Using Physical Compilation to Implement a System on Chip Platform

The goal of this thesis was to setup a complete design flow involving physical synthesis. The design chosen for this purpose was a system-on-chip (SoC) platform developed at the University of Tennessee. It involves a Leon Processor with a minimal cache configuration, an AMBA on-chip bus and an Advanced Encryption Standard module which performs decryption. As transistor size has entered the deep submicron level, iterations involved in the design cycle have increased due to the domination of interconnect delays over cell delays. Traditionally, interconnect delay has been estimated through the use of wire-load models. However, since there is no physical placement information, the delay estimation may be ineffective and result in increased iterations. Hence, placement-based synthesis has recently been introduced to provide better interconnect delay estimation. The tool used in this thesis to implement the system-on-chip design using physical synthesis is Synopsys Physical Compiler. The flow has been setup through the use of the Galaxy Reference Flow scripts obtained from Synopsys. As part of the thesis, an analysis of the differences between a physically synthesized design and a logically synthesized one in terms of area and delay is presented

Toward guiding simulation experiments

To face the variety of simulation experiment methods, tools are needed that allow their seamless integration, guide the user through the steps of an experiment, and support him in selecting the most suitable method for the task at hand. This work presents techniques for facing such challenges. To guide users through the experiment process, six typical tasks have been identified for structuring the experiment workflow. The M&S framework JAMES II and its plug-in system is exploited to integrate various methods. Finally, an approach for automatic selection and use of such methods is realized

A Survey on Compiler Autotuning using Machine Learning

Since the mid-1990s, researchers have been trying to use machine-learning based approaches to solve a number of different compiler optimization problems. These techniques primarily enhance the quality of the obtained results and, more importantly, make it feasible to tackle two main compiler optimization problems: optimization selection (choosing which optimizations to apply) and phase-ordering (choosing the order of applying optimizations). The compiler optimization space continues to grow due to the advancement of applications, increasing number of compiler optimizations, and new target architectures. Generic optimization passes in compilers cannot fully leverage newly introduced optimizations and, therefore, cannot keep up with the pace of increasing options. This survey summarizes and classifies the recent advances in using machine learning for the compiler optimization field, particularly on the two major problems of (1) selecting the best optimizations and (2) the phase-ordering of optimizations. The survey highlights the approaches taken so far, the obtained results, the fine-grain classification among different approaches and finally, the influential papers of the field.Comment: version 5.0 (updated on September 2018)- Preprint Version For our Accepted Journal @ ACM CSUR 2018 (42 pages) - This survey will be updated quarterly here (Send me your new published papers to be added in the subsequent version) History: Received November 2016; Revised August 2017; Revised February 2018; Accepted March 2018

Construction of online catalog topologies using decision trees

Organization of a Web site is important to help users get the most out of the site. A good Web site should help visitors find the information they want easily. Visitors typically find information by searching for selected terms of interest or by following links from one Web page to another. The first approach is more useful if the visitor knows exactly what he is seeking, while the second approach is useful when the visitor has less of a preconceived notion about what he wants. The organization of a Web site is especially important in the latter case. Traditionally, Web site organization is done by hand. In this paper, we introduce the problem of automatic Web site construction and propose a solution for solving a major step of the problem based on decision tree algorithms. The solution is found to be useful in automatic construction of product catalogs.published_or_final_versio