We show through empirical results obtained by running, on a single processor machine, a simple matrix multiplication program written in OpenMP C that the drop in performance compared with the single threaded ve
We show that a multithreaded cache oblivious matrix multiplication incurs \\(O(n^{3}/\\sqrt{ Z}+(Pn)^{1/3}n^{2})\\) cache misses when executed by the Cilk scheduler on a machine with P processors, each with a cache of size Z , with high probability. This bound is tighter than...
Better yet, follow Simple Rule 4 and use a concurrent library function that performs the matrix-matrix multiplication. Summary I’ve given you eight simple rules that you should keep in mind when designing the threading that will transform a serial application into a concurrent version. By ...
The prediction of the structure of large RNAs remains a particular challenge in bioinformatics, due to the computational complexity and low levels of accuracy of state-of-the-art algorithms. The pfold model couples a stochastic context-free grammar to phylogenetic analysis for a high accuracy in ...
f/k/a Dell Computer and Intel Corporation; C.A. No. 2-04CV-120; In the United States District Court of the Eastern Distrcit of Texas, Marshall Division filed Mar. 26, 2004. Amended Complaint for Patent Infringement, MicroUnity Systems Engineering, Inc. v. Dell, Inc. f/k/a/ Dell ...
Matrix multiplication is an essential building block of many linear algebra operations and applications. This paper presents parallel algorithms with shared A or B matrix in the memory for the specialdoi:10.1007/978-3-642-33065-0_18Jie Liu
Such algorithms can benefit from combining parallel SpMV and SpMTV into a single operation we call joint direct and transposed sparse matrix﹙ector multiplication (SpMMTV). In this article, we present a parallel SpMMTV algorithm for shared﹎emory CPUs. The algorithm uses a sparse matrix format ...
Sparse matrix-vector multiplication Multithreaded executionOpenMP Joint direct and transposed multiplicationScalabilityOne of the most common operations executed on modern high-performance computing systems is multiplication of a sparse matrix by a dense vector within a shared-memory computational node. ...
Sparse matrix assemblyIn earlier work we have introduced the "Recursive Sparse Blocks" (RSB) sparse matrix storage scheme oriented towards cache efficient matrix–vector multiplication (SpMV) and triangular solution (SpSV) on cache based shared memory parallel computers. Both the transposed (SpMV_T)...
Sparse matrix-matrix multiplication is a critical kernel for several scientific computing applications, especially the setup phase of algebraic multigrid. The MPI+X programming model, which is growing in popularity, requires that such kernels be implemented in a way that exploits on-node parallelism. ...