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Enabling Virtual Priority in Data Center Congestion control 25

Enabling Virtual Priority in Data Center Congestion Control

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20th European conference on computer systems, EuroSys 2025, co-located 30th ACM international conference on Architectural Support for Programming Languages and Operating systems, ASPLOS 2025

作者： Zhang, Zhaochen Xue, Feiyang He, Keqiang Yin, Zhimeng Antichi, Gianni Gao, Jiaqi Wang, Yizhi Ning, Rui Nan, Haixin Zhang, Xu Cao, Peirui Wang, Xiaoliang Dou, Wanchun Chen, Guihai Tian, Chen Nanjing University China Shanghai Jiao Tong University China City University of Hong Kong Hong Kong Politecnico Milano Italy Queen Mary University of London United Kingdom

ISBN: (纸本)9798400711961

In data center networks, various types of traffic with strict performance requirements operate simultaneously, necessitating effective isolation and scheduling through priority queues. However, most switches support only around ten priority queues. Virtual priority can address this limitation by emulating multi-priority queues on a single physical queue, but existing solutions often require complex switch-level scheduling and hardware changes. Our key insight is that virtual priority can be achieved by carefully managing bandwidth contention in a physical queue, which is traditionally handled by congestion control (CC) algorithms. Hence, the virtual priority mechanism needs to be tightly coupled with CC. In this paper, we propose PrioPlus, a CC enhancement algorithm that can be integrated with existing congestion control schemes to enable virtual priority transmission. PrioPlus assigns specific delay ranges to different priority levels, ensuring that flows transmit only when the delay is within the assigned range, effectively meeting virtual priority requirements. Compared to Swift CC with physical priority queues, PrioPlus provides strict priority for high-priority flows without impacting performance sensibly. Meanwhile, it benefits low-priority flows from 25% to 41% as its priority-aware design enhances CC’s ability to fully utilize available bandwidth once higher-priority traffic completes. As a result, in coflow and model training scenarios, PrioPlus improves job completion times by 21% and 33%, respectively, compared to Swift with physical priority queues. © 2025 Copyright held by the owner/author(s).

关键词： Bandwidth

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MEPipe: Democratizing LLM Training with Memory-Efficient Slice-Level Pipeline Scheduling on Cost-Effective Accelerators 25

MEPipe: Democratizing LLM Training with Memory-Efficient Sli...

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20th European conference on computer systems, EuroSys 2025, co-located 30th ACM international conference on Architectural Support for Programming Languages and Operating systems, ASPLOS 2025

作者： Sun, Zhenbo Chen, Shengqi Wang, Yuanwei Sha, Jian Feng, Guanyu Chen, Wenguang Tsinghua University Beijing China Zhipu AI Beijing China

ISBN: (纸本)9798400711961

the training of large language models (LLMs) typically needs costly GPUs, such as NVIDIA A100 or H100. they possess substantial high-bandwidth on-chip memory and rapid interconnects like NVLinks. the exorbitant expenses associated with LLM training pose not just an economic challenge but also a societal one, as it restricts the ability to train LLMs from scratch to a selected few organizations. there is a significant interest in democratizing access to LLM training. this paper explores a potential solution by employing innovative parallel strategies on more affordable accelerators. Budget-friendly options like NVIDIA RTX 4090, while considerably less expensive and comparable in computational power to A100, are hindered by their limited memory capacity and reduced interconnect bandwidth, making the effective training of LLMs challenging. Conventional parallel strategies often result in high communication costs or excessive memory usage. Our paper introduces MEPipe, a novel approach that includes a slice-level scheduling method for sequence pipeline parallelism. this method minimizes memory consumption without incurring additional communication overhead. Besides, MEPipe utilizes fine-grained weight gradient computation to reduce idle time and mitigate imbalanced computation among slices. MEPipe has demonstrated up to 1.68× speedup (1.35× on average) on clusters equipped with 64 NVIDIA 4090 GPUs when training Llama models of varying sizes. 35% Model FLOPS Utilization (MFU) is achieved in training Llama 13B model, being 2.5× more cost-effective than A100 clusters. © 2025 Copyright held by the owner/author(s).

关键词： Budget control

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Integrating Crypto-Based Payment systems for Data Marketplaces: Enhancing Efficiency, Security, and User Autonomy 20th

Integrating Crypto-Based Payment Systems for Data Marketplac...

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20th international conference on Information systems Security

作者： Walunj, Vipul Rajaraman, Vasanth Dutta, Jyotirmoy Sharma, Abhay Ctr Data Publ Good CDPG Bengaluru India

ISBN: (纸本)9783031800191;9783031800207

Data exchanges, as Digital Public Infrastructures are poised to significantly contribute to the data driven economies across the world. Cities worldwide have leveraged Data Exchanges to enhance efficiency, improve citizen services, reduce costs, and generate new revenue streams. Beyond serving as a public good, data exchange platforms also establish a framework where stakeholders, such as data providers and consumers, can trade and monetize data. While financial payment gateways offer significant utility, they also present several challenges, including security issues and the reliance on third-party applications. these limitations must be addressed to ensure the efficacy and trustworthiness of the system. this work explores the integration of crypto-based payment systems into Web 2.0 applications, with a specific focus on their application within Data Marketplaces, the India Urban Data Exchange (IUDX), and Agricultural Data Exchange (ADeX) platforms. the integration of crypto payments offers significant technical advantages, including enhanced security, faster settlement times, lower transaction fees, and decentralized control over funds. this work discusses the technical aspects of crypto payment integration, such as crypto payment gateways, smart contracts, and wallet integration. Additionally, it highlights the specific benefits for Data Exchanges, including seamless data discovery and purchase flows, secure transactions, and innovative business models like tokenized data access and decentralized governance. Addressing regulatory challenges, scalability, and user adoption are identified as crucial steps for realizing the full potential of crypto payments. this integration proposes to create a secure, efficient, and user-friendly ecosystem that fosters innovation and promotes the growth of the data economy.

关键词： Blockchain Data Marketplace Ethereum Metamask

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Machine Learning Explainability as a Service: Service Description and Economics 20th

Machine Learning Explainability as a Service: Service Desc...

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20th international conference on the Economics of Grids, Clouds, systems, and Services, GECON 2024

作者： Fantozzi, Paolo Laura, Luigi Naldi, Maurizio Department of Law Economics Politics and Modern Languages at LUMSA University Via Pompeo Magno 28 Rome00192 Italy International Telematic University Uninettuno Rome Italy

ISBN: (纸本)9783031812255

Explainability is a growing concern in many machine learning applications. Machine learning platforms now typically provide explanations accompanying their model output. However, this may be considered as just a first step towards defining explainability as a service in itself, which would allow users to get more control over the kind of explainability technique they wish to employ. In this paper, we first provide a survey of the current offer of machine learning platforms, observing their pricing models and the explainability features they possibly offer. In order to progress towards Explainability-as-a-Service (XaaS), we propose to base its definition on the REST paradigm, considering three major examples of explainability techniques, relying on either feature scoring, surrogate linear models, or internal state observation. We also show that XaaS is dependent on machine-learning model provisioning, and the two services are linked by a one-way essential complement relationship, where ML provisioning plays the role of the essential component and XaaS is the complement option. We also suggest that vertical integration is the natural arrangement for companies offering either service, given their mutual relationship. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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the Sense of Agency in Assistive Robotics Using Shared Autonomy 25

The Sense of Agency in Assistive Robotics Using Shared Auton...

引用

ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Maggie A. Collier Rithika Narayan Henny Admoni Robotics Institute Carnegie Mellon University Pittsburgh PA USA

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

Sense of agency is one factor that influences peo-ple's preferences for robot assistance and a phenomenon from cognitive science that represents the experience of control over one's environment. However, in assistive robotics literature, we often see paradigms that optimize measures like task success and cognitive load, rather than sense of agency. In fact, prior work has found that participants sometimes express a preference for paradigms, such as direct teleoperation, which do not perform well with those other metrics but give more control to the user. In this work, we focus on a subset of assistance paradigms for manipulation called shared autonomy in which the system combines control signals from the user and the automated control. We run a study to evaluate sense of agency and show that higher robot autonomy during assistance leads to improved task performance but a decreased sense of agency, indicating a potential trade-off between task performance and sense of agency. From our findings, we discuss the relation between sense of agency and optimality, and we consider a proxy metric for a component of sense of agency which might enable us to build systems that monitor and maintain sense of agency in real time.

关键词： Human computer interaction Human-robot interaction Robot sensing systems Particle measurements control systems Cognitive load Real-time systems Cognitive science Trajectory Monitoring

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Exploring Extended Reality to Optimize Human-Cobot Interaction 25

Exploring Extended Reality to Optimize Human-Cobot Interacti...

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ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Javier Gonzalez-Sanchez Rafael Guerra-Silva Computer Science and Software Engineering California Polytechnic State University San Luis Obispo California USA Industrial Technology and Packaging California Polytechnic State University San Luis Obispo California USA

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

We explore the integration of extended reality technologies for advancing human-robot collaboration in manufacturing environments. Utilizing a commercial XR headset, the Meta Quest 3, we capture real-time hand and virtual object movements to intuitively control a Universal Robotics e-Series cobot. Our primary objective is to assess whether this interaction paradigm is intuitive for operators while effectively leveraging the cobot's capabilities. Data is streamed from the headset to a broker using MQTT. A local computing module subscribes to the data, translates coordinates into the robot's workspace, and generates control instructions for the cobot. Preliminary findings suggest that XR-based interaction can provide an immersive and efficient framework for human-robot collaboration. these results set the stage for further exploration of multi-user and multi-robot scenarios.

关键词： Headphones Hands Protocols Extended reality Tracking Robot kinematics Human-robot interaction Collaborative robots Real-time systems Motion capture

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HRIxD: End-Effector Specialised in Drumming for Performing Robots 25

HRIxD: End-Effector Specialised in Drumming for Performing R...

引用

ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Khaja Ahmed Shaik Eduardo Benitez Sandoval Shengyuan Xie Francisco Cruz School of Mechanical and Manufacturing Engineering University of New South Wales Sydney Australia School of Art and Design University of New South Wales Sydney Australia School of Computer Science and Engineering University of New South Wales Sydney Australia Escuela de Ingeniería Universidad Central de Chile Santiago Chile

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

Human-robot interaction encompasses various applications, from simple tasks to advanced complex functionalities. this research introduces a specialised robotics end effector specially modelled with auditory processing for drumming along-side humans. this system interprets auditory vocal input to generate precise and adaptive drumming patterns. Utilising precision motor control and real-time signal processing to replicate drumming with human-like characteristics with precision. this work demonstrates collaboration between performing arts and robotics, demonstrating the potential of intelligent systems to interact with human creativity in real-time. the specialised end effector utilises precise motor control with motor drivers and a belt mechanism to regulate the speed and direction of the drumstick, enabling rapid, high-speed strokes to strike the drum 4 to 5 times per second. By integrating audio perception with mechanical execution, this research advances the state of the art and establishes a new framework for incorporating robotics into the creative and artistic domain.

关键词： Motor drives Human-robot interaction Collaboration Signal processing Motors End effectors Real-time systems Intelligent systems Robots Creativity

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Hey Miro! Multimodal Interaction with an Animal-Like Robot Companion with Conversational Abilities 25

Hey Miro! Multimodal Interaction with an Animal-Like Robot C...

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ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Aung Htet Kinga Bernacka Omar Marei Jake N. Holden Tony J. Prescott Department of Computing Sheffield Hallam University Sheffield United Kingdom Department of Computer Science The University of Sheffield Sheffield United Kingdom

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

To make best use of large-language models (LLMs) in social robotics it is critical that verbal interaction capabilities are suitably integrated with robot perceptual and behavioral systems, including non-verbal and emotional signaling, such that the robot can use language in a grounded and context-appropriate way. this demonstration shows the integration of a LLM with the layered control architecture of the animal-like robot platform Miro-e alongside deep network models for perception and spoken language recognition and generation. this system is currently being developed as a prototype companion robot for research on robot-assisted therapy.

关键词： Bio-inspired robotics Human-robot interaction Prototypes Medical treatment Robots Context modeling

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ViewVR: Visual Feedback Modes to Achieve Quality of VR-Based Telemanipulation 25

ViewVR: Visual Feedback Modes to Achieve Quality of VR-Based...

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ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Artem Erkhov Artem Bazhenov Sergei Satsevich Danil Belov Farit Khabibullin Sergei Egorov Maxim Gromakov Miguel Altamirano Cabrera Dzmitry Tsetserukou Skoltech Moscow Russia

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

the paper focuses on an immersive teleoperation system that enhances operator's ability to actively perceive the robot's surroundings. A consumer-grade HTC Vive VR system was used to synchronize the operator's hand and head movements with a UR3 robot and a custom-built robotic head with two degrees of freedom (2-DoF). the system's usability, manipulation efficiency, and intuitiveness of control were evaluated in comparison with static head camera positioning across three distinct tasks. Code and other supplementary materials can be accessed by link: https://***/ErkhovArtemNiewVR.

关键词： Hands Visualization Codes Robot vision systems Human-robot interaction 2-DOF Cameras Synchronization Usability Robots

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LAMS: LLM-Driven Automatic Mode Switching for Assistive Teleoperation 25

LAMS: LLM-Driven Automatic Mode Switching for Assistive Tele...

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ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Yiran Tao Jehan Yang Dan Ding Zackory Erickson Carnegie Mellon University Pittsburgh PA USA University of Pittsburgh Pittsburgh PA USA

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

Teleoperating high degrees-of-freedom (DoF) robotic manipulators via low-DoF controllers like joysticks often requires frequent switching between control modes, where each mode maps controller movements to specific robot actions. Manually performing this frequent switching can make teleoperation cumbersome and inefficient. On the other hand, existing automatic mode-switching solutions, such as heuristic-based or learning-based methods, are often task-specific and lack generalizability. In this paper, we introduce LLM-Driven Automatic Mode Switching (LAMS), a novel approach that leverages Large Language Models (LLMs) to automatically switch control modes based on task context. Unlike existing methods, LAMS requires no prior task demonstrations and incrementally improves by integrating user-generated mode-switching examples. We validate LAMS through an ablation study and a user study with 10 participants on complex, long-horizon tasks, demonstrating that LAMS effectively reduces manual mode switches, is preferred over alternative methods, and improves performance over time. the project website with supplementary materials is at https://***/.

关键词： Learning systems Hands Large language models Human-robot interaction Switches Manuals control systems Manipulators

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