Publications

Refine Results

(Filters Applied) Clear All

Parallel programming with MatlabMPI

Author:
Published in:
https://arxiv.org/abs/astro-ph/0107406

Summary

MatlabMPI is a Matlab implementation of the Message Passing Interface (MPI) standard and allows any Matlab program to exploit multiple processors. MatlabMPI currently implements the basic six functions that are the core of the MPI point-to-point communications standard. The key technical innovation of MatlabMPI is that it implements the widely used MPI "look and feel" on top of standard Matlab file I/O, resulting in an extremely compact (~100 lines) and "pure" implementation which runs anywhere Matlab runs. The performance has been tested on both shared and distributed memory parallel computers. MatlabMPI can match the bandwidth of C based MPI at large message sizes. A test image filtering application using MatlabMPI achieved a speedup of ~70 on a parallel computer.
READ LESS

Summary

MatlabMPI is a Matlab implementation of the Message Passing Interface (MPI) standard and allows any Matlab program to exploit multiple processors. MatlabMPI currently implements the basic six functions that are the core of the MPI point-to-point communications standard. The key technical innovation of MatlabMPI is that it implements the widely...

READ MORE

High Speed Interconnects and Parallel Software Libraries: Enabling Technologies for NVO

Author:
Published in:
Proc. of the Astronomical Society of the Pacific Conf. Series, Vol. 225, 2001, Virtual Observations of the Future, 13-16 June 2000, pp. 297-301.

Summary

The National Virtual Observatory (NVO) will directly or indirectly touch upon all steps in the process of transforming raw observational data into "meaningful" results. These steps include: (1) Acquisition and storage of raw data. (2) Data reduction (i.e. translating raw data into source detections). (3) Aquisition and storage of detected sources. (4) Multi-sensor/multi-temporal data mining of the products of steps (1), (2) and (3). (Not complete.)
READ LESS

Summary

The National Virtual Observatory (NVO) will directly or indirectly touch upon all steps in the process of transforming raw observational data into "meaningful" results. These steps include: (1) Acquisition and storage of raw data. (2) Data reduction (i.e. translating raw data into source detections). (3) Aquisition and storage of detected...

READ MORE

Exploiting VSIPL and OpenMP for Parallel Image Processing

Author:
Published in:
ADASS 2000, Astronomical Data Analysis Software and Systems X, 12-14 November 2000, pp. 209-212.

Summary

VSIPL and OpenMP are two open standards for portable high performance computing. VSIPL delivers optimized single processor performance while OpenMP provides a low overhead mechanism for executing thread based parallelism on shared memory systems. Image processing is one of the main areas where VSIPL and OpenMP can have a large impact. Currently, a large fraction of image processing applications are written in the Interpreted Data Language (IDL) environment. The aim of this work is to demonstrate that the performance benefits of these new standards can be brought to image processing community in a high level manner that is transparent to users. To this end, this talk presents a fast, FFT based algorithm for performing image convolutions. This algorithm has been implemented within the IDL environment using VSIPL (for optimized single processor performance) with added OpenMP directives (for parallelism). This work demonstrates that good parallel speedups are attainable using standards and can be integrated seamlessly into existing user environments.
READ LESS

Summary

VSIPL and OpenMP are two open standards for portable high performance computing. VSIPL delivers optimized single processor performance while OpenMP provides a low overhead mechanism for executing thread based parallelism on shared memory systems. Image processing is one of the main areas where VSIPL and OpenMP can have a large...

READ MORE

Phased array calibrations using measured element patterns

Published in:
1995 IEEE Int. Symp. Digest, Antennas and Propagation, Vol. 2, 18-23 June 1995, pp. 918-921.

Summary

A technique to compensate for differences in phased array element patterns is presented. Each measured element pattern is approximated by a virtual array whose excitation function is determined by the Woodward-Lawson synthesis technique. By extending the virtual array beyond the physical array dimensions, mutual coupling and edge diffraction effects can be separated. An example is given where calibration by coupling matrix inversion resulted in significantly reduced array pattern sidelobes.
READ LESS

Summary

A technique to compensate for differences in phased array element patterns is presented. Each measured element pattern is approximated by a virtual array whose excitation function is determined by the Woodward-Lawson synthesis technique. By extending the virtual array beyond the physical array dimensions, mutual coupling and edge diffraction effects can...

READ MORE