Computer and Systems Architecture Commons^™

Hyperchaotic Noise Generation For Adversarial Encryption In Privacy-Preserving Image Classification, Neeraja Beesetti

Master's Theses

Artificial intelligence systems make useful predictions by taking in data and returning a classification, recommendation, or decision. Obtaining that prediction, however, requires sharing the data first. This creates a fundamental privacy challenge in machine learning: users must expose their data to receive a valuable prediction. Machine learning systems increasingly rely on cloud-based image classification for this reason, transmitting images from edge devices to remote servers rather than running large models locally. This creates a conflict between the accuracy a classifier requires and the privacy a data owner wants. Traditional encryption destroys the image structure on which a classifier depends, while …

Developing A Rapid Urban Forest Assessment System For Sustainable City Greenification, Daniel Gonzalez

Master's Theses

This thesis presents the Rapid Urban Forest Assessment (RUFA) system, a web-based platform that integrates urban tree inventories and aerial tree detection to assess forest health across California’s census-designated places. RUFA combines inventoried tree records with coordinates detected from high-resolution multispectral imagery using convolutional neural networks, then computes a composite RUFA Score from four metrics: canopy cover percentage, trees per capita, tree diversity (TD-50), and tree evenness. The thesis addresses two engineering challenges in building the dashboard: querying and aggregating over seven million tree records in real time, and rendering spatial summaries at multiple zoom levels without recomputing cluster assignments …

A Maintainable Extensible And Performant Compiler Toolchain For The Trustguard Architecture, Ethan N. Emery

Master's Theses

TrustGuard is a hardware architecture implementing a CAVO (Containment Architecture with Verified Output) model, which provides security guarantees by bootstrapping trust of a system to a hardware component known as the Sentry. Rather than verifying an entire system, TrustGuard re-executes trusted computation on the Sentry and validates the host system's execution before allowing values to pass to the outside world, thereby containing the effects of erroneous computation. Implementing this architecture in practice without hardware modifications to a host CPU requires a compiler toolchain capable of automatically generating instrumented binaries for both the untrusted host and the trusted Sentry from C …

System Integration And Validation Of The Cal Poly Spacecraft Attitude Dynamics Simulator Mk. Iv, Bricen S. Rigby

Master's Theses

The Cal Poly Spacecraft Attitude Dynamics Simulator (SADS) is an ongoing project that seeks to enable the simulation and validation of sensors, actuators, and control logic related to spacecraft attitude control. The SADS platform rests atop a spher- ical air-bearing device which allows for nearly frictionless rotation in all three axes. The orientation of the platform is controlled by four reaction wheels arranged in a pyramidal configuration. Over the past few years, there have been significant updates to the reaction wheel subsystem, as well as requests for a more capable central com- puter. Therefore, a new system architecture for the …

Integrating Sustainability Into Engineering Education, Riley R. Moller

Master's Theses

Engineering decisions shape lasting technology that affects environmental integrity, public safety, economic stability, and social equity. As global challenges such as climate change, infrastructure vulnerability, and rapid technological advancement intensify, the responsibilities placed on engineers continue to expand. Sustainability provides a framework for addressing these interconnected pressures through systems-based design and long-term thinking. Yet, sustainability education within engineering programs remains unevenly integrated, often positioned as elective or peripheral rather than as a foundational component of professional preparation.

Prior research shows that sustainability is most frequently addressed through stand-alone courses rather than embedded across required curricula, reflecting disciplinary structures that prioritize …

Reproducing And Evaluating Charger Surfing: Robustness Of Smartphone Charging-Line Side-Channels, Colby M. Watts

Master's Theses

Smartphones are frequently connected to external, untrusted charging hardware, creating opportunities for side-channel attacks that do not require malware or direct access to device data. Charger Surfing, a recently proposed charging-line power analysis side-channel attack, reported high accuracy in inferring touchscreen input from voltage measurements collected from a smartphone’s charging cable; however, the reproducibility and robustness of these results under different conditions remain unclear. This thesis presents an independent replication and evaluation of Charger Surfing, including the development of an end-to-end data collection pipeline consisting of a modified charging cable, oscilloscope-based recordings, custom Android app, automated trace processing, and convolutional …

Preserving Structural Alias Information Across The Mlir-To-Llvm Lowering Boundary, Shravan Sheth

Master's Theses

Machine learning training and inference workloads run at massive scale, where the efficiency of generated machine code directly affects throughput and energy consumption. The compilers that lower model specifications to hardware instructions rely on optimization passes that can only exploit information visible in the representations they operate on. MLIR, the intermediate representation framework underlying production machine learning compilers such as IREE and Triton, is designed so that each abstraction level can encode semantics that lower levels cannot represent. One example is memref.subview, which partitions a buffer into typed regions with explicit offsets and sizes, making structural non-overlap provable from the …

Xylem: A Comparative Analysis Of Gpu Dispatch Pipelines For Large-Scale, Procedural Environments, Srinivas Sundararaman

Master's Theses

The real-time rendering of large-scale, procedural scenes presents a significant performance challenge for traditional CPU-bound rendering pipelines. The high volume of draw calls and the need for complex culling and level-of-detail management create bottlenecks that limit scene complexity and visual fidelity. This thesis investigates the evolution of GPU-driven rendering paradigms via the Xylem renderer within NVIDIA’s Donut rendering framework as a solution to these challenges.

A comprehensive benchmarking framework is developed to implement and quantitatively analyze three distinct rendering strategies for a procedurally generated, parameterizable, large-scale forest scene. The evaluated pipelines include: (1) traditional instanced rendering, (2) compute-driven indirect rendering …

Teaching Multi-Core Architecture: Design And Implementation Of A Cache-Coherent Cpu For Undergraduate Education, Isaac R. Lake

Master's Theses

Modern computing has relied on multicore processors for high performance for nearly two decades, yet undergraduate computer engineering curricula often provide limited exposure to parallel hardware architectures and their design challenges. This thesis presents the design of CPE 433, a course that extends the pipelined and cached OTTER CPU developed in CPE 233 and CPE 333 into a multicore processor capable of running parallel workloads. The thesis documents the architectural changes required to adapt the verified single-core design into a multicore system, including MMIO-based interrupt support, a shared cache hierarchy with cache-coherence mechanisms, and clock-gated modules. It further presents a …

Evaluating Design Choices For Gpu-Accelerated Finite-Difference Time-Domain Simulation On Resource-Constrained Devices, Joel Manesh

Master's Theses

The Finite-Difference Time-Domain (FDTD) method is a numerical technique for solving partial differential equations. It was first developed to solve Maxwell’s equations for electromagnetic wave propagation and has since been extended to model other physical phenomena governed by wave propagation. Because the FDTD method is data-parallel, it is well-suited for GPU acceleration; modern FDTD-based simulations run offline on large GPU clusters. There is, however, very little research on running FDTD on resource-constrained embedded GPUs, which are increasingly popular for real-time applications.

This thesis explores a CUDA-based FDTD solver for the 3D wave equation on the Nvidia Jetson Orin Nano. This …

A Novel Approach To Creativity Assessment: Forced Pairwise Ranking With Large Language Models, Phillip R. Gregory Jr

Master's Theses

Assessing creativity at scale remains a persistent challenge in cognitive science, as human raters are costly, slow, and often inconsistent in their judgments. This thesis introduced a novel framework for automated scientific creativity assessment using forced pairwise ranking, in which fine-tuned large language models compared response pairs and determined which was more creative. Five empirical studies were conducted using Llama-2-7B and Llama-2-13B models adapted via LoRA fine-tuning and benchmarked against human scored responses from the Scientific Creative Thinking Test. A regression baseline achieved Pearson �� = .74 on the test set, matching the human inter-rater ceiling reported in the literature. …

Demystifying Hardware Formal Verification For Undergraduate Education: A Risc-V Processor Case Study With Coursework Implementation, Riley A. Peters

Master's Theses

Hardware verification engineers apply formal methods to prove that a digital device always behaves according to its specification. This differs from traditional functional verification, in which engineers establish correctness by repeatedly sending test inputs to the device and comparing the outputs against a reference model. With the growing complexity of integrated circuits, the demand for digital verification engineers with formal methods experience has continued to increase. However, California Polytechnic State University: San Luis Obispo's current curriculum lacks dedicated material to prepare students for these roles.

This thesis seeks to address the lack of formal methods material through two efforts. First, …

Towards Automated And Explainable Insider Threat Response In Electronic Health Records: A Role-Aware Machine Learning Framework, Luca Lippi Ornstil

Master's Theses

Healthcare remains a prime target for cyberattacks, with insider misuse and credential compromise posing major risks to Electronic Health Records (EHRs). This thesis introduces a role-aware, explainable anomaly detection and response framework integrated with OpenEMR to address post-authentication threats. Four models—Local Outlier Factor (LOF), Isolation Forest, Autoencoder, and Graph Neural Network (GNN)—detect behavioral deviations across temporal, device, and role-based features, with LOF serving as the primary runtime detector. A configurable policy engine maps anomaly severity to proportional actions, from email alerts to read-only restrictions or account suspension, all reversible and auditable. Evaluation on real EHR logs shows the system’s operational …

Reverse Engineering Bring Up And Profiling Of Multi-Fpga Systems, Henry A. Evans

Master's Theses

FPGAs have long been used for prototyping and verifying high-speed digital designs in industry and in academic research. As ASIC designs have grown in complexity and size, prototyping those designs on FPGAs has required multiple FPGAs that sometimes span multiple servers. Western Digital donated multiple FPGA-based systems to Cal Poly in 2023. These servers contain multiple high-end AMD FPGAs that are ideal for prototyping large high-speed digital designs, however the full documentation on how to use the servers and how the servers work was not provided. The servers did not come with any information on how to program the FPGAs, …

Griddle: A Novel Hardware Based Matrix Multiplier Architecture, Seth Kiefer

Master's Theses

Matrix multiplication is a computational cornerstone in modern artificial intelligence and scientific computing, yet general-purpose processors struggle to perform these operations efficiently at scale. This thesis presents Griddle, a novel hardware architecture for matrix multiplication implemented on a Xilinx Artix-7 FPGA. Griddle focuses on flexibility and scalability by adopting a purely iterative approach that supports arbitrarily shaped input matrices without requiring padding or strict dimensional constraints. The architecture uses computational pipelines to execute a multiplication operation. Each pipe consists of a multiplication core and accumulation buffer that compute matrix products in parallel. The multiplication core contains a set of multiplier …

Sentry V3: Extending Context Switches On A Trusted Secure Coprocessor, Mark Kong

Master's Theses

Software correctness and integrity is only ensured through trust in the un- derlying hardware. However, modern computer systems are complex to design and secure. Thus, given the choice between performance and security, companies will often prioritize performance, resulting in vulnerable systems. This creates exploitable systems that must be patched retroactively because business value performance over security. One approach to this issue is to separate the root of security from the rest of the system to create a minimal trusted computing base. Trustguard is one instance of this. Trustguard implements a Containment Architecture with Ver- ified Output (CAVO) model which shows …

Optimizing Web Servers With Io_Uring, Mihika Nigam

Master's Theses

Modern web servers face unprecedented demands for high throughput and low latency [10] [11]. Yet, even the state-of-the-art optimizations often fail under heavy workloads on existing infrastructure. Despite advancements in hardware, communication between applications and the kernel remains a critical bottleneck.

Industry surveys reveal that over 50% of production servers still rely on traditional epoll-based architectures [5]. This research aims to investigate and characterize Linux’s new io_uring subsystem, which has the potential to overcome these challenges. Through controlled load testing of various existing architectures like event-driven, multi-process, and multi-threaded architectures (including other commercial servers), we demonstrate how io_uring can help …

Assessment Of The Imx7ulp Heterogeneous Soc For Use In A Next Generation Student Cubesat Obc, Lorenzo A. Pedroza

Master's Theses

CubeSats represent a rapidly evolving platform for space research, industry, and education, demanding increasingly sophisticated onboard computing solutions that balance performance, fault tolerance, size, weight, and power constraints. Although the design of the Cal Poly's CubeSat Lab's (PolySat) current On-Board Computer (OBC) keeps up with many of these factors, the demands of modern workloads like fine attitude determination will start to outpace available compute. While the selection of a more capable processor to address this would have traditionally resulted in increased energy usage, modern system-on-chip (SoC) architectures offer novel ways to trade available compute for power savings on-the-fly. With this …

A Fault-Tolerant, Multi-Heap Dynamic Memory Allocator For Freertos, Garrett E. O'Neill

Master's Theses

The use of dynamic memory allocation presents a significant challenge for embedded systems, particularly in applications that require high reliability. The software controlling these systems needs to perform critical operations within strict timing constraints, and memory management plays a critical role in a system’s ability to meet these constraints. Dynamic memory allocation is inherently non-deterministic: if a task requests memory, it is impossible to predict how long it will take for the memory to be allocated. If a critical task were to rely on dynamically allocated memory, its execution could become stalled leading to a missed deadline and system failure. …

Unified Evaluation Of Real-World Iot-Based Federated Learning, Yi Gu

Master's Theses

Federated learning (FL) is a novel paradigm that enables the training of a global machine learning (ML) model across distributed devices by exchanging model parameters instead of raw data in the training process. Internet of Things (IoT) devices typically operate with limited resources, have weaker security protections, and are more vulnerable to potential thermal stress (TS). Current evaluations of FL are mostly conducted through simulations of multiple clients on a single device. However, there remains a gap in understanding how FL performs under TS in real-world, low-power IoT environments. Conformal prediction (CP) is an effective method for quantifying uncertainty in …

Aiops–Driven Adaptive Anomaly Detection In Evolving Cloud Environments Using Transfer Learning, Mayur Shivakumar

Master's Theses

As cloud-based microservice architectures have become the foundation of contempo- rary enterprise solutions, performance interference, wherein co-located services com- pete for shared resources, remains a significant challenge. This phenomenon, often referred to as the noisy neighbor problem, manifests when one workload unexpect- edly increases the CPU, memory, disk I/O, or network consumption, resulting in latency spikes or throughput degradation for other services. While existing isolation mechanisms (e.g., cgroups and QoS policies) provide some mitigation, they rarely prevent contention entirely, particularly in dynamic, rapidly evolving environments with frequent code deployments.

This thesis proposes an AIOps-driven adaptive anomaly detection framework that integrates …

Efficacy Of Immersive Virtual Reality Gameplay In Environmental Attitude Change: The Case Of Abandoned Offshore Oil Platforms In Santa Barbara, Arun Prasad Srinivasan Manoharan

Master's Theses

Public perception plays an important role in shaping conservation policies and decisions, especially in contested environmental spaces. Offshore oil platforms, historically viewed as environmental hazards, have been found to serve as marine habitats that support diverse marine life. However, public perception remains largely negative, influenced by concerns over pollution from past oil spill accidents. Traditional environmental education methods, such as lectures and documentaries, often fail to engage audiences effectively or shift entrenched opinions. This study explores the efficacy of immersive Virtual Reality (VR) gameplay in changing environmental attitudes, specifically in the context of abandoned offshore oil platforms in Santa Barbara, …

Bonsai Merkle Tree Streams: Bulk Memory Verification Unit For Trusted Program Verification System, Richard J. Rios

Master's Theses

Today, all modern computing systems are undoubtedly vulnerable to numerous types of attacks that could be targeted toward any layer of the system from dedicated hardware to highly abstracted software. Unfortunately, many devices and systems naturally contain inadequately protected components or software modules that un- dermine their security as a whole. Additionally, security is heavily variable system to system, and has a huge dependence on adequate implementation and ongoing support from device and software manufacturers. To address these various security issues in a very general way, TrustGuard, a containment security system utilizing an external device called the Sentry that would …

Hardware Control Unit For Trusted Program Verification System, Jake Owen Alt

Master's Theses

Trust in the underlying hardware is the foundational step towards trusting the correctness and integrity of a software application. However, verifying that today's extremely complex processors work exactly as intended has not been feasible, as evidenced by several recent hardware bugs. Trustworthy, formally verified processors currently forego intricate performance enhancements such as out-of-order execution, hampering them substantially versus their less secure counterparts.

The Containment Architecture with Verified Output (CAVO) system solves this problem by isolating the host system and requiring the result of each instruction to be validated by a small, trusted hardware module called the Sentry. Any transmissions to …

Digimindready: Enhancing Military Readiness Through Edge Ai-Driven Wellness, Education, And Digital Discipline Via Privacy-First Mhealth Innovation, Md Mehedi Hasan

Master's Theses

Military personnel often find themselves in intense situations that require high focus. Successfully engaging in these dangerous missions means they must efficiently control cognitive load, manage overwhelming stress, and stay focused through distractions to perform at their best. Military training significantly focuses on human performance, which benefits military readiness. The 21st century has introduced unanticipated challenges to all, such as the adverse effects of excessive screen time, external distractions, and over-reliance on technology without being aware of digital discipline. Militaries are no exception. These challenges have become an emerging threat to military personnel's cognitive, emotional, and physical well-being. On top …

A Comparative Study Of The Npm, Pypi, Maven, And Rubygems Open-Source Communities, Saurav Gupta

Master's Theses

Open-source software (OSS) ecosystems, defined as environments composed of package managers and programming languages (e.g., NPM for JavaScript), are essential for software development and foster collaboration and innovation. Although their significance is acknowledged, understanding what makes OSS communities healthy and sustainable requires further exploration. This thesis quantitatively assesses the health of OSS projects and communities within the NPM, PyPI, Maven, and RubyGems ecosystems. We explore five research questions addressing project standards, community responsiveness, contribution distribution, contributor retention, and newcomer integration strategies. Our analysis shows varied documentation practices, insider engagement levels, and contribution patterns. Our findings highlight both strengths and different …

A Federation Of Sentries: Secure And Efficient Trusted Hardware Element Communication, Blake A. Ward

Master's Theses

Previous work introduced TrustGuard, a design for a containment architecture that allows only the result of the correct execution of approved software to be outputted. A containment architecture prevents results from malicious hardware or software from being communicated externally. At the core of TrustGuard is a trusted, pluggable device that sits on the path between an untrusted processor and the outside world. This device, called the Sentry, is responsible for validating the correctness of all communication before it leaves the system. This thesis seeks to leverage the correctness guarantees that the Sentry provides to enable efficient secure communication between two …

A Study On Privacy Over Security And Privacy Enhancing Networks, Everett Lee Conway

Master's Theses

With rapid developments in communication technologies and awareness of security and privacy risks online, Security and Privacy Enhancing Networks (SPENs) have become increasingly popular. Especially during the COVID-19 pandemic, workplaces encouraged employees to take additional security measures, such as VPNs. In this work, we conduct a comprehensive study on website fingerprinting attacks. A comprehensive system model and threat model based on two types of SPENs (Virtual Private Networks and Tor Networks) are presented. Moreover, we demonstrate a website fingerprinting attack by ethically collecting website fetch data and analyzing the collected data using five different machine learning classification models including k …

Evaluating The Effect Of Noise On Secure Quantum Networks, Karthick Anbalagan

Master's Theses

This thesis focuses on examining the resilience of secure quantum networks to environmental noise. Specifically, we evaluate the effectiveness of two well-known quantum key distribution (QKD) protocols: the Coherent One-Way (COW) protocol and Kak’s Three-Stage protocol (Kak06). The thesis systematically evaluates these protocols in terms of their efficiency, operational feasibility, and resistance to noise, thereby contributing to the progress of secure quantum communications. Using simulations, this study evaluates the protocols in realistic scenarios that include factors such as noise and decoherence. The results illustrate each protocol’s relative benefits and limitations, highlighting the three-stage protocol’s superior security characteristics, resistance to interference, …

Decentralized Machine Learning On Blockchain: Developing A Federated Learning Based System, Nikhil Sridhar

Master's Theses

Traditional Machine Learning (ML) methods usually rely on a central server to per-
form ML tasks. However, these methods have problems like security risks, data
storage issues, and high computational demands. Federated Learning (FL), on the
other hand, spreads out the ML process. It trains models on local devices and then
combines them centrally. While FL improves computing and customization, it still
faces the same challenges as centralized ML in security and data storage.

This thesis introduces a new approach combining Federated Learning and Decen-
tralized Machine Learning (DML), which operates on an Ethereum Virtual Machine
(EVM) compatible blockchain. The …