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Poster: Edge-Assisted Over-the-Air Software Updates 23

Poster: Edge-Assisted Over-the-Air Software Updates

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proceedings of the Eighth acm/IEEE Symposium on Edge computing

作者： Arpan Bhattacharjee Hamza Mahmood Sidi Lu Nejib Ammar Akila Ganlath Weisong Shi Computer and Information Sciences (CIS) University of Delaware Newark Delaware USA University of Delaware Newark Delaware USA William & Mary Williamsburg Virginia USA Toyota InfoTech Lab Mountain View California USA

ISBN: (纸本)9798400701238

The exploration of software Over-the-Air (OTA) updates for automotive applications is currently very limited. Our work introduces an edge-assisted framework for automotive OTA updates that carefully accounts for various factors, including different software models in vehicles, communication distances, and cluster sizes. We present valuable insights using key evaluation metrics like update speed, data transmission efficiency, and success rate, accompanied by a thorough scalability analysis. Our research involves three distinct vehicle software models: ResNet-18 (46.8 MB), ResNet-50 (102.5 MB), and Faster R-CNN (175.2 MB). These models are used to evaluate update performance across eight distance categories ranging from 0 to 21 meters with a 3-meter interval. We also utilize diverse computing platforms to assess the success rate and conduct a comprehensive scalability analysis. This innovative approach significantly advances our understanding and practical implementation of OTA updates in the automotive field.

关键词： edge computing and over-the-air (OTA) update

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"I See You!": A Design Framework for Interface Cues about Agent Visual Perception from a Thematic analysis of Videogames 22

"I See You!": A Design Framework for Interface Cues about Ag...

引用

CHI Conference on Human Factors in computing systems (CHI)

作者： Rueben, Matthew Horrocks, Matthew R. Martinez, Jennifer Eleanor Cormier, Michelle, V LaLone, Nicolas Fraune, Marlena R. Dugas, Z. Toups New Mexico State Univ Las Cruces NM 88003 USA Embry Riddle Aeronaut Univ Daytona Beach FL USA Univ Nebraska Dept Informat Syst & Quantitat Anal Omaha NE 68182 USA New Mexico State Univ Dept Psychol Las Cruces NM 88003 USA

ISBN: (纸本)9781450391573

As artifcial agents proliferate, there will be more and more situations in which they must communicate their capabilities to humans, including what they can "see." Artifcial agents have existed for decades in the form of computer-controlled agents in videogames. We analyze videogames in order to not only inspire the design of better agents, but to stop agent designers from replicating research that has already been theorized, designed, and tested in-depth. We present a qualitative thematic analysis of sight cues in videogames and develop a framework to support human-agent interaction design. The framework identifes the diferent locations and stimulus types - both visualizations and sonifcations - available to designers and the types of information they can convey as sight cues. Insights from several other cue properties are also presented. We close with suggestions for implementing such cues with existing technologies to improve the safety, privacy, and efciency of human-agent interactions.

关键词： human-robot interaction thematic analysis videogames sight cues qualitative methodologies

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Generative AI and Gametheory for the development and deployment of Honeypots to enhance the Security of Industrial Automation and Control systems

Generative AI and Gametheory for the development and deploym...

引用

2024 Lock-in or log out? Wie digitale Souveranitat gelingt, INFORMATIK 2024

作者： Peters, Ludger Gkoktsis, Georgios Fraunhofer SIT | ATHENE Rheinstraße 75 Darmstadt64295 Germany

ISBN: (纸本)9783885797463

The computing hardware and software of modern Industrial automation and control system has evolved to be like traditional IT hardware in the first decade of this century. Due to the specialized demands on these systems introduced, e.g., by specialized measurement equipment or additional safety requirements, typical IT update and security procedures cannot be followed. This paper explores the use of generative AI models in honeypots for enhancing the cybersecurity in industrial automation and control systems. As honeypots are used as traps for system attackers, the deployment of generative AI models enables the creation of more convincing and sophisticated decoy environments. This increases the likelihood of an attacker’s engagement with the environment, improving the detection and analysis of malicious activities. Through a brief summary, this paper quantifies the existing research on generative AI in honeypots. The findings highlight the significant potential of generative AI models in enhancing the security of IACS through their integration into honeypot systems. This can ultimately lead to organizations being able to gain more in-depth insights into emerging cyber threats, improve their incident response capabilities, and enhance the resilience of their industrial control systems. To quantify the impact of employing such advanced deception technologies on the behavior of the attacker, this paper proposes a novel approach using a non-cooperative game-theoretic framework for deploying honeypots in OT systems. This methodology enables strategic analysis that balances limited resources with the need to predict and counter sophisticated cyber adversaries’ actions. © 2024 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Generative adversarial networks

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Enabling Cache Aware Roofline analysis with Portable Hardware Counter Metrics 12

Enabling Cache Aware Roofline analysis with Portable Hardwar...

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12th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer systems held as part of the 33rd acm/IEEE International Conference for High Performance computing, Networking, Storage and analysis

作者： Gravelle, Brian J. Nystrom, William David Yokelson, Dewi Norris, Boyana Los Alamos Natl Lab Los Alamos NM 87545 USA Univ Oregon Dept Comp & Informat Sci Eugene OR 97403 USA

ISBN: (纸本)9781665411189

In this paper, we seek to provide guidance on how to empirically collect the information required to plot application points for Intel's Cascadelake XEON processor and Fujitsu's A64FX ARM-based processor. Understanding how to process this information is vital to use the Roofline for empirical performance analysis on these systems. This report is designed to enable users to collect data for these systems and lay the groundwork for us to create a portable method for empirical Roofline-based performance analysis. We do so by presenting our methods and several examples of them in use.

关键词： measurement Analytical models Computational modeling Conferences Benchmark testing Hardware Computer performance

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CHash: A High Cost-Performance Hash Design for CXL-based Disaggregated Memory System 25

CHash: A High Cost-Performance Hash Design for CXL-based Dis...

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Abstracts of the 2025 acm SIGMETRICS International Conference on measurement and Modeling of Computer systems

作者： Mengting Lu Gaocong Liu Kun Wang Feng Zhu Shu Li Alibaba Cloud Computing Hangzhou China

ISBN: (纸本)9798400715938

The exponential growth in demand for high-performance computing systems has created an urgent requirement for innovative memory technologies that can provide higher bandwidth and enhanced capacity scalability. In particular, Compute Express Link (CXL) has emerged as a promising solution for memory expansion and system acceleration. Hash-based index structures are widely recognized as fundamental components of in-memory database systems, and they are commonly used for indexing in-memory key-value stores due to their capability for rapid lookup performance. How to design and maintain a hash index structure in a CXLbased disaggregated memory system, with comprehensive consolidation, is a challenging topic of in-depth ***, the architecture and characteristics of the CXL memory device are significantly distinct from those of DRAM and PMEM. Simply applying prior hashing approaches without considering the differences would not fully exploit the characteristics presented by CXL memory devices. This leads to the performance inefficiencies of conventional indexing designs and operation processes that overlook the characteristics of the CXL memory *** this paper, we conduct extensive experiments on two real CXL memory devices based on the 4thgeneration Intel® Xeon® Scalable Processor with CXL 1.0 support. Specifically, we run various microbenchmarks not only to evaluate the performance characteristics of CXL memory devices, but also to measure the performance impact of different memory allocation methods. We observe significant performance disparities and allocation inefficiencies, motivating us to innovate the hash design in the CXL-based disaggregated memory system. Upon in-depth analysis, we propose CHash, as shown in Figure 1, which consists of several key designs, as shown below:Stage buckets for KV batching. The experimental results show that real CXL memory devices from different vendors exhibit diverse performance characteristics. Moreover, ther

关键词： compute express link

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Component-Based Analytical Modeling of GPU Runtime Performance: a Case-Study in Scientific computing 25

Component-Based Analytical Modeling of GPU Runtime Performan...

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2025 International Conference on Performance Engineering-ICPE-Annual

作者： Chen, Jolly Varbanescu, Ana Lucia Dessole, Monica Univ Twente Enschede Netherlands CERN Geneva Switzerland

ISBN: (纸本)9798400710735

Analytical performance models are excellent tools for fast performance prediction and can be used effectively for designing and tuning parallel algorithms. However, such models are non-trivial to build, especially when both the application and the system are very complex. In this context, we study the applicability and limitations of a component-based analytical approach to model (and predict) the performance of GPU operations. Using microbenchmarks, we incorporate dynamic runtime behavior and architecture-dependent factors in the predictions. Our model validation and evaluation focus on a specific case-study: ROOT histogramming - a high-energy physics (HEP) application whose performance is critical in most experiments' data analysis pipeline (i.e., histogramming is run millions of times per analysis). We show our approach in action by constructing the model and showing how it can be useful for scenario analysis, where it can accurately predict trends and performance rankings. In addition, the design process of the model itself can lead to insights into the source of performance bottlenecks. We conclude that component-based modeling is feasible and practical for GPU applications. It is a modeling approach with a reasonable trade-off between accuracy, prediction speed, and interoperability.

关键词： Analytical Model Component-based Approach GPU Runtime Prediction Microbenchmarks Histograms ROOT

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Serverless computing for Dynamic HPC Workflows 24

Serverless Computing for Dynamic HPC Workflows

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proceedings of the SC '24 Workshops of the International Conference on High Performance computing, Network, Storage, and analysis

作者： Vijay Thurimella Philipp Raith Rolando P. Hong Enriquez Anderson Andrei Da Silva Gourav Rattihalli Ada Gavrilovska Dejan Milojicic School of Computer Science Georgia Institute of Technology Atlanta USA and Hewlett Packard Labs Hewlett Packard Enterprise Milpitas CA Hewlett Packard Labs Hewlett Packard Enterprise Milpitas CA School of Computer Science Georgia Institute of Technology Atlanta USA

ISBN: (纸本)9798350355543

Containers have become an important component for scientific workflows, enhancing reproducibility, portability, and isolation when coupled with workflow management systems. However, integrating containers with these systems can be complex, potentially hindering wider adoption. Serverless platforms offer a solution by providing a layer of abstraction over container orchestrators, simplifying management while introducing event-driven capabilities. This paper presents a novel integration of serverless with workflow management systems to optimize scientific workflow execution. Our approach leverages serverless functions to dynamically provision containers for workflow tasks, resulting in up to 30% faster execution. We found that performance can be further improved by reusing containers between multiple different tasks that were provisioned by the serverless platform. These findings demonstrate the utility of combining specialized container orchestration with established workflow management to streamline scientific computing, improve resource utilization, and accelerate time-to-results. Server-less' event-driven architecture enables efficient resource scaling, aligning with the dynamic nature of scientific workloads.

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Development of Fedora Linux Distribution for RISC-V (RV64G) Architecture 24

Development of Fedora Linux Distribution for RISC-V (RV64G) ...

引用

proceedings of the SC '24 Workshops of the International Conference on High Performance computing, Network, Storage, and analysis

作者： Surendra Billa Arif Badar Rushikesh Jadhav Yogeshwar Sonawane Sanjay Wandhekar HPC Technologies Group Centre for Development of Advanced Computing Pune India

ISBN: (纸本)9798350355543

The rapid evolution of the RISC-V architecture presents both opportunities and challenges, particularly for systems lacking support for compressed instructions (RV64G). This paper explores the development of a Fedora Linux distribution tailored specifically for the RV64G architecture, providing a comprehensive narrative of the process from inception to implementation. Key milestones include establishing a robust filesystem hierarchy, creating a cross-compiler, preparing and bootstrapping target image, integrating a native GCC compiler, and leveraging the Koji build system to streamline package rebuilding. Additionally, we introduce a custom Python application to automate the Koji builds, enhancing efficiency and consistency. Our innovative approach not only addresses the immediate needs of RV64G systems but also lays the groundwork for future advancements in High-Performance computing (HPC) on the RISC-V platform. This work aims to bridge the gap in the current ecosystem, offering a scalable and maintainable solution that promotes the broader adoption of RISC-V technology [1].

关键词： C-DAC Vega Microprocessor

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The Ethics of Emotion in Artificial Intelligence systems 21

The Ethics of Emotion in Artificial Intelligence Systems

引用

acm Conference on Fairness, Accountability, and Transparency (FAccT)

作者： Stark, Luke Hoey, Jesse Univ Western Ontario Fac Informat & Media Studies London ON Canada Univ Waterloo David R Cheriton Sch Comp Sci Waterloo ON Canada

ISBN: (纸本)9781450383097

In this paper, we develop a taxonomy of conceptual models and proxy data used for digital analysis of human emotional expression and outline how the combinations and permutations of these models and data impact their incorporation into artificial intelligence (AI) systems. We argue we should not take computer scientists at their word that the paradigms for human emotions they have developed internally and adapted from other disciplines can produce ground truth about human emotions;instead, we ask how different conceptualizations of what emotions are, and how they can be sensed, measured and transformed into data, shape the ethical and social implications of these AI systems.

关键词： emotion affect artificial intelligence AI machine learning ML ethics norms Basic Emotion Theory Action Control Theory affective computing emotion AI privacy fairness AI ethics

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From Failure to Insight: Analyzing Disk Breakdowns in Large-Scale HPC Environments 24

From Failure to Insight: Analyzing Disk Breakdowns in Large-...

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proceedings of the SC '24 Workshops of the International Conference on High Performance computing, Network, Storage, and analysis

作者： Anjus George Meng Wang Jesse Hanley Garrett Wilson Ransom John Bent Christopher Zimmer National Center for Computational Sciences Oak Ridge National Laboratory Oak Ridge TN USA Department of Computer Science University of Chicago Chicago IL USA HPC Infrastructure Los Alamos National Laboratory Los Alamos NM USA High Performance Computing Los Alamos National Laboratory Los Alamos NM USA

ISBN: (纸本)9798350355543

Disk failure data provides valuable insights for preventing failures, enhancing storage robustness, guiding system design and deployment, and ensuring reliable operations at data centers. This paper introduces two disk failure datasets collected from large-scale HPC production environments over the past five years, comprising over 5,000 failure records from more than 40,000 disks. We analyzed these datasets across multiple dimensions, including temporal, spatial, and relational trends, and performed a comprehensive reliability assessment. Our analysis yielded numerous observations and insights that influence various operational aspects of HPC storage systems. We believe this study offers a holistic understanding of disk failure trends likely to interest the HPC storage community.

关键词： Cause effect analysis

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