Parallel VSIPL++: An Open Standard Software Library for High-Performance Parallel Signal Processing

2005 ◽  
Vol 93 (2) ◽  
pp. 313-330 ◽  
Author(s):  
J. Lebak ◽  
J. Kepner ◽  
H. Hoffmann ◽  
E. Rutledge
2012 ◽  
pp. 278-296
Author(s):  
Dake Liu ◽  
Joar Sohl ◽  
Jian Wang

A novel master-multi-SIMD architecture and its kernel (template) based parallel programming flow is introduced as a parallel signal processing platform. The name of the platform is ePUMA (embedded Parallel DSP processor architecture with Unique Memory Access). The essential technology is to separate data accessing kernels from arithmetic computing kernels so that the run-time cost of data access can be minimized by running it in parallel with algorithm computing. The SIMD memory subsystem architecture based on the proposed flow dramatically improves the total computing performance. The hardware system and programming flow introduced in this article will primarily aim at low-power high-performance embedded parallel computing with low silicon cost for communications and similar real-time signal processing.


Author(s):  
Dake Liu ◽  
Joar Sohl ◽  
Jian Wang

A novel master-multi-SIMD architecture and its kernel (template) based parallel programming flow is introduced as a parallel signal processing platform. The name of the platform is ePUMA (embedded Parallel DSP processor architecture with Unique Memory Access). The essential technology is to separate data accessing kernels from arithmetic computing kernels so that the run-time cost of data access can be minimized by running it in parallel with algorithm computing. The SIMD memory subsystem architecture based on the proposed flow dramatically improves the total computing performance. The hardware system and programming flow introduced in this article will primarily aim at low-power high-performance embedded parallel computing with low silicon cost for communications and similar real-time signal processing.


2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk

Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.


2011 ◽  
Vol 28 (1) ◽  
pp. 1-14 ◽  
Author(s):  
W. van Straten ◽  
M. Bailes

Abstractdspsr is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, dspsr is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.


2011 ◽  
Vol 383-390 ◽  
pp. 471-475
Author(s):  
Yong Bin Hong ◽  
Cheng Fa Xu ◽  
Mei Guo Gao ◽  
Li Zhi Zhao

A radar signal processing system characterizing high instantaneous dynamic range and low system latency is designed based on a specifically developed signal processing platform. Instantaneous dynamic range loss is a critical problem when digital signal processing is performed on fixed-point FPGAs. In this paper, the problem is well resolved by increasing the wordlength according to signal-to-noise ratio (SNR) gain of the algorithms through the data path. The distinctive software structure featuring parallel pipelined processing and “data flow drive” reduces the system latency to one coherent processing interval (CPI), which significantly improves the maximum tracking angular velocity of the monopulse tracking radar. Additionally, some important electronic counter-countermeasures (ECCM) are incorporated into this signal processing system.


Sign in / Sign up

Export Citation Format

Share Document