Several parallel sorting techniques on different architectures have been studied for many years. Due to the need for faster systems in today＇s world, parallelism can be used to accelerate applications. Nowadays, para...Several parallel sorting techniques on different architectures have been studied for many years. Due to the need for faster systems in today＇s world, parallelism can be used to accelerate applications. Nowadays, parallel operations are used to solve computer problems such as sort and search, which result in a reasonable speed. Sorting is one of the most important operations in computing world. The authors always try to find the best in different areas which the premier is speedup. In this paper, the authors issued a sort with O（logn） time complexity on PRAM EREW （Parallel Random Access Machine Exclusive Read Exclusive Write）. The algorithm is designed in a manner that keeps the tradeoff between the number of processor elements in the architecture and execution time. The simulation of the algorithm proves the theoretical analysis of the algorithm. The results of this research can be utilized in developing faster embedded systems. Sorting on Centralized Diamond （SOCD） algorithm is issued on the novel Centralized Diamond architecture which takes the advantages of Single Instruction Multiple Data （SIMD） architecture. This architecture and the sort on it are intuitive and optimal.展开更多
Let A be m by n matrix, M and N be positive definite matrices of order in and n respectively. This paper presents an efficient method for computing (M-N) singular value decomposition((M-N) SVD) of A on a cube connecte...Let A be m by n matrix, M and N be positive definite matrices of order in and n respectively. This paper presents an efficient method for computing (M-N) singular value decomposition((M-N) SVD) of A on a cube connected single instruction stream-multiple data stream(SIMD) parallel computer. This method is based on a one-sided orthogonalization algorithm due to Hestenes. On the cube connected SIMD parallel computer with o(n) processors, the (M -- N) SVD of a matrix A requires a computation time of o(m3 log m/n).展开更多
文摘Several parallel sorting techniques on different architectures have been studied for many years. Due to the need for faster systems in today＇s world, parallelism can be used to accelerate applications. Nowadays, parallel operations are used to solve computer problems such as sort and search, which result in a reasonable speed. Sorting is one of the most important operations in computing world. The authors always try to find the best in different areas which the premier is speedup. In this paper, the authors issued a sort with O（logn） time complexity on PRAM EREW （Parallel Random Access Machine Exclusive Read Exclusive Write）. The algorithm is designed in a manner that keeps the tradeoff between the number of processor elements in the architecture and execution time. The simulation of the algorithm proves the theoretical analysis of the algorithm. The results of this research can be utilized in developing faster embedded systems. Sorting on Centralized Diamond （SOCD） algorithm is issued on the novel Centralized Diamond architecture which takes the advantages of Single Instruction Multiple Data （SIMD） architecture. This architecture and the sort on it are intuitive and optimal.
文摘Let A be m by n matrix, M and N be positive definite matrices of order in and n respectively. This paper presents an efficient method for computing (M-N) singular value decomposition((M-N) SVD) of A on a cube connected single instruction stream-multiple data stream(SIMD) parallel computer. This method is based on a one-sided orthogonalization algorithm due to Hestenes. On the cube connected SIMD parallel computer with o(n) processors, the (M -- N) SVD of a matrix A requires a computation time of o(m3 log m/n).
