arXiv subjects

Michael Bechtel

Publications and source records attributed to Michael Bechtel.

7 recordsLinked to original sources

arXiv2026

Hypergamigication Through Integrating Game Engines and Learning Management Systems: Ender's Game

This paper discusses games, their use in education, and previous work on integrating game engines and learning management systems (LMS). It proposes a bidirectional integration where game environments are generated using LMS content, introducing the concept of hypergamification as the use of a comprehensive game environment rather than isolated game design elements. A working pilot implementation of an importable Unity package for Blackboard integration is demonstrated, along with a demo game that uses the developed package. The paper also discusses the limitations of the proposed approach and outlines avenues for future work.

cs.CY↗

arXiv2023

Nonreciprocal Spin Waves in Nanoscale Domain Walls Detected by Scanning X-ray Microscopy in Perpendicular Magnetic Anisotropic Fe/Gd Multilayers

Spin wave nonreciprocity in domain walls (DWs) allows for unidirectional signal processing in reconfigurable magnonic circuits. Using scanning transmission x-ray microscopy (STXM), we examined coherently-excited magnons propagating in Bloch-like DWs in amorphous Fe/Gd multilayers with perpendicular magnetic anisotropy (PMA). Near 1 GHz we detected magnons with short wavelengths down to $\lambda = 281$ nm in DWs whose minimum width amounted to $\delta_{\rm DW} = 52$ nm. Consistent with micromagnetic simulations, the STXM data reveal their nonreciprocal magnon band structures. We identified Bloch points which disrupted the phase evolution of magnons and induced different $\lambda$ adjacent to the topological defects. Our observations provide direct evidence of nonreciprocal spin waves within Bloch-like DWs, serving as programmable waveguides in magnonic devices with directed information flow.

cond-mat.mes-hall↗

arXiv2023

Analysis and Mitigation of Shared Resource Contention on Heterogeneous Multicore: An Industrial Case Study

In this paper, we present a solution to the industrial challenge put forth by ARM in 2022. We systematically analyze the effect of shared resource contention to an augmented reality head-up display (AR-HUD) case-study application of the industrial challenge on a heterogeneous multicore platform, NVIDIA Jetson Nano. We configure the AR-HUD application such that it can process incoming image frames in real-time at 20Hz on the platform. We use Microarchitectural Denial-of-Service (DoS) attacks as aggressor workloads of the challenge and show that they can dramatically impact the latency and accuracy of the AR-HUD application. This results in significant deviations of the estimated trajectories from known ground truths, despite our best effort to mitigate their influence by using cache partitioning and real-time scheduling of the AR-HUD application. To address the challenge, we propose RT-Gang++, a partitioned real-time gang scheduling framework with last-level cache (LLC) and integrated GPU bandwidth throttling capabilities. By applying RT-Gang++, we are able to achieve desired level of performance of the AR-HUD application even in the presence of fully loaded aggressor tasks.

cs.PF↗

arXiv2022

DeepPicarMicro: Applying TinyML to Autonomous Cyber Physical Systems

Running deep neural networks (DNNs) on tiny Micro-controller Units (MCUs) is challenging due to their limitations in computing, memory, and storage capacity. Fortunately, recent advances in both MCU hardware and machine learning software frameworks make it possible to run fairly complex neural networks on modern MCUs, resulting in a new field of study widely known as TinyML. However, there have been few studies to show the potential for TinyML applications in cyber physical systems (CPS). In this paper, we present DeepPicarMicro, a small self-driving RC car testbed, which runs a convolutional neural network (CNN) on a Raspberry Pi Pico MCU. We apply a state-of-the-art DNN optimization to successfully fit the well-known PilotNet CNN architecture, which was used to drive NVIDIA's real self-driving car, on the MCU. We apply a state-of-art network architecture search (NAS) approach to find further optimized networks that can effectively control the car in real-time in an end-to-end manner. From an extensive systematic experimental evaluation study, we observe an interesting relationship between the accuracy, latency, and control performance of a system. From this, we propose a joint optimization strategy that takes both accuracy and latency of a model in the network architecture search process for AI enabled CPS.

cs.LG↗

arXiv2020

Memory-Aware Denial-of-Service Attacks on Shared Cache in Multicore Real-Time Systems

In this paper, we identify that memory performance plays a crucial role in the feasibility and effectiveness for performing denial-of-service attacks on shared cache. Based on this insight, we introduce new cache DoS attacks, which can be mounted from the user-space and can cause extreme worst-case execution time (WCET) impacts to cross-core victims -- even if the shared cache is partitioned -- by taking advantage of the platform's memory address mapping information and HugePage support. We deploy these enhanced attacks on two popular embedded out-of-order multicore platforms using both synthetic and real-world benchmarks. The proposed DoS attacks achieve up to 111X WCET increases on the tested platforms.

cs.CR↗

arXiv2020

SpectreRewind: Leaking Secrets to Past Instructions

Transient execution attacks utilize micro-architectural covert channels to leak secrets that should not have been accessible during logical program execution. Commonly used micro-architectural covert channels are those that leave lasting footprints in the microarchitectural state, for example, a cache state change, from which the secret is recovered after the transient execution is completed. In this paper, we present SpectreRewind, a new approach to create contention based covert channels for transient execution attacks. In our approach, a covert channel is established by issuing the necessary instructions logically before the transiently executed victim code. Unlike prior contention based covert channels, which require simultaneous multi-threading (SMT), SpectreRewind supports single hardware thread based covert channels, making it viable on systems where attacker cannot utilize SMT. We show that contention on the floating point division unit on commodity processors can be used to create a high-performance (~100 KB/s), low-noise covert channel for transient execution attacks instead of commonly used flush+reload based cache covert channels. We implement a Meltdown attack utilizing the proposed covert channel showing competitive performance compared to the stateof-the-art cache based covert channel implementation. We also show that the covert channel works in the JavaScript engine of a Chrome browser.

cs.CR↗

arXiv2012

Ion beam lithography for Fresnel zone plates in X-ray microscopy

Fresnel Zone Plates (FZP) are to date very successful focusing optics for X-rays. Established methods of fabrication are rather complex and based on electron beam lithography (EBL). Here, we show that ion beam lithography (IBL) may advantageously simplify their preparation. A FZP operable from the extreme UV to the limit of the hard X-ray was prepared and tested from 450 eV to 1500 eV. The trapezoidal profile of the FZP favorably activates its 2nd order focus. The FZP with an outermost zone width of 100 nm allows the visualization of features down to 61, 31 and 21 nm in the 1st, 2nd and 3rd order focus respectively. Measured efficiencies in the 1st and 2nd order of diffraction reach the theoretical predictions.

physics.optics↗