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Decentralized in-order execution of a sequential task-based code for shared-memory architectures 36

Decentralized in-order execution of a sequential task-based ...

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36th IEEE International Parallel and Distributed Processing symposium (IEEE IPDPS)

作者： Castes, Charly Agullo, Emmanuel Aumage, Olivier Saillard, Emmanuelle Inria LaBRI Bordeaux France Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (纸本)9781665497473

the hardware complexity of modern machines makes the design of adequate programming models crucial for jointly ensuring performance, portability, and productivity in high-performance computing (HPC). Sequential task-based programming models paired with advanced runtime systems allow the programmer to write a sequential algorithm independently of the hardware architecture in a productive and portable manner, and let a third party software layer -the runtime system- deal with the burden of scheduling a correct, parallel execution of that algorithm to ensure performance. Many HPC algorithms have successfully been implemented following this paradigm, as a testimony of its effectiveness. Developing algorithms that specifically require fine-grained tasks along this model is still considered prohibitive, however, due to per-task management overhead [1], forcing the programmer to resort to a less abstract, and hence more complex "task+X" model. We thus investigate the possibility to offer a tailored execution model, trading dynamic mapping for efficiency by using a decentralized, conservative in-order execution of the task flow, while preserving the benefits of relying on the sequential taskbased programming model. We propose a formal specification of the execution model as well as a prototype implementation, which we assess on a shared-memory multicore architecture with several synthetic workloads. the results show that under the condition of a proper task mapping supplied by the programmer, the pressure on the runtime system is significantly reduced and the execution of fine-grained task flows is much more efficient.

关键词： Runtime Computational modeling Software algorithms computer architecture Programming Hardware Software

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CLEAR: An Efficient Traffic Sign Recognition Technique for Cyber-Physical Transportation Systems 15

CLEAR: An Efficient Traffic Sign Recognition Technique for C...

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IEEE/ACM 15th International Conference on Utility and Cloud computing (UCC) / 9th International Conference on Big Data computing, Applications and Technologies (BDCAT)

作者： Rai, Meghna Khosla, Bhawna Dhawan, Yash Kharotia, Himanshi Kumar, Neeraj Bandi, Ajay Thapar Inst Engn & Technol Dept Comp Sci & Engn Patiala Punjab India Northwest Missouri State Univ Maryville MO USA

ISBN: (纸本)9781665460873

In this modern era, the popularity of autonomous systems has increased manifold because they are replacing people in various jobs and are expected to become the backbone of modern society. Specifically, self-driving vehicles and robots are gaining popularity in a wide range of applications. However, traffic sign detection, a critical component of intelligent transportation systems, remains quite challenging since it needs to be done quickly, with high precision, and with high dependability. A fast, real-time, robust automatic traffic sign detection and recognition can support and relieve the driver and significantly increase driving safety and comfort. Out of many algorithms and frameworks available for traffic sign identification, i.e., object detection, one of the most popular ones is You Only Look Once (YOLO) since it provides accurate results with minimal background errors in most real-time processing tasks and has excellent learning capabilities. Motivated by this, this research article provides a novel framework, CLEAR, for traffic sign identification in adverse climate conditions using YOLOv5. We compare different models' speed, accuracy, and other metrics on a Traffic Sign Dataset obtained from the Open Image Dataset V6. Experimental results demonstrated that the proposed CLEAR model achieved the best performance with a Mean Average Precision of 0.73392 and Recall of 0.74194 compared to the existing schemes.

关键词： YOLO Traffic Signs Autonomous Vehicles Object Detection Image Classification computer Vision Deep Learning Real-Time Detection

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Integrating Machine Learning and Social Sensing in Smart City Digital Twin for Citizen Feedback 25

Integrating Machine Learning and Social Sensing in Smart Cit...

引用

25th IEEE International Conferences on high performance computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Kumi, Sandra Lomotey, Richard K. Deters, Ralph University of Saskatchewan Department of Computer Science SK Canada The Pennsylvania State University Information Sciences and Technology PA United States

ISBN: (纸本)9798350330014

Smart City Digital Twin (SCDT), a virtual representation of a physical city, is an emerging technology for optimizing urban services and enhancing urban planning and decision-making. the integration of Machine Learning (ML) and social sensing provides valuable insights into public feedback to policymakers and for informed decision-making and responsive urban governance. this study aims to explore the use of social media data and topic modeling algorithms in the context of SCDT to highlight the concerns of citizens in Saskatoon, Canada. In this work, we use the Uniform Manifold Approximation and Projection (UMAP) and K-means clustering algorithm in the BERTopic architecture to extract 30 topics from comments collected through the Saskatoon subreddit posts. the topics were then merged into 15 themes to discover the concerns. A pretrained transformer model, SiEBERT was used to determine the sentiments of the Reddit comments. the research findings highlighted concerns such as - unreliable public transit, high cost of living, long wait times in emergency rooms, shortage of family doctors, drug addiction, and lack of mental awareness. © 2023 IEEE.

关键词： Sentiment analysis

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A Study on Distributed Fault-Tolerant Service architectures for Critical Software Systems 15

A Study on Distributed Fault-Tolerant Service Architectures ...

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IEEE 15th International symposium on Applied Computational Intelligence and Informatics (SACI)

作者： Schuszter, Ioan Cristian Cioca, Marius Univ Petrosani Dept Comp & Elect Engn Petrosani Romania Lucian Blaga Univ Sibiu Dept Comp Sci Sibiu Romania

ISBN: (纸本)9781728195438

Reliable systems have been the subject of much research in the past %ears. with societal dependency on computer systems becoming more and more apparent. With more and more organizations embracing DevOps culture, there is a persistent need to understand how these systems are built and what their trade-offs are. this paper discusses and benchmarks the components of a modern fault tolerant and easily scalable system. designed to maximize up-time. the paper also describes the techniques used In the development of such a system. the system architecture described is implemented through several services deploy ed for a new critical single sign-on system deployed at CERN (the European Laboratory for Particle Physics). A case study of several critical components of the system is also performed, identifying several trade-offs. issues and future research directions.

关键词： Fault tolerance high energy physics Fault tolerant systems Systems architecture Europe Organizations computer architecture

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SURE: Secure Unikernels Make Serverless computing Rapid and Efficient 15

SURE: Secure Unikernels Make Serverless Computing Rapid and ...

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15th Annual ACM symposium on Cloud computing, SoCC 2024

作者： Parola, Federico Qi, Shixiong Narappa, Anvaya B. Ramakrishnan, K.K. Risso, Fulvio Politecnico di Torino Italy University of California Riverside United States University of Kentucky United States

ISBN: (纸本)9798400712869

Current serverless platforms introduce non-trivial overheads when chaining and orchestrating loosely-coupled microservices. Containerized function runtimes are also constrained by insufficient isolation and excessive startup time. this motivates our exploration of a more efficient, secure, and rapid serverless design. We describe SURE, a unikernel-based serverless framework for fast function startup, equipped with a high-performance and secure data plane. SURE's data plane supports distributed zero-copy communication via the seamless interaction between zero-copy protocol stack (Z-stack) and local shared memory processing. To establish a lightweight service mesh, SURE uses library-based sidecars instead of individual userspace sidecars. We leverage Intel's Memory Protection Keys (MPK) as a lightweight capability to ensure safe access to the shared memory data plane. It also isolates the Trusted computing Base (TCB) components in SURE's function runtime (e.g., library-based sidecar, scheduler, etc) from untrusted user code, while preserving the efficient single-address-space nature of unikernels. In particular, SURE prevents unintended privilege escalation involving MPK with an enhanced TCB. these combined efforts create a more secure and robust data plane while improving throughput up to 79X over Knative, a representative open-source serverless platform. © 2024 Owner/Author.

关键词： Trusted computing

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VAQEM: A Variational Approach to Quantum Error Mitigation 28

VAQEM: A Variational Approach to Quantum Error Mitigation

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28th Annual IEEE International symposium on high-performance computer architecture (HPCA)

作者： Ravi, Gokul Subramanian Smith, Kaitlin N. Gokhale, Pranav Mari, Andrea Earnest, Nathan Javadi-Abhari, Ali Chong, Frederic T. Univ Chicago Chicago IL 60637 USA Supertech Washington DC USA Unitary Fund Washington DC USA IBM TJ Watson Res Ctr IBM Quantum Yorktown Hts NY USA

ISBN: (纸本)9781665420273

Variational Quantum Algorithms (VQA) are one of the most promising candidates for near-term quantum advantage. Traditionally, these algorithms are parameterized by rotational gate angles whose values are tuned over iterative execution on quantum machines. the iterative tuning of these gate angle parameters make VQAs more robust to a quantum machine's noise profile. However, the effect of noise is still a significant detriment to VQA's target estimations on real quantum machines - they are far from ideal. thus, it is imperative to employ effective error mitigation strategies to improve the fidelity of these quantum algorithms on near-term machines. While existing error mitigation techniques built from theory do provide substantial gains, the disconnect between theory and real machine execution characteristics limit the scope of these improvements. thus, it is critical to optimize mitigation techniques to explicitly suit the target application as well as the noise characteristics of the target machine. We propose VAQEM, which dynamically tailors existing error mitigation techniques to the actual, dynamic noisy execution characteristics of VQAs on a target quantum machine. We do so by tuning specific features of these mitigation techniques similar to the traditional rotation angle parameters by targeting improvements towards a specific objective function which represents the VQA problem at hand. In this paper, we target two types of error mitigation techniques which are suited to idle times in quantum circuits: single qubit gate scheduling and the insertion of dynamical decoupling sequences. We gain substantial improvements to VQA objective measurements a mean of over 3x across a variety of VQA applications, run on IBM Quantum machines. More importantly, while we study two specific error mitigation techniques, the proposed variational approach is general and can be extended to many other error mitigation techniques whose specific configurations are hard to select a pri

关键词： quantum computing noisy intermediate-scale quantum variational quantum algorithms variational quantum eigensolver error mitigation dynamic decoupling gate scheduling

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Analyzing HPC Monitoring Data With a View Towards Efficient Resource Utilization

Analyzing HPC Monitoring Data With a View Towards Efficient ...

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International symposium on computer architecture and high performance computing (SBAC-PAD)

作者： Samuel Maloney Estela Suarez Norbert Eicker Filipe Guimarães Wolfgang Frings Jülich Supercomputing Centre Forschungszentrum Jülich Germany Institute of Computer Science University of Bonn Germany School of Mathematics and Natural Sciences University of Wuppertal Germany

ISBN: (数字)9798350356168

ISBN: (纸本)9798350356175

Compute nodes in modern HPC systems are growing in size and their hardware has become ever more diverse. Still, many HPC centers allocate the resources of full nodes exclusively to avoid contention, despite the associated risk of underutilization. this paper describes a thorough resource utilization study of CPU and GPU compute and memory capacity, and interconnect bandwidth on JUWELS, a mature leadership-class modular supercomputer, with the aim of identifying opportunities for improving utilization through advanced scheduling and node sharing. Separate analysis of CPU-only and GPU-accelerated nodes finds that CPU compute usage is already close to optimal for the CPU-only nodes, whereas there is plenty of scope for co-scheduling CPU-based jobs on GPU-accelerated nodes. Memory capacity and node-level interconnect bandwidth are sufficient to provision co-scheduled jobs. We analyze multiple one-month datasets to validate robustness of conclusions over time and compare with previous studies on other systems to establish generalizability of results.

关键词： Runtime high performance computing Graphics processing units Bandwidth computer architecture Supercomputers Robustness Hardware Resource management Monitoring

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Davinci Goes to Bebras: A Study on the Problem Solving Ability of GPT-3 15

Davinci Goes to Bebras: A Study on the Problem Solving Abili...

引用

15th International Conference on computer Supported Education, CSEDU 2023

作者： Bellettini, Carlo Lodi, Michael Lonati, Violetta Monga, Mattia Morpurgo, Anna Università degli Studi di Milano Milan Italy Alma Mater Studiorum Università di Bologna Bologna Italy Laboratorio Nazionale CINI ‘Informatica e Scuola’ Rome Italy

ISBN: (纸本)9789897586415

In this paper we study the problem-solving ability of the Large Language Model known as GPT-3 (codename DaVinci), by considering its performance in solving tasks proposed in the "Bebras International Challenge on Informatics and Computational thinking". In our experiment, GPT-3 was able to answer with a majority of correct answers about one third of the Bebras tasks we submitted to it. the linguistic fluency of GPT-3 is impressive and, at a first reading, its explanations sound coherent, on-topic and authoritative;however the answers it produced are in fact erratic and the explanations often questionable or plainly wrong. the tasks in which the system performs better are those that describe a procedure, asking to execute it on a specific instance of the problem. Tasks solvable with simple, one-step deductive reasoning are more likely to obtain better answers and explanations. Synthesis tasks, or tasks that require a more complex logical consistency get the most incorrect answers. Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Education computing

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Optimal Time and Energy-Aware Client Selection Algorithms for Federated Learning on Heterogeneous Resources

Optimal Time and Energy-Aware Client Selection Algorithms fo...

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International symposium on computer architecture and high performance computing (SBAC-PAD)

作者： Alan L. Nunes Cristina Boeres Lúcia M. A. Drummond Laércio L. Pilla Fluminense Federal University Niterói Brazil University of Bordeaux CNRS Bordeaux INP Inria LaBRI Talence France

ISBN: (数字)9798350356168

ISBN: (纸本)9798350356175

Federated Learning systems allow training machine learning models distributed across multiple clients, each one using private local data. Iteratively, the clients send their training contributions to a server, which performs a merge to produce an enhanced global model. Due to resource and data heterogeneity, client selection is crucial to optimize the system efficiency and improve the global model generalization. Selecting more clients is likely to increase the overall energy consumption, while a small number of clients may decline the performance of the trained model or require longer training time. We propose two time- and energy-aware client selection algorithms, MEC and ECMTC, which are proven regarding their optimality and evaluated against state-of-the-art algorithms on an extensive series of experiments in both simulation and HPC platform scenarios. the results indicate the benefits of jointly optimizing the time and energy consumption metrics using our proposals.

关键词： Training Measurement Energy consumption Federated learning high performance computing Distributed databases computer architecture Data models Servers Proposals

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Leveraging Large Vision Models for Terrain Classification in HiRISE Mars Orbital Images

Leveraging Large Vision Models for Terrain Classification in...

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International Conference on computing and Networking Technology (ICCNT)

作者： J. Mary Hanna Priyadharshini C Chrisil David M Jaikrish M Aswin Computer Science Engineering(Artificial Intelligence And Machine Learning) VEL TECH HIGH TECH Dr. RANGARAJAN Dr. SAKUNTHALA ENGINEERING COLLEGE Chennai Tamil Nadu India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

In this paper, we present a comprehensive benchmarking and comparative analysis of state-of-the-art Vision Transformer (ViT) architectures, including ViT, BEiT, DeiT, LeViT, and SwinV2, for the classification of HiRISE landmark images. Our study aims to evaluate the performance of these pre-trained models in categorizing images into seven predefined classes, with an additional “unknown” class to account for images that do not fit into these categories. By leveraging the advanced capabilities of transformer-based models, we seek to enhance the accuracy and efficiency of classifying high-resolution satellite imagery, a critical task in remote sensing and planetary exploration.

关键词： Training Mars computer vision Accuracy Computational modeling computer architecture Transformers Computational efficiency Time complexity Image classification

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