It has been a decade since the ACM/IEEE CS2013 Curriculum guidelines recommended that all CS students learn about parallel and distributedcomputing (PDC). But few textbooks for "core" CS courses especially ...
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ISBN:
(纸本)9798350364613;9798350364606
It has been a decade since the ACM/IEEE CS2013 Curriculum guidelines recommended that all CS students learn about parallel and distributedcomputing (PDC). But few textbooks for "core" CS courses especially first-year courses include coverage of PDC topics. To fill this gap, we have written free, online, beginner- and intermediate-level PDC textbooks, containing interactive C/C++ OpenMP, MPI, mpi4py, CUDA, and OpenACC code examples that students can run and modify directly in the browser. The books address a serious challenge to leaching PDC concepts, namely, easy access to the powerful hardware needed for observing patterns and scalability. This paper describes the content of these textbooks and the underlying infrastructure that make them possible. We believe the described textbooks fill a critical gap in PDC education and will be very useful for the community.
The proceedings contain 24 papers. The special focus in this conference is on parallel and distributed Processing Techniques. The topics include: parallel N-Body Performance Comparison: Julia, Rust, and More;REFT...
ISBN:
(纸本)9783031856372
The proceedings contain 24 papers. The special focus in this conference is on parallel and distributed Processing Techniques. The topics include: parallel N-Body Performance Comparison: Julia, Rust, and More;REFT: Resource-Efficient Federated Training Framework for Heterogeneous and Resource-Constrained Environments;An Efficient Data Provenance Collection Framework for HPC I/O Workloads;using Minicasts for Efficient Asynchronous Causal Unicast and Byzantine Tolerance;a Comparative Study of Two Matrix Multiplication Algorithms Under Current Hardware Architectures;Is Manual Code Optimization Still Required to Mitigate GPU Thread Divergence? Applying a Flattening Technique to Observe Performance;towards Automatic, Predictable and High-Performance parallel Code Generation;Attack Graph Generation on HPC Clusters;analyzing the Influence of File Formats on I/O Patterns in Deep Learning;inference of Cell–Cell Interactions Through Spatial Transcriptomics Data Using Graph Convolutional Neural Networks;natural Product-Like Compound Generation with Chemical Language Models;improved Early–Modern Japanese Printed Character Recognition Rate with Generated Characters;Improved Method for Similar Music Recommendation Using Spotify API;Reconfigurable Virtual Accelerator (ReVA) for Large-Scale Acceleration Circuits;Building Simulation Environment of Reconfigurable Virtual Accelerator (ReVA);vector Register Sharing Mechanism for High Performance Hardware Acceleration;Efficient Compute Resource Sharing of RISC-V Packed-SIMD Using Simultaneous Multi-threading;introducing Competitive Mechanism to Differential Evolution for Numerical Optimization;hyper-heuristic Differential Evolution with Novel Boundary Repair for Numerical Optimization;jump Like a Frog: Optimization of Renewable Energy Prediction in Smart Gird Based on Ultra Long Term Network;vision Transformer-Based Meta Loss Landscape Exploration with Actor-Critic Method;Fast Computation Method for Stopping Condition of Range Restricted
The proceedings contain 18 papers. The topics discussed include: decentralized machine learning for face recognition;a generic-based federated learning model for smart grid and renewable energy;design techniques for m...
ISBN:
(纸本)9798350341270
The proceedings contain 18 papers. The topics discussed include: decentralized machine learning for face recognition;a generic-based federated learning model for smart grid and renewable energy;design techniques for multi-core neural network accelerators on radiation-hardened FPGAs;a distributed automatic domain-specific multi-word term recognition architecture using spark ecosystem;finding minimum loss path in big networks;system architecture for real-time condition monitoring and anomaly detection on ships;investigating HPC job resource requests and job efficiency reporting;a new ad-hoc parallel file system for HPC environments based on the expand parallel file system;a performance prediction model for structured grid based applications in HPC environments;and local and global scheduling in mobile drop computing.
With the rapid development of power grid engineering, especially the rapid development of extra-high voltage engineering, the multi-source heterogeneous investigation data is on the increase, and the traditional inves...
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The urban waterlogging risk assessment has gradually become an effective measure for preventing waterlogging disasters. The accuracy of the risk assessment results rely on the assessment methods and data precision. Ta...
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The 2024 DEBS Grand Challenge addresses the topic of hard drive failure predictive maintenance, through analysis of data streams that contain SMART readings, reported by drives located in different groups of storage s...
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ISBN:
(纸本)9798400704437
The 2024 DEBS Grand Challenge addresses the topic of hard drive failure predictive maintenance, through analysis of data streams that contain SMART readings, reported by drives located in different groups of storage servers. This paper details the technical implementation of a solution that focuses primarily on parallelizing the data stream processing to obtain vertical scalability. When processing two queries concerning the addressed topic, and setting a threshold of a maximum 16 ms latency for responding, our solution obtained a throughput of about 57% out of the maximum possible when no processing is made on the data stream. We also describe an initial work-in-progress implementation of a distributed extension that relies on Apache Kafka, meant to further scale the throughput of the parallel solution and to address possible failure conditions of retrieving the input stream.
With the increasing penetration of inverter based renewable energy and distributed energy storages in nowadays' power systems, the system status and operation conditions are hard to track with traditional scheduli...
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ISBN:
(纸本)9798350378467;9798350367676
With the increasing penetration of inverter based renewable energy and distributed energy storages in nowadays' power systems, the system status and operation conditions are hard to track with traditional scheduling-based power system transient analysis approach, and more fast and efficient transient analysis methods are needed to address the power system dynamic security problems. This paper proposed a graph computing based power system transient analysis approach to achieve efficient and accurate solution for power system stability analysis. To overcome the data management challenges, a spatiotemporal graph model is constructed for efficient data management in power system transient analysis. Then, a graph computing based transient analysis method is proposed to leverage the parallelcomputing power to speed up the computational process. Finally, a power system transient analysis software is developed based on the graph computing based transient analysis method to validate the proposed approach.
Based on Large Language Models (LLMs), AI chatbots are widely utilized in people's daily life. However, deploying general LLMs directly into domain-specific intelligent chatbots poses challenges due to their lack ...
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This paper studies an artificial intelligence cloud platform for the 5G era, specifically involving the fields of artificial intelligence, cloud computing and big data, including heterogeneous distributed cloud platfo...
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For multiple distributed generation units (DG unit) parallel system, excessive fault current has adverse effects on the safe and stable operation of the utility grid. As a result, a fault current limitation control of...
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For multiple distributed generation units (DG unit) parallel system, excessive fault current has adverse effects on the safe and stable operation of the utility grid. As a result, a fault current limitation control of multiple DG units is developed in this paper to limit the fault current of related fault branch and ride through the associated fault conditions. The injection fault current amplitude and phase angle of each DG unit for grid-side converter are controlled through the point of common coupling (PCC) voltage support and fault current limitation to limit the total current amplitude at the corresponding fault location. The validity of the proposed control strategy has been verified by simulation and hardware-in-loop (HIL) experiment results. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
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