Sparse Matrix-Vector Multiplication refers to a fundamental computational operation used in scientific and engineering applications that involves multiplying a sparse matrix with a vector. It is a process where the nonzero elements of a sparse matrix are multiplied with the corresponding elements of a ...
Symmetric sparse matrix vector multiplicationUnstructured meshesMulti-core architecturesMemory bounded algorithmsWe present a massively parallel implementation of symmetric sparse matrix鈥搗ector product for modern clusters with scalar multi-core CPUs. Matrices with highly variable structure and density arising ...
Karwacki, "Computational aspects of gpu- accelerated sparse matrix-vector multiplication for solving markov models," Theoretical and Applied Informatics, vol. 23, no. 2, pp. 127-145, 2011.Bylina, B., Bylina, J., Karwacki, M.: Computational aspects of GPU-accelerated sparse matrix-vector ...
We benefit from this robustness in reducing the computational effort and the communication volume when implementing sparse matrix vector multiplication (SMVM) on a Network-on-Chip (NoC).doi:10.1007/978-3-642-55224-3_50Ahmad MansourJürgen Götze...
vector<vector<int>> multiply(vector<vector<int>>& A, vector<vector<int>>&B) {intm1=A.size(), n1=A[0].size(), m2=B.size(), n2=B[0].size(); vector<vector<int>>res;if(m1==0|| n1==0|| m2==0|| n2==0|| n1!=m2)returnres; ...
Computer Science - PerformanceIn this paper, we propose an optimization selection methodology for the ubiquitous sparse matrix-vector multiplication (SpMV) kernel. We propose two models that attempt to identify the major performance bottleneck of the kernel for every instance of the problem and then ...
{public: vector<vector<int>> multiply(vector<vector<int>>& A, vector<vector<int>>&B) { vector<vector<int>>ret;intha =A.size();if(!ha)returnret;intwa = A[0].size();if(!wa)returnret;inthb =wa;intwb = B[0].size();if(!wb)returnret;//Preprocessingunordered_map<int,bool>A...
I have a huge matrix with very few non-zero elements. Some of the columns and rows may also be completely zero. This matrix should be multiplied by a very long vector which has only few non-zero elements. I know that mkl_?cscmv performs the sparse matrix-ve...
Creating a high throughput sparse matrix vector multiplication (SpMxV) implementation depends on a balanced system design. In this paper, we introduce the ... J Sun,GD Peterson,OO Storaasli - IEEE Symposium on Field-programmable Custom Computing Machines 被引量: 89发表: 2007年 FPGA vs. GPU ...
2023. DASP: Specific Dense Matrix Multiply-Accumulate Units Accelerated General Sparse Matrix-Vector Multiplication. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '23). Association for Computing Machinery, New York, NY, USA, Article ...