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proceedings of 2022 acm/IEEE 7th International Workshop on Extreme Scale Programming Models and Middleware, ESPM2 2022, Held in conjunction with SC 2022: The International Conference for High Performance computing, Networking, Storage and analysis

Proceedings of 2022 ACM/IEEE 7th International Workshop on E...

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7th acm/IEEE International Workshop on Extreme Scale Programming Models and Middleware, ESPM2 2022

ISBN: (纸本)9781665463393

The proceedings contain 3 papers. The topics discussed include: a selective nesting approach for the sparse multi-threaded Cholesky factorization;from merging frameworks to merging stars: experiences using HPX, KOKKOS and SIMD types;and broad performance measurement support for asynchronous multi-tasking with APEX.

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Revealing Influences of Socioeconomic Factors over Disease Outbreaks 22

Revealing Influences of Socioeconomic Factors over Disease O...

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4th acm SIGCAS/SIGCHI Conference on computing and Sustainable Societies (COMPASS)

作者： Hasan, S. Mahmudul Anisha, Alabi Mehzabin Adnin, Rudaiba Eliza, Ishrat Jahan Tarin, Ishika Afroz, Sadia Al Islam, A. B. M. Alim Bangladesh Univ Engn & Technol Dhaka Bangladesh Univ Cent Florida Orlando FL USA

ISBN: (纸本)9781450393478

The recent Covid-19 pandemic elucidates the need for a better disease outbreak analysis and surveillance system, which can harness state-of-the-art data mining and machine learning techniques to produce better forecasting. In this regard, understanding the correlation between disease outbreaks and socioeconomic factors should pave the way for such systems by providing useful indicators, which are yet to be explored in the literature to the best of our knowledge. Therefore, in this study, we accumulated data on 72 infectious diseases and their outbreaks all over the globe over a period of 23 years as well as corresponding different socioeconomic data. We, then, performed point-biserial and spearman correlation analysis over the collected data. Our analysis of the obtained correlations demonstrates that various disease outbreak attributes are positively and negatively correlated with different socioeconomic indicators. For example, indicators such as lifetime risk of maternal death, adolescent fertility rate, etc., are positively correlated, while indicators such as life expectancy at birth, measles immunization, etc., are negatively correlated, with disease outbreaks that affect the digestive organ system. In this paper, we find and summarize the correlations between 126 outbreak attributes derived from the characteristics of the 72 diseases in consideration and 192 socioeconomic factors which is a novel contribution to the field of disease outbreak analysis and prediction.

关键词： Socioeconomic factors Disease outbreaks Statistical analysis correlation

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analysis Towards Energy-Aware Image-based In Situ Visualization on the Fugaku 24

Analysis Towards Energy-Aware Image-based In Situ Visualizat...

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7th International Conference on High Performance computing in Asia-Pacific Region (HPC Asia)

作者： Tahir, Razil Nonaka, Jorji Iwata, Ken Matsushima, Taisei Sakamoto, Naohisa Bi, Chongke Nakao, Masahiro Murai, Hitoshi Univ Malaya Kuala Lumpur Malaysia RIKEN R CCS Kobe Hyogo Japan Kobe Univ Kobe Hyogo Japan Tianjin Univ Tianjin Peoples R China

ISBN: (纸本)9798400708893

Energy efficiency has become a serious concern when running applications on HPC systems. Although these systems were designed to mainly run simulation codes as fast as possible, due to the ever-increasing size of the simulation outputs, the in situ visualization has gained increasing attention. In situ visualization uses the same HPC system to execute a part or even the entire visualization processing, and there are currently a variety of tools and libraries, that facilitate domain scientists to integrate them with their simulation codes. Among different approaches, image- and video-based in situ visualization has been widely adopted as an effective approach for the subsequent offline visual analysis. In this approach, a large number of renderings are required at every visualization time step and can consume a considerable computational resource. Fugaku adopted PowerAPI which enables the users to set the power mode for their jobs. However, simulation and visualization codes may have different processing behaviors requiring different power settings for obtaining the most energy-efficient runnings. In this work, we tried to shed light on the energy efficiency of the visualization portion that was not considered before. We investigated the computational cost and energy consumption of some rendering techniques by using the PowerAPI and KVS (Kyoto Visualization System) on the Fugaku, and hope that the obtained findings will be useful for potential users looking to run in situ visualization on the Fugaku and other PowerAPI-enabled HPC systems.

关键词： In Situ Visualization Image-based analysis HPC system PowerAPI

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Collaborative Work in Malware analysis: Understanding the Roles and Challenges of Malware Analysts 25

Collaborative Work in Malware Analysis: Understanding the Ro...

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

作者： Yamagishi, Rei Fujii, Shota Yasuda, Shingo Sato, Takayuki Hasegawa, Ayako A. Hitachi Ltd. Tokyo Japan Nict Tokyo Japan

ISBN: (纸本)9798400713941

Malware analysis provides useful information for defending organizations against the growing number of cyberattacks. To leverage such information to enhance security, malware analysts are expected to collaborate with members of their own and other teams. However, there has been insufficient research into their actual collaboration and communication. Furthermore, given that challenges in their communication can lead to critical errors, it is imperative to understand and mitigate these challenges. We interviewed 15 malware analysts to explore their roles, collaborators, and communication means and challenges. We found that the roles within malware analysis teams are diverse and identified the roles and collaborations in which analysts leverage malware analysis knowledge effectively. We also identified several key communication challenges, including difficulties in aligning understanding in collaborative analysis and low motivation for information sharing. On the basis of our findings, we provide recommendations to address each communication challenge. © 2025 Copyright held by the owner/author(s).

关键词： communication challenges malware analysts security experts security operations

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About Engaging and Governing Strategies: A Thematic analysis of Dark Paterns in Social Networking Services 23

About Engaging and Governing Strategies: A Thematic Analysis...

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CHI conference on Human Factors in computing systems (CHI)

作者： Mildner, Thomas Savino, Gian-Luca Doyle, Philip R. Cowan, Benjamin R. Malaka, Rainer Univ Bremen Bremen Germany Univ St Gallen St Gallen Switzerland Univ Coll Dublin Dublin Ireland

ISBN: (纸本)9781450394215

Research in HCI has shown a growing interest in unethical design practices across numerous domains, often referred to as "dark patterns". There is, however, a gap in related literature regarding social networking services (SNSs). In this context, studies emphasise a lack of users' self-determination regarding control over personal data and time spent on SNSs. We collected over 16 hours of screen recordings from Facebook's, Instagram's, TikTok's, and Twitter's mobile applications to understand how dark patterns manifest in these SNSs. For this task, we turned towards HCI experts to mitigate possible difficulties of non-expert participants in recognising dark patterns, as prior studies have noticed. Supported by the recordings, two authors of this paper conducted a thematic analysis based on previously described taxonomies, manually classifying the recorded material while delivering two key findings: We observed which instances occur in SNSs and identified two strategies - engaging and governing - with five dark patterns undiscovered before.

关键词： SNS social media social networking services interface design dark patterns well-being ethical interfaces

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LaserShoes: Low-Cost Ground Surface Detection Using Laser Speckle Imaging 23

LaserShoes: Low-Cost Ground Surface Detection Using Laser Sp...

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CHI conference on Human Factors in computing systems (CHI)

作者： Yan, Zihan Lin, Yuxiaotong Wang, Guanyun Cai, Yu Cao, Peng Mi, Haipeng Zhang, Yang Zhejiang Univ Hangzhou Peoples R China MIT Media Lab Cambridge MA 02139 USA MIT CSAIL Cambridge MA 02139 USA Tsinghua Univ Beijing Peoples R China Univ Calif Los Angeles Los Angeles CA USA

ISBN: (纸本)9781450394215

Ground surfaces are often carefully designed and engineered with various textures to fit the functionalities of human environments and thus could contain rich context information for smart wearables. Ground surface detection could power a wide array of applications including activity recognition, mobile health, and context-aware computing, and potentially provide an additional channel of information for many existing kinesiology approaches such as gait analysis. To facilitate the detection of ground surfaces, we present LaserShoes, a texture-sensing-enabled system using laser speckle imaging that can be retrofitted to shoes. Our system captures videos of speckle patterns induced on ground surfaces and uses pre-processing to identify ideal images with clear speckle patterns collected when users feet are in contact with ground surfaces. We demonstrated our technique with a ResNet-18 model and achieved real-time inference. We conducted an evaluation in different conditions and demonstrated results that verified the feasibility.

关键词： Smart Shoes Laser Speckle Imaging Surface Identifcation Texture Identifcation Context Aware computing

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Exploiting 2.5D/3D Heterogeneous Integration for AI computing 24

Exploiting 2.5D/3D Heterogeneous Integration for AI Computin...

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29th Asia and South Pacific Design Automation Conference (ASP-DAC)

作者： Wang, Zhenyu Sun, Jingbo Goksoy, Alper Mandal, Sumit K. Liu, Yaotian Paragraph, Jae-Sun Seo Chakrabarti, Chaitali Ogras, Umit Y. Chhabria, Vidya Zhang, Jeff Cao, Yu Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ USA Univ Wisconsin Madison Dept Elect & Comp Engn Madison WI USA Indian Inst Sci Dept Comp Sci & Automat Bangalore Karnataka India Cornell Tech Dept Elect & Comp Engn New York NY USA Univ Minnesota Dept Elect & Comp Engn St Paul MN USA

ISBN: (纸本)9798350393545

The evolution of AI algorithms has not only revolutionized many application domains, but also posed tremendous challenges on the hardware platform. Advanced packaging technology today, such as 2.5D and 3D interconnection, provides a promising solution to meet the ever-increasing demands of bandwidth, data movement, and system scale in AI computing. This work presents HISIM, a modeling and benchmarking tool for chiplet-based heterogeneous integration. HISIM emphasizes the hierarchical interconnection that connects various chiplets through network-on-package. It further integrates technology roadmap, power/latency prediction, and thermal analysis together to support electro-thermal co-design. Leveraging HISIM with in-memory computing chiplets, we explore the advantages and limitations of 2.5D and 3D heterogenous integration on representative AI algorithms, such as DNNs, transformers, and graph neural networks.

关键词： Heterogeneous Integration 2.5D 3D Chiplet ML accelerators Performance analysis

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PaTAT: Human-AI Collaborative Qualitative Coding with Explainable Interactive Rule Synthesis 23

PaTAT: Human-AI Collaborative Qualitative Coding with Explai...

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CHI conference on Human Factors in computing systems (CHI)

作者： Gebreegziabher, Simret Araya Zhang, Zheng Tang, Xiaohang Meng, Yihao Glassman, Elena Li, Toby Jia-Jun Univ Notre Dame Notre Dame IN 46556 USA Univ Liverpool Liverpool Merseyside England Xi An Jiao Tong Univ Xian Peoples R China Harvard Univ Cambridge MA USA

ISBN: (纸本)9781450394215

Over the years, the task of AI-assisted data annotation has seen remarkable advancements. However, a specific type of annotation task, the qualitative coding performed during thematic analysis, has characteristics that make effective human-AI collaboration difficult. Informed by a formative study, we designed PaTAT, a new AI-enabled tool that uses an interactive program synthesis approach to learn flexible and expressive patterns over user-annotated codes in real-time as users annotate data. To accommodate the ambiguous, uncertain, and iterative nature of thematic analysis, the use of user-interpretable patterns allows users to understand and validate what the system has learned, make direct fixes, and easily revise, split, or merge previously annotated codes. This new approach also helps human users to learn data characteristics and form new theories in addition to facilitating the "learning" of the AI model. PaTAT's usefulness and effectiveness were evaluated in a lab user study.

关键词： data annotation human-AI collaboration qualitative analysis

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GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator Frontend with Graph Decoupling and Recoupling 24

GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator ...

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61st acm/IEEE Design Automation Conference, DAC 2024

作者： Xue, Runzhen Yan, Mingyu Han, Dengke Teng, Yihan Tang, Zhimin Ye, Xiaochun Fan, Dongrui State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Shanghai Innovation Center for Processor Technologies China

ISBN: (纸本)9798400706011

Heterogeneous Graph Neural Networks (HGNNs) have broadened the applicability of graph representation learning to heterogeneous graphs. However, the irregular memory access pattern of HGNNs leads to the buffer thrashing issue in HGNN *** this work, we identify an opportunity to address buffer thrashing in HGNN acceleration through an analysis of the topology of heterogeneous graphs. To harvest this opportunity, we propose a graph restructuring method and map it into a hardware frontend named GDR-HGNN. GDR-HGNN dynamically restructures the graph on the fly to enhance data locality for HGNN accelerators. Experimental results demonstrate that, with the assistance of GDR-HGNN, a leading HGNN accelerator achieves an average speedup of 14.6X and 1.78X compared to the state-of-the-art software framework running on A100 GPU and itself, respectively. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Graph neural networks

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Determination of Digital Spectra Parameters and their analysis 27

Determination of Digital Spectra Parameters and their Analys...

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27th International Conference on Soft computing and measurements, SCM 2024

作者： Vorotyntseva, Julija S. Suloeva, Elena S. Saint Petersburg Electrotechnical University 'LETI' Department of Information and Measurement Systems and Technology Saint Petersburg Russia

ISBN: (纸本)9798350363708

In this paper, a method for multidimensional optimization of digital spectra is discussed in order to determine the key parameters of spectral lines using software resources. Given that the line profile can be described by a Gaussian function, multidimensional optimization is performed. The outcome of the program is a set of values for the fundamental parameters of the spectral line, as well as the determination of standard error values. To accomplish this, a statistical technique is employed that allows for the calculation of standard errors based on generated random samples. Additionally, the paper examines various factors that may influence the accuracy of the results. © 2024 IEEE.

关键词： Random errors

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