A custom computing framework for orientation and photogrammetry

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 211-223).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.There is great demand today for real-time computer vision systems, with applications including image enhancement, target detection and surveillance, autonomous navigation, and scene reconstruction. These operations generally require extensive computing power; when multiple conventional processors and custom gate arrays are inappropriate, due to either excessive cost or risk, a class of devices known as Field-Programmable Gate Arrays (FPGAs) can be employed. FPGAs per the flexibility of a programmable solution and nearly the performance of a custom gate array. When implementing a custom algorithm in an FPGA, one must be more efficient than with a gate array technology. By tailoring the algorithms, architectures, and precisions, the gate count of an algorithm may be sufficiently reduced to t into an FPGA. The challenge is to perform this customization of the algorithm, while still maintaining the required performance. The techniques required to perform algorithmic optimization for FPGAs are scattered across many fields; what is currently lacking is a framework for utilizing all these well known and developing techniques. The purpose of this thesis is to develop this framework for orientation and photogrammetry systems.by Paul D. Fiore.Ph.D

High-Performance Special-Purpose Computers in Science

The next decade will be an exciting time for computational physicists. After 50 years of being forced to use standardized commercial equipment, it will finally become relatively straightforward to adapt one's computing tools to one's own needs. The breakthrough that opens this new era is the now wide-spread availability of programmable chips that allow virtually every computational scientist to design his or her own special-purpose computer. Towards Real Numerical Laboratories Unlike real laboratories, numerical laboratories have been constructed almost exclusively from commercial products, which gave little flexibility. Starting in the late seventies, after the first microchips became available, there have been some exceptions. However, only the bravest souls dared to design their own equipment (Bakker and Bruin 1988). In those days, speeding up the most compute-intensive few lines of FORTRAN code, in a large-scale simulation project, required building a bulky piece of electronic h..