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Split array and scalar data cache: A comprehensive study of data cache organization.

Description: Existing cache organization suffers from the inability to distinguish different types of localities, and non-selectively cache all data rather than making any attempt to take special advantage of the locality type. This causes unnecessary movement of data among the levels of the memory hierarchy and increases in miss ratio. In this dissertation I propose a split data cache architecture that will group memory accesses as scalar or array references according to their inherent locality and will subsequently map each group to a dedicated cache partition. In this system, because scalar and array references will no longer negatively affect each other, cache-interference is diminished, delivering better performance. Further improvement is achieved by the introduction of victim cache, prefetching, data flattening and reconfigurability to tune the array and scalar caches for specific application. The most significant contribution of my work is the introduction of novel cache architecture for embedded microprocessor platforms. My proposed cache architecture uses reconfigurability coupled with split data caches to reduce area and power consumed by cache memories while retaining performance gains. My results show excellent reductions in both memory size and memory access times, translating into reduced power consumption. Since there was a huge reduction in miss rates at L-1 caches, further power reduction is achieved by partially or completely shutting down L-2 data or L-2 instruction caches. The saving in cache sizes resulting from these designs can be used for other processor activities including instruction and data prefetching, branch-prediction buffers. The potential benefits of such techniques for embedded applications have been evaluated in my work. I also explore how my cache organization performs for non-numeric data structures. I propose a novel idea called "Data flattening" which is a profile based memory allocation technique to compress sparsely scattered pointer data into regular contiguous memory locations and explore the ...
Date: August 2007
Creator: Naz, Afrin
Partner: UNT Libraries

The VirtualwindoW: A Reconfigurable, Modular, Stereo Vision System

Description: An important need while using unmanned vehicles is the ability for the remote operator or observer to easily and accurately perceive the operating environment. A classic problem in providing a complete representation of the remote work area is sensory overload or excessive complexity in the human-machine interface. In addition, remote operations often benefit from depth perception capability while viewing or manipulating objects. Thus, there is an on going effort within the remote and teleoperated robotic field to develop better human-machine interfaces. The Department of Energy's Idaho National Engineering and Environmental Laboratory (INEEL) has been researching methods to simplify the human-machine interface using atypical operator techniques. Initial telepresence research conducted at the INEEL developed and implemented a concept called the VirtualwindoW. This system minimized the complexity of remote stereo viewing controls and provided the operator the "feel" of viewing the environment, including depth perception, in a natural setting. The VirtualwindoW has shown that the human-machine interface can be simplified while increasing operator performance. This paper deals with the continuing research and development of the VirtualwindoW to provide a reconfigurable, modular system that easily utilizes commercially available off the shelf components. This adaptability is well suited to several aspects of unmanned vehicle applications, most notably environmental perception and vehicle control.
Date: April 1, 1999
Creator: Kinoshita, Robert Arthur; Anderson, Matthew Oley; Mckay, Mark D & Willis, Walter David
Partner: UNT Libraries Government Documents Department