Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
This paper presents a portable, efficient method for accessing memory resident persistent objects in virtual memory in the context of the E programming language. Under the approac...
Code Compression has been shown to be efficient in minimizing the memory requirements for embedded systems as well as in power consumption reduction and performance improvement. I...
Linked data structure (LDS) accesses are critical to the performance of many large scale applications. Techniques have been proposed to prefetch such accesses. Unfortunately, many...
Abstract. Recent results in the Rio project at the University of Michigan show that it is possible to create an area of main memory that is as safe as disk from operating system cr...