Results for matrix-vector multiplication DFGs
Sparse matrix-vector multiplication on GPGPUs
... sparse matrix in decreasing order of the number of nonzero elements; then, the rows are separated into blocks and each block is stored in the ELLPACK ...predict matrix-dependent tuning parameters, such as ...
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Improving Parallel Sparse Matrix-vector Multiplication
... 4.3 Colouring algorithms Azad and Pothen introduces colouring of the columns to avoid write conflicts for SMvM with CCS-representation. However, the efficiency of CCS-col is dependent on which colouring algorithm it ...
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Sparse matrix-vector multiplication on network-on-chip
... by the system matrix A which is usually large and sparse (Elkurdi et al., 2008). Iterative solvers, mainly the Conjugate Gradient (CG) method, are almost dominated by SMVM op- erations. The CG method is the ...
6
Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication
... FErari does not have an equivalent to the inner-product vertex and edges. This represents a difference in scope for the two respective optimization prob- lems. The FErari optimization problem includes binary ...
141
Optimizing Symmetric Dense Matrix-Vector Multiplication on GPUs
... This SYMV kernel was included in the release of MAGMA 0.2. Although the algorithm described above yields better performance compared to CUBLAS on a GTX 280, the ob- served performance is far from the theoretical peak ...
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Optimization by runtime specialization for sparse matrix-vector multiplication
... which there is sparse-matrix algebra library as well. Program specialization is used to address a realistic problem, Gaussian Elimination [32], where a highly configurable generator is written that is able to ...
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Distributed Matrix-Vector Multiplication with Sparsity and Privacy Guarantees
... Computing matrix-vector multipli- cation for sparse matrices is known to be ...input matrix and in which perfect privacy must be satisfied; in the partly trusted cluster, only up to z workers may ...
Streaming reduction circuit for sparse matrix vector multiplication in FPGAs
... Figure 2.6: Reduction circuit (α = 5) A pipeline depth of one is not realistic when dealing with floating point values. Floating point adders are quite complex compared to integer adders. The floating point adder has to ...
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Fast Multiplication of Matrix-Vector by Virtual Grids Technique in AIM
... projection matrix is modified to eliminate the padding and unpadding procedures without any extra ...function vector in the proposed method is also slightly less than the one in the 1D FFT if EFIE is ...
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Sparse matrix vector multiplication on a field programmable gate array
... the vector x may be used in several ...the vector lie often next to each ...the vector x, each PE can copy an element into its own local memory when it needs that ...the vector x must be ...
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Cache-oblivious sparse matrix-vector multiplication by using sparse matrix partitioning methods
... a matrix stored in Matrix Market ...permuted matrix P AQ is then written in triplet format to a binary file, and can be read in by specialized CRS, ICRS, and ZZ-ICRS benchmark or cache simulation ...
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Parallel Multicore CSB Format and Its Sparse Matrix Vector Multiplication
... banded matrix, we can optimize the algorithm more ...thinner matrix, which is costly for more partitions could happen so that more threads will be generated in some ...
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Performance Prediction Based on Statistics of Sparse Matrix Vector Multiplication on GPUs
... the matrix structure completely, so the execu- tion time predicted by their model tends to be inaccurate for general sparse ...sparse matrix storage formats by the new models on the CUDA ...experimental ...
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Matrix-Vector Multiplication in Sub-Quadratic Time (Some Preprocessing Required)
... A preprocessing/multiplication algorithm for matrix-vector multiplication that builds on lookup table techniques. 20.[r] ...
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Hypergraph-partitioning based decomposition for parallel sparse-matrix vector multiplication
... Experimental results car- ried out on a wide range of sparse test matrices arising in different application domains confirmed the validity of the proposed hypergraph ...parallel matrix-vector ...
21
On analysis of partitioning models and metrics in parallel sparse matrix-vector multiplication
... the relative performances of the models do not change with K. However, their difference tend to increase and hence, the model used for partitioning becomes more important as the parallel matrix-vector ...
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An Architecture-aware Technique for Optimizing Sparse Matrix-vector Multiplication on GPUs
... The heuristic starts allocating the first row of S according to the original column index. We use the same allocation policy for those cache requests that do not overlap with previous threads. Intuitively, this is a ...
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Cache locality exploiting methods and models for sparse matrix-vector multiplication
... sparse matrix-vector multiplication (SpMxV) is an important kernel operation widely used in linear ...sparse matrix is multiplied by a dense vec- tor repeatedly in these solvers to solve a ...
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Parallel sparse matrix vector multiplication techniques for shared memory architectures
... count may be less than 240 (which is supported hardware thread count). In this case smaller matrix sizes work better. Additionally, smaller sub-matrix sizes produce better load balance, thus perform faster. ...
115
A Work-Efficient Parallel Sparse Matrix-Sparse Vector Multiplication Algorithm
... sparse matrix-sparse vector multiplication (SpMSpV) where the matrix, the input vector, and the output vector are all ...sparse matrix data structure than doing ...
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