Digital Commons Network^™

Accelerating Graphics Rendering On Risc-V Gpus, Joshua Simpson

Master's Theses

Graphics Processing Units (GPUs) are commonly used to accelerate massively parallel workloads across a wide range of applications from machine learning to cryptocurrency mining. The original application for GPUs, however, was to accelerate graphics rendering which remains popular today through video gaming and video rendering. While GPUs began as fixed function hardware with minimal programmability, modern GPUs have adopted a design with many programmable cores and supporting fixed function hardware for rasterization, texture sampling, and render output tasks. This balance enables GPUs to be used for general purpose computing and still remain adept at graphics rendering. Previous work at the …

Optimizing Lempel-Ziv Factorization For The Gpu Architecture, Bryan Ching

Master's Theses

Lossless data compression is used to reduce storage requirements, allowing for the relief of I/O channels and better utilization of bandwidth. The Lempel-Ziv lossless compression algorithms form the basis for many of the most commonly used compression schemes. General purpose computing on graphic processing units (GPGPUs) allows us to take advantage of the massively parallel nature of GPUs for computations other that their original purpose of rendering graphics. Our work targets the use of GPUs for general lossless data compression. Specifically, we developed and ported an algorithm that constructs the Lempel-Ziv factorization directly on the GPU. Our implementation bypasses the …

Paris: A Parallel Rsa-Prime Inspection Tool, Joseph R. White

Master's Theses

Modern-day computer security relies heavily on cryptography as a means to protect the data that we have become increasingly reliant on. As the Internet becomes more ubiquitous, methods of security must be better than ever. Validation tools can be leveraged to help increase our confidence and accountability for methods we employ to secure our systems.

Security validation, however, can be difficult and time-consuming. As our computational ability increases, calculations that were once considered “hard” due to length of computation, can now be done in minutes. We are constantly increasing the size of our keys and attempting to make computations harder …