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Performance Tools for the NEC SX-Aurora Tsubasa 25

Performance Tools for the NEC SX-Aurora Tsubasa

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16th acm/SPEC International Conference on Performance Engineering, ICPE Companion 2025

作者： Von Elm, Christian Schöne, Robert Cids Information Services and High Performance Computing (ZIH) Tu Dresden Dresden Germany

ISBN: (纸本)9798400711305

83% of the TOP500s performance share is contributed by systems that utilize accelerators. While the overwhelming majority of accelerators in TOP500 systems are Graphics Processing Units (GPUs), other accelerators, that excel in specialized applications, are also present. The NEC SX-Aurora Tsubasa is the most common non-GPU accelerator for November 2024 TOP500 systems and has proven to be efficient for certain codes like the weather and climate model ICON. However, applications have to be carefully optimized to achieve this efficiency. Performance analysis tools, which support developers in understanding the runtime behavior of their programs can help in that regard. With profiling tools programmers can see which functions contribute to the overall runtime, but also which of them are causing high amounts of cache misses. However, the basic principle of profiling - the summarization of metrics over all invocations of a function - can hide differences between subsequent invocations of the same function. Due to its implementation a function could perhaps only exhibit high-amounts of cache misses, increasing its runtime, every fourth call. Hence, tools that allow developers to trace their applications by recording non-aggregated events in the time-domain can further provide insight into the applications performance properties. However, as of today only profiling tools exist for the NEC SX-Aurora Tsubasa. In this paper, we use its performance measurement capabilities to extend the Score-P measurement infrastructure and the lo2s system monitoring tool to enable developers to record the exact execution of programs using tracing. We further demonstrate how developers can find performance issues that cannot be detected with profiling-based tools in the ICON weather and climate model. We also describe the overhead and perturbation that our tools introduce. © 2025 Owner/Author.

关键词： high performance computing measurement performance engineering vector computing

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RJoules: An Energy measurement Tool for R 23

RJoules: An Energy Measurement Tool for R

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proceedings of the 38th IEEE/acm International Conference on Automated Software Engineering

作者： Rajrupa Chattaraj Sridhar Chimalakonda Research in Intelligent Systems and Human Analytics Lab Department of Computer Science and Engineering Indian Institute of Technology Tirupati India

ISBN: (纸本)9798350329964

With the exponential growth of data, the demand for effective data analysis tools has increased significantly. R language, known for its statistical modeling and data analysis capabilities, has become one of the most popular programming languages among data scientists and researchers. As the importance of energy-aware software systems continues to rise, several studies investigate the impact of source code and different stages of machine learning model training on energy consumption. However, existing studies in this domain primarily focus on programming languages like Python and Java, resulting in a lack of energy measuring tools for other programming languages such as R. To address this gap, we propose "RJoules", a tool designed to measure the energy consumption of R code snippets. We evaluate the correctness and performance of RJoules by applying it to four machine learning algorithms on three different systems. Our aim is to support developers and practitioners in building energy-aware systems in R. The demonstration of the tool is available at https://***/yMKFuvAM-DE and related artifacts at https://***/RJoules/.

关键词： energy measurement

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"I Will Not Drink With You Today": A Topic-Guided Thematic analysis of Addiction Recovery on Reddit 22

"I Will Not Drink With You Today": A Topic-Guided Thematic A...

引用

CHI Conference on Human Factors in computing systems (CHI)

作者： Gauthier, Robert P. Costello, MMary Jean Wallace, James R. Univ Waterloo Waterloo ON Canada Homewood Res Inst Guelph ON Canada

ISBN: (纸本)9781450391573

Recovery from addiction is a journey that requires a lifetime of support from a strong network of peers. Many people seek out this support through online communities, like those on Reddit. However, as these communities developed outside of existing aid groups and medical practice, it is unclear how they enable recovery. Their scale also limits researchers ability to engage through traditional qualitative research methods. To study these groups, we performed a topic-guided thematic analysis that used machine-generated topic models to purposively sample from two recovery subreddits: r/stopdrinking and r/OpiatesRecovery. We show that these communities provide access to an experienced and accessible support group whose discussions include consequences, reflections, and celebrations, but that also play a distinct metacommunicative role in supporting formal treatment. We discuss how these communities can act as knowledge sources to improve in-person recovery support and medical practice, and how computational techniques can enable HCI researchers to study communities at scale.

关键词： Reddit machine learning thematic analysis addiction online communities

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The art of deep learning and natural language processing for emotional sentiment analysis on the academic scholars' peer review process. 23

The art of deep learning and natural language processing for...

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24th Annual Conference on Information Technology Education, SIGITE 2023

作者： Mah, Pascal Muam AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9798400701306

Deep learning and natural language processing has emerged as modern machine with state-of-the-art modern learning and applicable techniques that help academicians, students, and teachers to identify, evaluate and validate documents and text features. Most educational systems have incorporated deep learning and natural language processing in fulfilling tasks except publishers and editorial boards, whom they handle important aspects of academic achievement in the decision-making for both journals and conferences. The aim is to introduce a standardized systematic peer review process based on factual justification, amendment, and recommendation approach on scholarly works free from emotional sentiments, politicization, bias, criticism, and condemnation. The study uses peer review feedback from journal XXXX to identify, evaluate and validate emotional sentimental aspects. A Confusion Metrix model was examined in the study to justify and validate the emotional sentiment pros and cons of the reviewer. Also, behavior-oriented drive and influential functions were used to convert text to value and rank the sentiment score. Each reviewer's text was converted into value using a behavior-oriented drive and influential function were used to examine the emotional sentiment level of the reviewers. Text mining and extraction of data uses a natural language process approach to identify sentiments from the reviewer's comments. Based on the confusion matrix and behavior-oriented drive, and influential function, the findings revealed limited significant emotional sentiment involved during the peer review process. The study concluded that the reviewers didn't perfectly validate the manuscript content due to minor emotional sentiments. The reviewer's evaluation of paper #Journal XXXX based on the findings exercise, few emotional sentiments were attracted during the review process. The study recommended editorial boards, journals, conferences, and publishing houses implement this approach

关键词： Sentiment analysis

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Comparative analysis of Independent Food Delivery Platforms: Empowering Food Movement Values

Comparative Analysis of Independent Food Delivery Platforms:...

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2025 CHI Conference on Human Factors in computing systems, CHI EA 2025

作者： Sultan, Siti Khadijah Binti Israni, Aarti Katzman, Jared Lee Dillahunt, Tawanna R. College of Literature Science and the Arts University of Michigan Ann ArborMI United States School of Information University of Michigan Ann ArborMI United States

ISBN: (纸本)9798400713958

Food insecurity remains a persistent issue in the United States, affecting approximately 10–15% of households, with marginalized communities disproportionately impacted. Food security focuses on ensuring consistent access to adequate and nutritious food. In contrast, the food movement, which encompasses principles of food justice and food sovereignty, addresses these disparities by advocating for equitable access to healthy food and empowering communities to shape their food systems. Our study investigates how independent food delivery platforms (indie) align with food movement values by selecting and analyzing a random sample of 50 US-based platforms out of a total pool of 489. Our findings reveal that while many platforms demonstrate strong alignment with food security principles, particularly in terms of accessibility and nutritional quality, significant gaps remain in anti-racist practices, community control, and sustainability efforts. We offer design recommendations and policy insights to help indie platforms promote equity, inclusivity, and sustainability, ultimately advancing more equitable food systems and addressing systemic challenges in food insecurity. © 2025 Copyright held by the owner/author(s).

关键词： Food security

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Curvature-based analysis of Network Connectivity in Private Backbone Infrastructures

Curvature-based Analysis of Network Connectivity in Private ...

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作者： Salamatian, Loqman Anderson, Scott Matthews, Joshua Barford, Paul Willinger, Walter Crovella, Mark Loqman Salamatian Columbia University New YorkNY United States University of Wisconsin-Madison MadisonWI United States NIKSUN Inc. PrincetonNJ United States Boston University BostonMA United States

The main premise of this work is that since large cloud providers can and do manipulate probe packets that traverse their privately owned and operated backbones, standard traceroute-based measurement techniques are no longer a reliable means for assessing network connectivity in large cloud provider infrastructures. In response to these developments, we present a new empirical approach for elucidating private connectivity in today's Internet. Our approach relies on using only "light-weight"(i.e., simple, easily-interpretable, and readily available) measurements, but requires applying a "heavy-weight"or advanced mathematical analysis. In particular, we describe a new method for assessing the characteristics of network path connectivity that is based on concepts from Riemannian geometry (i.e., Ricci curvature) and also relies on an array of carefully crafted visualizations (e.g., a novel manifold view of a network's delay space). We demonstrate our method by utilizing latency measurements from RIPE Atlas anchors and virtual machines running in data centers of three large cloud providers to (i) study different aspects of connectivity in their private backbones and (ii) show how our manifold-based view enables us to expose and visualize critical aspects of this connectivity over different geographic scales. © 2022 acm.

关键词： Visualization

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On Exploiting Patterns For Robust FPGA-based Multi-accelerator Edge computing systems

On Exploiting Patterns For Robust FPGA-based Multi-accelerat...

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25th Design, Automation and Test in Europe Conference and Exhibition (DATE)

作者： Razavi, Seyyed Ahmad Ting, Hsin-Yu Giyahchi, Thotiya Bozorgzadeh, Eli Univ Calif Irvine Irvine CA 92697 USA

ISBN: (纸本)9783981926361

Edge computing plays a key role in providing services for emerging compute-intensive applications while bringing computation close to end devices. FPGAs have been deployed to provide custom acceleration services due to their reconfigurability and support for multi-tenancy in sharing the computing resource. This paper explores an FPGA-based Multi-Accelerator Edge computing System, that serves various DNN applications from multiple end devices simultaneously. To dynamically maximize the responsiveness to end devices, we propose a system framework that exploits the characteristic of applications in patterns and employs a staggering module coupled with a mixed offline/online multi-queue scheduling method to alleviate resource contention, and uncertain delay caused by network delay variation. Our evaluation shows the framework can significantly improve responsiveness and robustness in serving multiple end devices.

关键词： Schedules Runtime Processor scheduling Time measurement Robustness Delays Time factors

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When to Collect Sensitive Category Data? Public Sector Considerations For Balancing Privacy and Freedom from Discrimination in Automated Decision systems 25

When to Collect Sensitive Category Data? Public Sector Consi...

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25th acm Conference on Computer-Supported Cooperative Work and Social computing, CSCW 2022

作者： Lenhart, Anna University of Maryland United States

ISBN: (纸本)9781450391900

Automated Decision systems (ADS) are being used to inform important decisions in government services. Concerns regarding discrimination in ADS have led to the rise of bias mitigation techniques, or data science practices that measure and adjust for disparities based on protected class data. These techniques often require demographic or sensitive category data to both measure discrimination in ADS and process data to mitigate the discriminatory bias. The collection of sensitive category data increases privacy concerns. This preliminary study includes nine semi-structured interviews with data practitioners working in government. The analysis explores what considerations data practitioners in the public sector make when determining best practices for sensitive category data collection and how they engage with the tradeoff between privacy and right to freedom from discrimination. Themes pertinent to social services emerged including the importance of accessibility, reasons for data minimization and the role of reporting structures and historical norms. © 2022 Owner/Author.

关键词： Data acquisition

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Deconstructing Depression Stigma: Integrating AI-driven Data Collection and analysis with Causal Knowledge Graphs 25

Deconstructing Depression Stigma: Integrating AI-driven Data...

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2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Meng, Han Zhang, Renwen Wang, Ganyi Yang, Yitian Qin, Peinuan Lee, Jungup Lee, Yi-Chieh School of Computing National University of Singapore Singapore Singapore Department of Communications and New Media National University of Singapore Singapore Singapore Department of Social Work National University of Singapore Singapore Singapore Computer Science National University of Singapore Singapore Singapore

ISBN: (纸本)9798400713941

Mental-illness stigma is a persistent social problem, hampering both treatment-seeking and recovery. Accordingly, there is a pressing need to understand it more clearly, but analyzing the relevant data is highly labor-intensive. Therefore, we designed a chatbot to engage participants in conversations;coded those conversations qualitatively with AI assistance;and, based on those coding results, built causal knowledge graphs to decode stigma. The results we obtained from 1,002 participants demonstrate that conversation with our chatbot can elicit rich information about people's attitudes toward depression, while our AI-assisted coding was strongly consistent with human-expert coding. Our novel approach combining large language models (LLMs) and causal knowledge graphs uncovered patterns in individual responses and illustrated the interrelationships of psychological constructs in the dataset as a whole. The paper also discusses these findings' implications for HCI researchers in developing digital interventions, decomposing human psychological constructs, and fostering inclusive attitudes. © 2025 Copyright held by the owner/author(s).

关键词： Emotional intelligence

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FlexiFly: Interfacing the Physical World with Foundation Models Empowered by Reconfigurable Drone systems 25

FlexiFly: Interfacing the Physical World with Foundation Mod...

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proceedings of the 23rd acm Conference on Embedded Networked Sensor systems

作者： Minghui Zhao Junxi Xia Kaiyuan Hou Yanchen Liu Stephen Xia Xiaofan Jiang Columbia University New York USA Northwestern University Evanston USA

ISBN: (纸本)9798400714795

Foundation models (FM) have shown immense human-like capabilities for generating digital media. However, foundation models that can freely sense, interact, and actuate the physical domain is far from being realized. This is due to 1) requiring dense deployments of sensors to fully cover and analyze large spaces, while 2) events often being localized to small areas, making it difficult for FMs to pinpoint relevant areas of interest relevant to the current task. We propose FlexiFly, a platform that enables FMs to "zoom in" and analyze relevant areas with higher granularity to better understand the physical environment and carry out tasks. FlexiFly accomplishes by introducing 1) a novel image segmentation technique that aids in identifying relevant locations and 2) a modular and reconfigurable sensing and actuation drone platform that FMs can actuate to "zoom in" with relevant sensors and actuators. We demonstrate through real smart home deployments that FlexiFly enables FMs and LLMs to complete diverse tasks up to 85% more successfully. FlexiFly is critical step towards FMs and LLMs that can naturally interface with the physical world.

关键词： embodied AI

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