Engineering topics

Gloster, Clay S.

Publications and source records attributed to Gloster, Clay S..

2 records

NASA NTRS2000

Floating-Point Modules Targeted for Use with RC Compilation Tools

Reconfigurable Computing (RC) has emerged as a viable computing solution for computationally intensive applications. Several applications have been mapped to RC system and in most cases, they provided the smallest published execution time. Although RC systems offer significant performance advantages over general-purpose processors, they require more application development time than general-purpose processors. This increased development time of RC systems provides the motivation to develop an optimized module library with an assembly language instruction format interface for use with future RC system that will reduce development time significantly. In this paper, we present area/performance metrics for several different types of floating point (FP) modules that can be utilized to develop complex FP applications. These modules are highly pipelined and optimized for both speed and area. Using these modules, and example application, FP matrix multiplication, is also presented. Our results and experiences show, that with these modules, 8-10X speedup over general-purpose processors can be achieved.

Sahin, Ibrahin↗

NASA NTRS1999

Implementation of Multispectral Image Classification on a Remote Adaptive Computer

As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).

Figueiredo, Marco A.↗