Sparse Matrix Vector Multiplication (SpMV) is one of the most basic problems in scientific and engineering computations. It is the basic operation in many realms, such as solving linear systems or eigenvalue problems....Sparse Matrix Vector Multiplication (SpMV) is one of the most basic problems in scientific and engineering computations. It is the basic operation in many realms, such as solving linear systems or eigenvalue problems. Nowadays, more than 90 percent of the world’s highest performance parallel computers in the top 500 use multicore architecture. So it is important practically to design the efficient methods of computing SpMV on multicore parallel computers. Usually, algorithms based on compressed sparse row (CSR) format suffer from a number of nonzero elements on each row so hardly as to use the multicore structure efficiently. Compressed Sparse Block (CSB) format is an effective storage format which can compute SpMV efficiently in a multicore computer. This paper presents a parallel multicore CSB format and SpMV based on it. We carried out numerical experiments on a parallel multicore computer. The results show that our parallel multicore CSB format and SpMV algorithm can reach high speedup, and they are highly scalable for banded matrices.展开更多
The cavity formation and propagation process of stress wave from parallel hole cut blasting was simulated with ANSYS/LS-DYNA 3D nonlinear dynamic finite element software. The distribution of element plastic strain, no...The cavity formation and propagation process of stress wave from parallel hole cut blasting was simulated with ANSYS/LS-DYNA 3D nonlinear dynamic finite element software. The distribution of element plastic strain, node velocity, node time-acceleration history and the blasting cartridge volume ratio during the process were analyzed. It was found that the detonation of charged holes would cause the interaction of stress wave with the wall of uncharged holes. Initial rock cracking and displacement to neighboring uncharged holes become the main mechanism of cavity formation in early stage.2008 University of Science and Technology Beijing. All rights reserved.展开更多
基金Supported by National Natural Science Foundation of China(60474035),National Research Foundation for the Doctoral Program of Higher Education of China(20050359004),Natural Science Foundation of Anhui Province(070412035)
文摘Sparse Matrix Vector Multiplication (SpMV) is one of the most basic problems in scientific and engineering computations. It is the basic operation in many realms, such as solving linear systems or eigenvalue problems. Nowadays, more than 90 percent of the world’s highest performance parallel computers in the top 500 use multicore architecture. So it is important practically to design the efficient methods of computing SpMV on multicore parallel computers. Usually, algorithms based on compressed sparse row (CSR) format suffer from a number of nonzero elements on each row so hardly as to use the multicore structure efficiently. Compressed Sparse Block (CSB) format is an effective storage format which can compute SpMV efficiently in a multicore computer. This paper presents a parallel multicore CSB format and SpMV based on it. We carried out numerical experiments on a parallel multicore computer. The results show that our parallel multicore CSB format and SpMV algorithm can reach high speedup, and they are highly scalable for banded matrices.
文摘The cavity formation and propagation process of stress wave from parallel hole cut blasting was simulated with ANSYS/LS-DYNA 3D nonlinear dynamic finite element software. The distribution of element plastic strain, node velocity, node time-acceleration history and the blasting cartridge volume ratio during the process were analyzed. It was found that the detonation of charged holes would cause the interaction of stress wave with the wall of uncharged holes. Initial rock cracking and displacement to neighboring uncharged holes become the main mechanism of cavity formation in early stage.2008 University of Science and Technology Beijing. All rights reserved.
基金Manuscript received March 5, 2010 accepted March 2, 2011 Supported by National Natural Science Foundation of China (61004103), National Research Foundation for the Doctoral Program of Higher Education of China (20100111110005), China Postdoctoral Science Foundation (20090460742), and Natural Science Foundation of Anhui Province of China (090412058, 11040606Q44)