The WSP: a modular architecture for high performance signal processing (for radar)

2003 ◽  
Author(s):  
J.R. Jackson ◽  
S.S. Sinor
Keyword(s):  
Signal Processing ◽  
High Performance ◽  
Modular Architecture

Matlab and Parallel Computing

2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Control Systems ◽  
High Performance ◽  
Parallel Applications ◽  
Process Simulations ◽  
Key Features ◽  
Financial Process

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.

scholarly journals DSPSR: Digital Signal Processing Software for Pulsar Astronomy

2011 ◽  
Vol 28 (1) ◽  
pp. 1-14 ◽  
Author(s):  
W. van Straten ◽  
M. Bailes
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Graphics Processing Units ◽  
High Performance ◽  
Digital Signal ◽  
General Purpose ◽  
Design Decisions ◽  
Extensive Range ◽  
Processing Software ◽  
Graphics Processing

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.

A High-Performance Signal Processing System for Monopulse Tracking Radar

2011 ◽  
Vol 383-390 ◽  
pp. 471-475
Author(s):  
Yong Bin Hong ◽  
Cheng Fa Xu ◽  
Mei Guo Gao ◽  
Li Zhi Zhao
Keyword(s):  
Signal Processing ◽  
High Performance ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Processing System ◽  
Digital Signal ◽  
Radar Signal ◽  
Signal Processing System ◽  
Parallel Pipelined ◽  
Tracking Radar

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.

scholarly journals VLSI ARCHITECTURE OF PARALLEL MULTIPLIER– ACCUMULATOR BASED ON RADIX-2 MODIFIED BOOTH ALGORITHM

2012 ◽  
pp. 40-46
Author(s):  
Mr.M.V. Sathish ◽  
Mrs. Sailaja
Keyword(s):  
Signal Processing ◽  
High Speed ◽  
High Performance ◽  
Vlsi Architecture ◽  
Clock Frequency ◽  
Parallel Multiplier ◽  
Hybrid Type ◽  
Standard Design ◽  
Overall Performance ◽  
And Performance

A new architecture of multiplier-andaccumulator (MAC) for high-speed arithmetic. By combining multiplication with accumulation and devising a hybrid type of carry save adder (CSA), the performance was improved. Since the accumulator that has the largest delay in MAC was merged into CSA, the overall performance was elevated. The proposing method CSA tree uses 1’s-complement-based radix-2 modified Booth’s algorithm (MBA) and has the modified array for the sign extension in order to increase the bit density of the operands. The proposed MAC showed the superior properties to the standard design in many ways and performance twice as much as the previous research in the similar clock frequency. We expect that the proposed MAC can be adapted to various fields requiring high performance such as the signal processing areas.

Parallel Programming and Its Architectures Based on Data Access Separated Algorithm Kernels

2012 ◽  
pp. 278-296
Author(s):  
Dake Liu ◽  
Joar Sohl ◽  
Jian Wang
Keyword(s):  
Signal Processing ◽  
Parallel Programming ◽  
High Performance ◽  
Data Access ◽  
Time Signal ◽  
Hardware System ◽  
Memory Subsystem ◽  
Computing Performance ◽  
Processing Platform ◽  
Parallel Signal Processing

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.

scholarly journals Service for parallel applications based on JINR cloud and HybriLIT resources

2019 ◽  
Vol 214 ◽  
pp. 07012 ◽  
Author(s):  
Nikita Balashov ◽  
Maxim Bashashin ◽  
Pavel Goncharov ◽  
Ruslan Kuchumov ◽  
Nikolay Kutovskiy ◽  
...  
Keyword(s):  
High Performance ◽  
Cloud Service ◽  
Parallel Applications ◽  
Cloud Infrastructure ◽  
Modular Architecture ◽  
Practical Applications ◽  
Speed Up ◽  
Scientific Results ◽  
Computational Resources ◽  
Performance Computing

Cloud computing has become a routine tool for scientists in many fields. The JINR cloud infrastructure provides JINR users with computational resources to perform various scientific calculations. In order to speed up achievements of scientific results the JINR cloud service for parallel applications has been developed. It consists of several components and implements a flexible and modular architecture which allows to utilize both more applications and various types of resources as computational backends. An example of using the Cloud&HybriLIT resources in scientific computing is the study of superconducting processes in the stacked long Josephson junctions (LJJ). The LJJ systems have undergone intensive research because of the perspective of practical applications in nano-electronics and quantum computing. In this contribution we generalize the experience in application of the Cloud&HybriLIT resources for high performance computing of physical characteristics in the LJJ system.

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