Memory requirements of a CMM using a sparse matrix
Parallelizing the Sparse Matrix Transposition: Reducing the Programmer Effort Using Transactional Memory
... complex memory access patterns require a good knowledge of the problem from the programmer and great efforts to develop efficient parallel ...transactional memory might help in obtaining parallel codes with ...
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A Novel Processing-In-Memory Architecture for Dense and Sparse Matrix Multiplications
... and memory gap, unique and novel archit- ecture solutions are ...the memory. In this work, a novel Processing-in-Memory architecture is proposed which uses simple, reconfigurable logic to perform ...
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Parallel sparse matrix vector multiplication techniques for shared memory architectures
... Also, locks and other sychronization primitives used by handcoded schedulers are defined at a relatively high level (also called as application-level), which incurs more overhead than sometimes needed (as they are ...
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Performance Analysis of Sparse Matrix Representation in Hierarchical Temporal Memory for Sequence Modeling
... solutions using image recognition by convolutional neural networks, building general solutions in game environments using reinforcement learning and researching unconventional methods like Hierarchical ...
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Optimizing Sparse Matrix-Matrix Multiplication for the GPU
... operation using parallel primitives forces many data movement operations in global memory between ...global memory between operations ignores more efficient use of registers and shared memory ...
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Assessing a Sparse Distributed Memory Using Different Encoding Methods
... This sorting can be accomplished by trying different per- mutations of the numbers and computing the matrix of hamming distances. For 3-bit numbers, there are 8 dif- ferent numbers and 8! = 40, 320 permutations. ...
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A Rule Chaining Architecture Using a Correlation Matrix Memory
... 8 A Rule Chaining Architecture Using a Correlation Matrix Memory The graphs in Fig. 3 are contour plots showing the recall error rates for the ARCA architecture for a given depth of search tree and ...
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Sparse matrix-vector multiplication on GPGPUs
... all sparse matrix storage formats are devised around means of re- building this map using auxiliary index information: a pair of dimensions does not suffice any ...of sparse matrix ...
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Dictionary selection for Compressed Sensing of EEG signals using sparse binary matrix and spatiotemporal sparse Bayesian learning
... sensing matrix also needs to be considered that can affect the quality of reconstructed ...sensing matrix is required for accurate reconstruction of the EEG signal with minimal ...sensing matrix ...
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Partitioning Models for Scaling Parallel Sparse Matrix-Matrix Multiplication
... of sparse matrix-matrix multiplication (SpGEMM) on distributed memory ...through using the communication hypergraph models, the parallel SpGEMM time can be further improved up to ...
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Seismic sparse-spike deconvolution via Toeplitz-sparse matrix factorization
... computer memory, large seismic data sets were divided into blocks, and the aver- age of the source wavelets deconvolved from these blocks via TSMF-based SSD was used as the final estimation of the source wavelet ...
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Sparse Matrices and Summa Matrix Multiplication Algorithm in STAPL Matrix Framework
... as sparse matrices. The goal is to find representations of sparse matrices in today’s computers such that zero elements are disregarded, not stored, and com- putation can be orchestrated using ...
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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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Enhancement of digital grayscale image watermarking using sparse matrix
... matriks sparse untuk keberkesanan imej tera air menggunakan digital wavelet tranform dan inverse wavelet tranform yang diubahsuai untuk mencari lokasi terbaik untuk meletakkan imej tera air dan tahap imej yang ...
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Enhancement of digital grayscale image watermarking using sparse matrix
... matriks sparse untuk keberkesanan imej tera air menggunakan digital wavelet tranform dan inverse wavelet tranform yang diubahsuai untuk mencari lokasi terbaik untuk meletakkan imej tera air dan tahap imej yang ...
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Convex Sparse Matrix Factorizations
... 6 Conclusion In this paper, we have investigated the possibility of convexifying the sparse dictionary learn- ing problem. We have reached both positive and negative conclusions: indeed, it is possible to ...
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Experiments on Sparse Matrix Partitioning
... The total number of received-sent messages by all processors is shown in Figure 7. For any processor, the number of received-sent messages amount to how many times it exchanges data with other processors. The maximum ...
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RcppArmadillo: Sparse Matrix Support
... RcppArmadillo sparse matrix users based on integration of the documentation of library Matrix (Bates and Maechler, 2018) and Armadillo (Sanderson, 2010; Sanderson and Curtin, ...of sparse ...
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Using the Software CMM in Small Organizations
... § “The right schedule is one that is utterly impossible, just not obviously impossible.” DeMarco goes on to observe that our industry is over-goaded, and the only real (perceived) option is to pay for speed by reducing ...
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The sparse matrix vector product on GPUs
... The key of the success of GPUs in high performance computing comes from the outstanding speedup factors in comparison with standard computers or even clusters of workstations. In order to estimate the net gain provided ...
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