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检索条件"任意字段=Conference on High Performance Computer Modernization Program"

共 10259 条记录，以下是141-150 订阅

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EGCR: an Enhanced Graph Neural Network for Cache Replacement 3

EGCR: an Enhanced Graph Neural Network for Cache Replacement

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3rd International conference on high performance Computing and Communication Engineering, HPCCE 2023

作者： Zhu, Kexin Jiang, Weifeng School of Computer Science and Enginering University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (数字)9781510674653

ISBN: (纸本)9781510674646

Caching is a fundamental strategy in computer systems to minimize latency and enhance performance, crucial for achieving optimal program execution speed. The Cache Hit Ratio is a key metric, emphasizing the critical role of cache hits, which are significantly faster than misses. The challenge lies in efficient cache replacement strategies, determining which cache line to evict when introducing a new line. Current policies, often based on heuristics for common access patterns, fall short in diverse scenarios. In response, this paper introduces EGCR (Enhanced Graph Neural Network for Cache Replacement), a pioneering model integrating Graph Neural Networks (GNN) to intelligently adapt to varying workloads and enhance the Cache Hit Ratio. EGCR introduces a graph-based representation for cache-related data, dynamically learning to respond effectively to intricate access patterns. In empirical evaluations, EGCR consistently outperforms the current state of the art, demonstrating a remarkable 36% improvement in cache hit rates across 13 memory-intensive SPEC applications. This positions EGCR as a promising solution, effectively bridging traditional heuristics and the potential of GNNs for optimized Cache Hit Ratios in dynamic computing environments. © 2024 SPIE.

关键词： Graph neural networks

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Towards Fault Tolerance and Resilience in the Sequential Codelet Model 10th

Towards Fault Tolerance and Resilience in the Sequential Cod...

引用

10th Latin American conference on high performance Computing (CARLA)

作者： Perdomo, Diego A. Roa Guaitero, Rafael A. Herrera Fox, Dawson Yviquel, Herve Raskar, Siddhisanket Li, Xiaoming Diaz, Jose M. Monsalve Argonne Natl Lab Argonne IL 60439 USA Univ Delaware Newark DE 19716 USA Univ Estadual Campinas Campinas Brazil

ISBN: (纸本)9783031521850;9783031521867

Failure or disruption in high-performance computer Systems can have a significant impact on human life, the environment, or the economy. Critical applications refer to software systems or functionalities that are essential for the safety, security, or continuity of critical infrastructure, services, or operations. Considering that semiconductor devices are susceptible to errors and failure, providing error detection and correction mechanisms in such systems is imperative. However, the main challenge for achieving fault tolerance and resiliency is compartmentalizing the causes and the consequences of error, in both hardware and software. Moreover, today's extreme-scale parallel HPC systems necessitate fundamentally non-deterministic executions, making compartmentalization an even bigger challenge. To address these challenges, this paper proposes leveraging the Sequential Codelet Model (SCM), which facilitates parallel execution of programs expressed sequentially and hierarchically. We propose to exploit SCM's encapsulation of semantics and data to compartmentalize faults transparently and efficiently. We present multiple techniques that can be implemented in the Sequential Codelet Model to include fault-tolerant and resiliency mechanisms. We implement already-known solutions by extending a functional emulator for the Sequential Codelet Model.

关键词： Codelet Model program Execution Model Fault Tolerance Resiliency

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Analyzing the Impacts of Dynamic Game Balancing in a Survival Roguelike Chess Game

Analyzing the Impacts of Dynamic Game Balancing in a Surviva...

引用

2025 International conference on Advancement in Data Science, E-learning and Information System, ICADEIS 2025

作者： Mario Arifin, Yulyani Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798331513320

This research investigates the novel application of Dynamic Game Balancing (DGB) techniques in the context of a hybrid chess-survival roguelike game, a unique combination of genres not widely explored in previous studies. The study addresses two primary research questions: the identification of suitable DGB techniques for these genres and the enhancement of user experience through DGB. A game prototype was developed using Unity, where players control a chess knight in a turn-based system, facing increasingly challenging enemy pieces. The DGB system dynamically adjusts the game's difficulty based on player performance, utilizing various inputs such as damage received or dealt, health points, powerup usage, and decision speed. Preliminary results from 14 beta-testers show overall positive feedback, with players reporting higher engagement and enjoyment due to the seamless difficulty adjustments, as reflected by the high mean scores from surveys like the User Experience Questionnaire (UEQ). This research fills a gap in the literature by demonstrating the feasibility and benefits of integrating DGB in a chess-survival roguelike setting. These findings highlight the potential for DGB to significantly improve player experience in hybrid game genres, suggesting that its application can create more adaptive and immersive gaming environments in various other genres as well. © 2025 IEEE.

关键词： Game design

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Synthetic Dataset Generation Methods for computer Vision Application 6

Synthetic Dataset Generation Methods for Computer Vision App...

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2024 International conference on Smart Systems and Technologies

作者： Arlovic, Matej Damjanovic, Davor Hrzic, Franko Balen, Josip JJ Strossmayer Univ Osijek Fac Elect Engn Comp Sci & Informat Technol Osijek Croatia Harvard Med Sch Boston Childrens Hosp Dept Orthopaed Surg & Sports Med Boston MA 02115 USA Univ Rijeka Ctr Artificial Intelligence & Cybersecur Rijeka Croatia

ISBN: (纸本)9798350386394;9798350386400

Deep learning models rely on datasets for training, validation, and testing. They require diverse and representative datasets to represent real-world scenarios effectively. The performance of deep learning models is heavily influenced by data quality and quantity. high-quality and diverse datasets are essential for developing robust and accurate models. However, acquiring data for datasets can pose challenges since the time and complexity associated with manual data labeling. In order to address this problem, synthetic data generated by 3D software like Unreal Engine 5, Blender, and NVIDIA Omniverse, as well as AI-generated images in Stable Diffusion and DALL-E 3, are employed. Synthetic data facilitate the rapid and straightforward generation of aggregated datasets that accurately represent realworld scenarios. The impact of synthetic data on the performance and quality of deep learning model outcomes requires further investigation.

关键词： 3D applications computer vision deep learning diffusion models synthetic data

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PEbfs: Implement high-performance Breadth-First Search on PEZY-SC3s 24th

PEbfs: Implement High-Performance Breadth-First Search on P...

引用

24th International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Guo, Weihao Wang, Qinglin Liu, Xiaodong Peng, Muchun Yang, Shun Liang, Yaling Shi, Yongzhen Cao, Ligang Liu, Jie Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology Changsha410073 China Engineering Research Center for National Fundamental Software National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819615506

The breadth-first search (BFS) algorithm is a fundamental algorithm in graph theory, and it’s parallelization can significantly improve performance. Therefore, there have been numerous efforts to leverage the powerful parallel computing capabilities of hardware like GPGPU to implement high-performance BFS algorithms. However, the energy efficiency is relatively low due to the high power consumption of the platforms on which the algorithm is adapted to. To deal with these challenges, this paper introduces PEbfs that is a high-performance BFS algorithm based on the PEZY-SC3s efficient processor. We integrated three search algorithms, two algorithm optimization strategies, and a directional optimization scheme into PEbfs. Through multiple evaluations of the performance of PEbfs on the public SNAP dataset, the results demonstrate that the average energy efficiency ratio of PEbfs is higher than that of Enterprise and Tigr, the two most advanced implementations on Nvidia’s GPGPU: It achieves 3.08× the average energy efficiency ratio of Enterprise and 4.53× that of Tigr. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

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Large-Scale Simulation of Structural Dynamics Computing on GPU Clusters 23

Large-Scale Simulation of Structural Dynamics Computing on G...

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2023 International conference for high performance Computing, Networking, Storage and Analysis, SC 2023

作者： Shi, Yumeng Nie, Ningming Wang, Jue Lin, Kehao Zhou, Chunbao Li, Shigang Yao, Kehan Li, Shunde Feng, Yangde Zeng, Yan Liu, Fang Wang, Yangang Gao, Yue University of Chinese Academy of Sciences Computer Network Information Center Chinese Academy of Sciences Beijing China Hangzhou Dianzi University Hangzhou China School of Computer Science Beijing University of Posts and Telecommunications Beijing China China Institute of Atomic Energy Beijing China

ISBN: (纸本)9798400701092

Structural dynamics simulation plays an important role in research on reactor design and complex engineering. The Hybrid Total Finite Element Tearing and Interconnecting (HTFETI) method combined with Newmark method is an efficient way to solve large-scale structural dynamics problems. However, the sparse direct solver and the load imbalance caused by inconsistent density models are two critical issues limiting the performance and the scalability of structural dynamics computing. For the former, we propose an efficient variable-size batched method to accelerate SpMV on GPUs. For the latter, we establish an online performance prediction model, based on which we then design a novel inter-cluster subdomain fine-tuning algorithm to balance the workload of HTFETI parallel computing. We are the first to achieve the high-fidelity structural dynamics simulation of China Experimental Fast Reactor core assembly with up to 53.4 billion grids. The weak and strong scalability efficiencies reach 91.77% and 86.13% on 12,800 GPUs, respectively. © 2023 Owner/Author(s).

关键词： Structural dynamics

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Edge-IoTDistilBERT: Fine-Tuning DistilBERT for Multi-Class Classification of Network Packet Attacks

Edge-IoTDistilBERT: Fine-Tuning DistilBERT for Multi-Class C...

引用

2025 International conference on Advancement in Data Science, E-learning and Information System, ICADEIS 2025

作者： Setiawan, Valentino Soewito, Benfano Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331513320

This exponential proliferation of IoT devices is creating an ever-growing demand for efficient cybersecurity solutions in resource-constrained environments. In this study, we propose Edge-IoTDistilBERT, a fine-tuned DistilBERT model, intended for the multi-class classification of network packet attacks within IoT ecosystems. Our proposed model was trained on the Edge-IIoT dataset, representative of all traffic classes and attack variants with high accuracy of up to 99.99%, outperforming state-of-the-art solutions. The new preprocessing pipeline of PCAP to text would transform the network traffic to a textual form allowing the model to learn the pattern in the dataset and making it able to generalize its content. Our fine-tuned model show a robust result on imbalanced dataset with two diffrent splits namely 80-20 and 70-30. The result shown by Edge-IoTDistilBERT place this model as a feasible effective cybersecurity solution for IoT networks, offering a good trade-off between high performance and resource constraints linked to edge devices. © 2025 IEEE.

关键词： Cyber attacks

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How Mental Health program Moderate Remote Audit, computer Literacy and CAATs Impact on AuditorWork performance during Pandemic Covid-19 22

How Mental Health Program Moderate Remote Audit, Computer Li...

引用

6th International conference on E-Commerce, E-Business and E-Government (ICEEG)

作者： Handoko, Bambang Leo Thomas, Gen Norman Bina Nusantara Univ Fac Econ & Commun Accounting Dept Jakarta 11480 Indonesia

ISBN: (纸本)9781450396523

The stress level of working in a public accounting firm is no longer a secret, this happens all over the world, including in Indonesia. The stress level is very high, especially during peak season. Many public accounting firm employees, namely auditors who are not strong and resign, so that the turnover rate is very high. This is still exacerbated by the pandemic of Covid-19, which requires the auditor's work pace to change. What previously worked onsite became online. The use of remote auditing and computer assisted audit techniques is being increased. However, without adequate computer literacy, of course this will make it more difficult for auditors and become a new cause of stress. Researchers are interested in examining the use of mental health programs as moderating variables to moderate the effect of remote audit, computer literacy and computer assisted audit techniques on auditor work performance during the Covid-19 pandemic. Our research is a quantitative research, the data that is processed is primary data. The survey results from the object of our research, namely the auditor at a public accounting firm in Jakarta. Processing the data using statistical software and also the Sobel test to test the moderating effect. We get the results that remote audit, computer literacy and computer assisted audit techniques have a significant effect on auditor work performance during Covid-19 and mental health programs moderate the effect of these three variables.

关键词： 64Tcomputer Literacy Mental Health CAATs Work performance

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ANT-MOC: Scalable Neutral Particle Transport Using 3D Method of Characteristics on Multi-GPU Systems 23

ANT-MOC: Scalable Neutral Particle Transport Using 3D Method...

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2023 International conference for high performance Computing, Networking, Storage and Analysis, SC 2023

作者： Li, Shunde Wang, Zongguo Bu, Lingkun Wang, Jue Xin, Zhikuang Li, Shigang Wang, Yangang Feng, Yangde Shi, Peng Hu, Yun Chi, Xuebin Computer Network Information Center Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China National Center for Materials Service Safety University of Science and Technology Beijing Beijing China School of Computer Science Beijing University of Posts and Telecommunications Beijing China China Institute of Atomic Energy Beijing China

ISBN: (纸本)9798400701092

The Method Of Characteristic (MOC) to solve the Neutron Transport Equation (NTE) is the core of full-core simulation for reactors. high resolution is enabled by discretizing the NTE through massive tracks to traverse the 3D reactor geometry. However, the 3D full-core simulation is prohibitively expensive because of the high memory consumption and the severe load imbalance. To deal with these challenges, we develop ANT-MOC1. Specifically, we build a performance model for memory footprint, computation and communication, based on which a track management strategy is proposed to overcome the resolution bottlenecks caused by limited GPU memory. Furthermore, we implement a novel multi-level load mapping strategy to ensure load balancing among nodes, GPUs, and CUs. ANT-MOC enables a 3D full-core reactor simulation with 100 billion tracks on 16,000 GPUs, with 70.69% and 89.38% parallel efficiency for strong scalability and weak scalability, respectively. © 2023 Owner/Author(s).

关键词： Scalability

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computer Vision and AI Techniques for Enhancing performance at FIRST Robotics Competitions 14

Computer Vision and AI Techniques for Enhancing Performance ...

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14th IEEE Integrated STEM Education conference, ISEC 2024

作者： Tewolde, Joshua Tewolde, John Tewolde, Girma Frc Team #1506 Grand Blanc High School Grand BlancMI United States Kettering Unversity Ece Department FlintMI United States

ISBN: (纸本)9798350352801

FIRST is a global robotics program focused on generating opportunities for youth to immerse themselves in STEM through engaging annual games that teams design robots to compete in [1]. As technology advances, the various challenges introduced in the yearly robotics competitions continue to push teams to take advantage of hardware and software tools that are becoming mainstream in industry. The primary focus of this poster is to present two computer vision and AI tools that have been recently introduced in the FTC (First Tech Challenge, middle school age) and FRC (First Robotics Competition, high school age) competitions. Both TensorFlow software (FTC), and the Limelight camera (and associated software). have been incorporated into the FTC and FRC competitions;called 'Power Play' and 'Crescendo' respectively. In this paper, we will discuss these vision and AI tools used as well as the possible implementation and application of them for other uses. © 2024 IEEE.

关键词： computer aided software engineering

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