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Improving Resource and Energy Efficiency for Cloud 3D through Excessive Rendering Reduction
(Association for Computing Machinery, 2024-04-22) Liu, Tianyi; Lucas, Jerry; He, Sen; Liu, Tongping; Wang, Xiaoyin; Wang, Wei
The rise of cloud gaming makes interactive 3D applications an emerging type of data center workload. However, the excessive rendering in current cloud 3D systems leads to large gaps between the cloud and client frame rates (FPS, frames per second), thus wasting resources and power. Although FPS regulation can remove excessive rendering, due to the highly-varying frame processing time and the use of rendering delays, existing cloud FPS regulation solutions have low FPS and slow motion-to-photon (MtP) latency, causing violations of Quality-of-Service (QoS) requirements. In this paper, we present a novel cloud FPS regulation solution, called OnDemand Rendering (ODR). ODR employs multi-buffering, dynamic rendering delay/acceleration, and input processing prioritization to reduce excessive rendering and ensure QoS satisfaction. ODR was evaluated in our private cloud and Google cloud. Evaluation results showed that ODR effectively removed excessive rendering, thus improving DRAM performance by 19% and reducing power usage by 16% over no FPS regulation. Better memory efficiency also allowed ODR to increase client FPS by 5.5%. Moreover, ODR reduced average MtP latency by more than 92% and outperformed existing FPS regulations. More importantly, ODR's high FPS and low latency make it feasible to deploy 3D applications to conventional public clouds.
Experiences in Delivering Online CS Teacher Professional Development
(Association for Computing Machinery, 2024-03-07) Wilde, Jina; Beltran, Emiliano; Zawatski, Michael J.; Fernandez, Amanda S.; Prasad, Priya V.; Yuen, Timothy T.
This paper describes our team's experience in designing and delivering the online teacher professional development (PD) program, Computer Science for San Antonio (CS4SA), aimed at empowering educators with computer science (CS) knowledge to increase Latinx participation in CS and STEM education within a large, urban predominantly Latinx school district in South Texas. This paper highlights the successes, challenges, and lessons learned while facilitating two cohorts of the CS PD through online platforms during the COVID-19 pandemic. As a result of this program, participants recognized the importance of integrating CS into their classroom and becoming advocates for the discipline at the high school level. Additionally, teachers, investigators, and other personnel learned important lessons for enhancing the program's impact through collaboration with district administrators and refinement of the online learning experience.
Disability Accommodation and Accessibility in Post-secondary Education: A Preliminary Study
(2024-05-10) Campa, Olivia
Accommodations are a critical component of accessibility for students with disabilities in post-secondary education. Although the purpose of accommodations is to ensure that students with disabilities have equal opportunity to excel within a learning environment, only a minute portion of the disabled population registers to acquire accommodations in university. Numerous barriers that students with disabilities encounter when obtaining accommodations have been identified in previous literature; however, our research intends to exhaustively examine the nature of prominent barriers at a local university and particularly amongst unregistered students. By understanding why various barriers exist and the limitations they impose on students, universities and other influential systems can attempt to alleviate these obstacles inhibiting accessibility in post-secondary education. This study explores disability as a political identity, evaluates attitudes towards disability in the U.S., and discusses proposed barriers in education from past research. It then analyses data from a survey given to students with neurodevelopmental, mental or emotional, or learning disabilities that are not registered with student disability services. Through descriptive statistics and qualitative analysis, this study identifies prominent barriers alongside student regard for accommodation effectiveness. Finally, this study provides guidance in targeting these disparities to educational institutions.
SeTe nano-alloy for the regulation of redox reaction in cancer cells
(2024-05-10) Flores, Ernesto
Nanomaterials are one of the most promising technologies of the 21st century. They are widely used in fields of science, health care, agriculture, technology, and industries. Their physical and chemical properties, such as magnetic, electrical, and optical, differentiate them from their bulk counterparts. These physical characteristics make them the focus of different scientific studies. The synthesis of nanomaterials is currently being studied due to the restrictions relevant to the translation of these materials from laboratory to fabrication. Pulse Laser Ablation in Liquids (PLAL) has been shown to be optimal. It is a versatile technique that allows the production of most nanomaterials, is low-cost and is environmentally friendly. To overcome the challenges of the oxidative effects of traditional liquid phases (water, acetone), we synthesized SeTe nanoalloys utilizing deep eutectic solvents with Ch-Cl as the hydrogen bond donor. The hydrogen bond acceptor is sugar-based to increase biocompatibility. We analyzed the size, shape, and charge of the nanomaterials to characterize the properties of SeTe. Our goal is to regulate redox activity in cancer cells by reducing the toxicity of SeTe by using Deep Eutectic Solvents. The use of this solvent as a liquid environment for pulse laser ablation was explored for the first time. Another key factor to consider ahead for the scalability of the system is the low cost of production of these deep eutectic solvents.
CS1 with a Side of AI: Teaching Software Verification for Secure Code in the Era of Generative AI
(Association for Computing Machinery, 2024-03-07) Fernandez, Amanda S.; Cornell, Kimberly A.
As AI-generated code promises to become an increasingly relied upon tool for software developers, there is a temptation to call for significant changes to early computer science curricula. A move from syntax-focused topics in CS1 toward abstraction and high-level application design seems motivated by the new large language models (LLMs) recently made available. In this position paper however, we advocate for an approach more informed by the AI itself - teaching early CS learners not only how to use the tools but also how to better understand them. Novice programmers leveraging AI-code-generation without proper understanding of syntax or logic can create "black box" code with significant security vulnerabilities. We outline methods for integrating basic AI knowledge and traditional software verification steps into CS1 along with LLMs, which will better prepare students for software development in professional settings.