This paper studies the adaptive beamforming algorithm based on the frequency diverse array(FDA)array where the interference is located at the same angle(but different range)with the target.We take the cross subarray-b...This paper studies the adaptive beamforming algorithm based on the frequency diverse array(FDA)array where the interference is located at the same angle(but different range)with the target.We take the cross subarray-based FDA with sinusoidal frequency offset(CSB sin-FDA)as the receiving array instead of the basic FDA.The sampling covariance matrix under insufficient snapshot can be corrected by the automatic diagonal loading method.On the basis of decomposing the mismatched steering vector error into a vertical component and a parallel one,this paper searches the vertical component of the error by the quadratic constraint method.The numerical simulation verifies that the beamformer based on the CSB sin-FDA can effectively hold the mainlobe at the target position when the snapshot is insufficient or the steering vector is mismatched.展开更多
Sparse Matrix Vector Multiplication (SpMV) is one of the most basic problems in scientific and engineering computations. It is the basic operation in many realms, such as solving linear systems or eigenvalue problems....Sparse Matrix Vector Multiplication (SpMV) is one of the most basic problems in scientific and engineering computations. It is the basic operation in many realms, such as solving linear systems or eigenvalue problems. Nowadays, more than 90 percent of the world’s highest performance parallel computers in the top 500 use multicore architecture. So it is important practically to design the efficient methods of computing SpMV on multicore parallel computers. Usually, algorithms based on compressed sparse row (CSR) format suffer from a number of nonzero elements on each row so hardly as to use the multicore structure efficiently. Compressed Sparse Block (CSB) format is an effective storage format which can compute SpMV efficiently in a multicore computer. This paper presents a parallel multicore CSB format and SpMV based on it. We carried out numerical experiments on a parallel multicore computer. The results show that our parallel multicore CSB format and SpMV algorithm can reach high speedup, and they are highly scalable for banded matrices.展开更多
数字城市建设过程中,日益需要一个开放式、易扩展、可重用的核心系统平台。本文给出了满足上述条件的CyberSIG Studio 的特征和系统组成,并重点描述用于无缝集成和管理 CyberSIG Studio 各功能服务器的服务总线 Cy-berSIG Service Bus ...数字城市建设过程中,日益需要一个开放式、易扩展、可重用的核心系统平台。本文给出了满足上述条件的CyberSIG Studio 的特征和系统组成,并重点描述用于无缝集成和管理 CyberSIG Studio 各功能服务器的服务总线 Cy-berSIG Service Bus 的设计。展开更多
基金supported by the National Natural Science Foundation of China(61503408)
文摘This paper studies the adaptive beamforming algorithm based on the frequency diverse array(FDA)array where the interference is located at the same angle(but different range)with the target.We take the cross subarray-based FDA with sinusoidal frequency offset(CSB sin-FDA)as the receiving array instead of the basic FDA.The sampling covariance matrix under insufficient snapshot can be corrected by the automatic diagonal loading method.On the basis of decomposing the mismatched steering vector error into a vertical component and a parallel one,this paper searches the vertical component of the error by the quadratic constraint method.The numerical simulation verifies that the beamformer based on the CSB sin-FDA can effectively hold the mainlobe at the target position when the snapshot is insufficient or the steering vector is mismatched.
文摘Sparse Matrix Vector Multiplication (SpMV) is one of the most basic problems in scientific and engineering computations. It is the basic operation in many realms, such as solving linear systems or eigenvalue problems. Nowadays, more than 90 percent of the world’s highest performance parallel computers in the top 500 use multicore architecture. So it is important practically to design the efficient methods of computing SpMV on multicore parallel computers. Usually, algorithms based on compressed sparse row (CSR) format suffer from a number of nonzero elements on each row so hardly as to use the multicore structure efficiently. Compressed Sparse Block (CSB) format is an effective storage format which can compute SpMV efficiently in a multicore computer. This paper presents a parallel multicore CSB format and SpMV based on it. We carried out numerical experiments on a parallel multicore computer. The results show that our parallel multicore CSB format and SpMV algorithm can reach high speedup, and they are highly scalable for banded matrices.
