It is an important task to improve performance for sparse matrix vector multiplication （SpMV）, and it is a difficult task because of its irregular memory access. Gen- eral purpose GPU （GPGPU） provides high computi...
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It is an important task to improve performance for sparse matrix vector multiplication （SpMV）, and it is a difficult task because of its irregular memory access. Gen- eral purpose GPU （GPGPU） provides high computing abil- ity and substantial bandwidth that cannot be fully exploited by SpMV due to its irregularity. In this paper, we propose two novel methods to optimize the memory bandwidth for SpMV on GPGPU. First, a new storage format is proposed to exploit memory bandwidth of GPU architecture more effi- ciently. The new storage format can ensure that there are as many non-zeros as possible in the format which is suitable to exploit the memory bandwidth of the GPU. Second, we pro- pose a cache blocking method to improve the performance of SpMV on GPU architecture. The sparse matrix is partitioned into sub-blocks that are stored in CSR format. With the block- ing method, the corresponding part of vector x can be reused in the GPU cache, so the time to access the global memory for vector x is reduced heavily. Experiments are carried out on three GPU platforms, GeForce 9800 GX2, GeForce GTX 480, and Tesla K40. Experimental results show that both new methods can efficiently improve the utilization of GPU mem- ory bandwidth and the performance of the GPU.
Compound property assays are an important part of drug development, but incomplete data may occur for a variety of reasons. To deal with these incomplete data and improve the success rate of drug development, research...
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MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of b...
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MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of biological functions such as regulation of innate and adaptive immunity,cell differentiation and development as well as
Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content s...
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As a new computing paradigm, cloud computing is receiving considerable attention in both industry and academia. Task scheduling plays an important role in large-scale distributed systems. However, most previous work o...
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The key issue of Peer Data Management Systems (PDMSs) is how to efficiently organize and manage distributed resources in P2P networks to accurately route queries from the peer initiating the query to appropriate peers...
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A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the ...
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Analysis of transforming matrices between Bezier basis functions and geometrically continuous basis functions is presented It is shown that G 2 transforming matrix has some relationship with G1 transforming matrix. Ba...
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A new distance for image clustering called Generalized Geodesic Distance (GGD) and an appearance-based image clustering approach called Global Geometric Clustering for Image (GGCI) are *** the traditional distance, GG...
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A new distance for image clustering called Generalized Geodesic Distance (GGD) and an appearance-based image clustering approach called Global Geometric Clustering for Image (GGCI) are *** the traditional distance, GGD takes into account the spatial relationships of ***, it is robust to small perturbation of *** based on GGD uses easily measured local metric information to learn the underlying global geometry of images space, then applies the extended nearest neighbor approach to cluster *** from the usual nearest neighbor approach, GGCI considers the density around the nearest points within manifolds embedded in high dimensional image space, which better reflects the intrinsic geometric structure of *** results suggest that the proposed GGCI approach achieves lower error rates in image clustering.
Scene text recognition (STR) is still a hot research topic in computer vision field due to its various applications. Existing works mainly focus on learning a general model with a huge number of synthetic text images ...
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