Crawford PhD - Examiners' reports -- what do they look …
To alleviate this problem, this thesis present Parakeet, a runtime compiler for an array-oriented subset of Python. Parakeet does not replace the Python interpreter, but rather selectively augments it by compiling and executing functions explicitly marked by the programmer. Parakeet uses runtime type specialization to eliminate the performance-defeating dynamicism of untyped Python code. Parakeet's pervasive use of data parallel operators as a means for implementing array operations enables high-level restructuring optimization and compilation to parallel hardware such as multi-core CPUs and graphics processors. We evaluate Parakeet on a collection of numerical benchmarks and demonstrate its dramatic capacity for accelerating array-oriented Python programs.
The study analysed examiners’ reports for 62 PhD theses
The main file is . It is the file to run in whatever LaTeX program you are using. It is used for reports and dissertations in addition to theses. needs various other files however. The first of these is . Never edit this file.
The other files you will edit with your information. For example, your abstract will be in the file . Edit this file to replace the sample abstract with your own.
Theses and Reports | Process Systems Engineering …
First, I examine word embeddings, a general word representation that is produced by training a deep learning model on a large unlabelled dataset. I introduce methods to use word embeddings to obtain new features that generalize well across domains for relation extraction. This is done for both the feature-based method and the kernel-based method of relation extraction.
Thesis Files - Theses and Reports - Google Sites
Barton. Justification of the Modeling Assumptions in the Intermediate Fidelity Models for Portable Power Generation, Technical Report, February 2005 ()
Master's Theses and Project Reports
Barton. Issues in the Development of Global Optimization Algorithms for Bilevel Programs with a Nonconvex Inner Program, Technical Report, February 2005 ()
To locate a thesis written before November 1, ..
We compare multiple synthesis techniques to one another as well as the real data that they seek to replicate. We also introduce learned synthesis techniques that either train models better than the most realistic graphical methods used by standard rendering packages or else approach their fidelity using far less computation. We accomplish this by learning shading of geometry as well as denoising the results of low sample Monte Carlo image synthesis. Our major contributions are (i) a dataset that allows comparison of real and synthetic versions of the same scene, (ii) an augmented data representation that boosts the stability of learning, and (iii) three different partially differentiable rendering techniques where lighting, denoising and shading are learned. Finally we are able to generate datasets that can outperform full global illumination rendering and approach the performance of training on real data.
Graduate Dissertations, Theses, & Reports
Many tasks in design, verification, and testing of hardware and computer systems can be reduced to checking satisfiability of logical formulas. Certain fragments of first-order logic that model the semantics of prevalent data types, and hardware and software constructs, such as integers, bit-vectors, and arrays are thus of most interest. The appeal of satisfiability modulo theories (SMT) solvers is that they implement decision procedures for efficiently reasoning about formulas in these fragments. Thus, they can often be used off-the-shelf as automated back-end solvers in verification tools. In this thesis, we expand the scope of SMT solvers by developing decision procedures for new theories of interest in reasoning about hardware and software.