysis methods are effective, the va…
View article: HPS Cholesky: Hierarchical Parallelized Supernodal Cholesky with Adaptive Parameters
HPS Cholesky: Hierarchical Parallelized Supernodal Cholesky with Adaptive Parameters Open
Sparse supernodal Cholesky on multi-NUMAs is challenging due to the supernode relaxation and load balancing. In this work, we propose a novel approach to improve the performance of sparse Cholesky by combining deep learning with a relaxati…
View article: Guest Editorial Special Issue on Smart IoT System: Opportunities by Linking Cloud, Edge, and AI
Guest Editorial Special Issue on Smart IoT System: Opportunities by Linking Cloud, Edge, and AI Open
Recently, the Internet of Things (IoT) technologies have made their entrances into many fields, such as smart city, healthcare, intelligent transportation, forest protection, and environmental monitoring.
View article: An Efficient Methodology for License Plate Localization and Recognition with Low Quality Images
An Efficient Methodology for License Plate Localization and Recognition with Low Quality Images Open
It is challenging to find an effective license plate detection and recognition method due to the different conditions during the image acquisition phase. This paper aims to develop a new accurate and efficient method based on color differe…
View article: Improved Algorithm Based on The Deep Integration of Googlenet and Residual Neural Network
Improved Algorithm Based on The Deep Integration of Googlenet and Residual Neural Network Open
In this paper, we propose a new improved algorithm based on the deep integration of GoogleNet and Residual neural network and we call it GRSN. The new improved algorithm has the new advantages of multi-size and small convolution kernel in …
View article: The impact of data flow computing thinking on the development of computer architecture
The impact of data flow computing thinking on the development of computer architecture Open
Throughout the entire history of computer architecture, the von Neumann model has been the most mainstream model for computer systems architecture.Data flow computer systems are undoubtedly the most well-studied type of non-von Neumann com…