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检索条件"主题词=batch data processing"

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A GPU Implementation of the Analog Ensemble Method 33

A GPU Implementation of the Analog Ensemble Method

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33rd Euromicro International Conference on Parallel, Distributed, and Network-Based processing, PDP 2025

作者： Crico, Ruben Charles, Ines Balsa, Carlos Rufino, Jose Université de Toulouse - INP - ENSEEIHT Toulouse France Bragança5300-253 Portugal

ISBN: (纸本)9798331524937

The Analog Ensemble (AnEn) method can be used to reconstruct incomplete time series using correlated series. Since the AnEn method may use data including several variables through long periods of time, its storage and computational cost may be substantial, slowing down reconstructions. This paper presents a full GPU implementation of the AnEn method, based on PyCUDA, that leads to a significant a cceleration of its execution. The implementation resorts to several techniques that seek to minimize the consumption of GPU global memory in the various steps of the AnEn algorithm, thus making room for larger input datasets. This is further reinforced by the use of batch processing as a way to automatically adapt the datasets size to the GPU memory available. The GPU implementation was tested on a meteorological dataset spanning 10 years, exhibiting a 30-fold speedup in the reconstruction time against a comparable CPUbased multicore version executed with up to 48 cores. The impact on the reconstruction error of changes on several important parameters of the implementation was also assessed. © 2025 IEEE.

关键词： batch data processing

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Design and implementation of batch file intelligent summary assistant based on AIGC+RPA 24

Design and implementation of batch file intelligent summary ...

引用

8th International Conference on Electronic Information Technology and Computer Engineering, EITCE 2024

作者： Lin, Meirong Information Engineering College Hainan Vocational University of Science and Technology Hainan Haikou China

ISBN: (纸本)9798400710094

This paper presents the design and implementation of a batch file intelligent summary assistant based on AIGC and RPA. This system aims to solve the problem of large human resource consumption and low efficiency in batch document processing. By combining the ability of text summary generation of AIGC technology and efficient document processing ability of RPA technology, it can realize the rapid and accurate summary of a large number of documents. This project describes in detail the overall process design of the system, the specific implementation methods of AIGC module and RPA module, summarizes the research results, and puts forward the future research direction. This study provides new ideas and technical support for improving the efficiency of batch file processing. © 2024 Copyright held by the owner/author(s).

关键词： batch data processing

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Fair-Sharing Simulator for batch Computing Systems 15th

Fair-Sharing Simulator for Batch Computing Systems

引用

15th International Conference on Parallel processing and Applied Mathematics, PPAM 2024

作者： Klusáček, Dalibor CESNET Prague Czech Republic

ISBN: (纸本)9783031856990

Scientific computing centers or private (in-house) cloud data centers do not rely on the standard pay-as-you-go business model which is common in commercial clouds to allocate resources. Instead, the system is typically shared by a set of selected users, and the administrator’s job is to ensure that resources are shared fairly given the existing policies of that organization. One common approach, especially in batch systems, is to deploy a fairshare-based prioritization in the scheduler, where a prioritization mechanism balances resource consumption so that individual users get the right shares of resources over time. In this paper, we present a tool developed to simulate the fairshare setting in a batch system. Using a set of experiments, we demonstrate the utility of this tool in tuning fairshare settings in a standard HPC/HTC scheduler and present the impact of often-overlooked additional options for modifying the basic fairshare settings. All the findings in this paper are based on our real-world experience of running and optimizing a distributed national computing infrastructure in the Czech Republic. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： batch data processing

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Separation Is for Better Reunion: data Lake Storage at Huawei 40

Separation Is for Better Reunion: Data Lake Storage at Huawe...

引用

40th IEEE International Conference on data Engineering, ICDE 2024

作者： Tang, Xin Chai, Chengliang Zhao, Dawei Ma, Haohai Zheng, Yong Fan, Zhenyong Wu, Xin Zhang, Jiaquan Zhang, Rui Li, Duanshun He, Yi Huang, Keji Meng, Guangbin Wang, Yidong Zhou, Yuefeng Tao, Tao Jian, Lirong Shu, Jiwu Wang, Yuping Yuan, Ye Wang, Guoren Li, Guoliang Beijing Institute of Technology Huawei China Mobile Communications Hashdata Tsinghua University China

ISBN: (纸本)9798350317152

Huawei collaborates with some Chinese large busi-ness companies to store and process exabytes of nationwide operational data in data lake storage to provide business insights. Specifically, our customers will ask to store and process massive log message data to support their real-time and decision-making applications. Thus, we need computation and storage components in the analytic platform to process and store these data cost-efficiently. To meet these user requirements, we have designed a storage system in data lake, StreamLake, which introduces a novel design to serve log message streaming and batch data processing in distributed storage, with high scalability, efficiency, reliability and low cost. Specifically, we introduce a stream (storage) object as a storage abstraction for message streaming data to achieve the storage-disaggregated architecture with high scalability and reliability. Moreover, we utilize the erasure coding and tiered storage to save the storage cost, and furthermore, the stream object can be automatically converted to a table object such that cost-effective stream and batch data processing can be achieved. For tabular data, we implement the lakehouse functionality to support ACID via the table object, with a metadata acceleration to improve the efficiency of data access between the compute and storage engines. Also, we design a LakeBrain optimizer at the storage side to optimize the query performance and resource utilization under the storage-disaggregated architecture. Finally, we have also deployed StreamLake in China Mobile, the world's largest mobile network operator to serve over 20PB production data, and the results demonstrate improvements of 30% to 4x in terms of query performance and over 37% in terms of cost saving. © 2024 IEEE.

关键词： batch data processing

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Identification of batch reactor process using Extreme Learning Machine based Hammerstein and Hammerstein-Wiener Models

Identification of batch reactor process using Extreme Learni...

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2024 International Conference on Thermofluids and Manufacturing Science, ICTMS 2024

作者： Balakrishnan, Murugan Rajendran, Vinodha Prajwal, Shettigar J. Indiran, Thirunavukkarasu Department of Electronics and Instrumentation Engineering Annamalai University Annamalai Nagar Tamilnadu India Department of Instrumentation and Control Engineering Institution Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India

This paper concentrates on system identification using neural networks, specifically avoiding the need for gradient calculation. In our proposed approach, the parameters of the nonlinear static blocks in both Hammerstein and Hammerstein-Wiener models are represented as Single Hidden Layer Feed forward Networks (SLFNs). The identification of both nonlinear and linear parameters is accomplished through the application of Extreme Learning Machine (ELM). In ELM, the hidden layer weights and biases are generated randomly and remain fixed, whereas the output weights are computed using linear regression. The training process involves a forward pass, in which the hidden layer activations are computed, followed by the computation of the output weights and backward pass is exempted, where iterative optimization based weight updates are done. To show the efficacy of the ELM based block oriented models, intense nonlinear batch reactor process is identified with its input output data. One can take away the best model fit for controller design from this ELM based modelling. © Published under licence by IOP Publishing Ltd.

关键词： batch data processing

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PARSIR: a Package for Effective Parallel Discrete Event Simulation on Multi-processor Machines 28

PARSIR: a Package for Effective Parallel Discrete Event Simu...

引用

28th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2024

作者： Quaglia, Francesco DICII - University of Rome Tor Vergata Italy

ISBN: (纸本)9798331527211

In this article we present PARSIR (PARallel SImulation Runner), a package that enables the effective exploitation of shared-memory multi-processor machines for running discrete event simulation models. PARSIR is a compile/run-time environment for discrete event simulation models developed with the C programming language. The architecture of PARSIR has been designed in order to keep low the amount of CPU-cycles required for running models. This is achieved via the combination of a set of techniques like: 1) causally consistent batch-processing of simulation events at an individual simulation object for caching effectiveness;2) high likelihood of disjoint access parallelism;3) the favoring of memory accesses on local NUMA (Non-Uniform-Memory-Access) nodes in the architecture, while still enabling well balanced workload distribution via work-stealing from remote nodes;4) the use of RMW (Read-Modify-Write) machine instructions for fast access to simulation engine data required by the worker threads for managing the concurrent simulation objects and distributing the workload. Furthermore, any architectural solution embedded in the PARSIR engine is fully transparent to the application level code implementing the simulation model. We also provide experimental results showing the effectiveness of PARSIR when running the reference PHOLD benchmark on a NUMA shared-memory multi-processor machine equipped with 40 CPUs. © 2024 IEEE.

关键词： batch data processing

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Is It Time To Put Cold Starts In The Deep Freeze? 15

Is It Time To Put Cold Starts In The Deep Freeze?

引用

15th Annual ACM Symposium on Cloud Computing, SoCC 2024

作者： Segarra, Carlos Durev, Ivan Pietzuch, Peter Imperial College London United Kingdom

ISBN: (纸本)9798400712869

Cold-start times have been the "end-all, be-all"metric for research in serverless cloud computing over the past decade. Reducing the impact of cold starts matters, because they can be the biggest contributor to a serverless function's end-to-end execution time. Recent studies from cloud providers, however, indicate that, in practice, a majority of serverless functions are triggered by non-interactive workloads. To substantiate this, we study the types of serverless functions used in 35 publications and find that over 80% of functions are not semantically latency sensitive. If a function is non-interactive and latency insensitive, is end-to-end execution time the right metric to optimize in serverless? What if cold starts do not matter that much, after all? In this vision paper, we explore what serverless environments in which cold starts do not matter would look like. We make the case that serverless research should focus on supporting latency insensitive, i.e., batch, workloads. Based on this, we explore the design space for DFaaS, a serverless framework with an execution model in which functions can be arbitrarily delayed. DFaaS users annotate each function with a delay tolerance and, as long as the deadline has not passed, the runtime may interrupt or migrate function execution. Our micro-benchmarks suggest that, by targeting batch workloads, DFaaS can improve substantially the resource usage of serverless clouds and lower costs for users. © 2024 ACM.

关键词： batch data processing

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Modeling and Scheduling of Multi-batch Process Based on Petri Nets and Monte-Carlo Tree Search 63

Modeling and Scheduling of Multi-Batch Process Based on Petr...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Jia, Mengsen Krebs, Nico Fritz, Rapheal Zhang, Ping University of Kaiserslautern-Landau Institute of Automatic Control Erwin-Schroedinger 12 Kaiserslautern67653 Germany

ISBN: (纸本)9798350316339

This paper proposes a novel approach for modeling and scheduling of flexible multi-batch processes (MBP) by using timed Petri nets (TPN) and Monte-Carlo Tree Search (MCTS). A TPN-based approach to model MBP is developed, which takes into account the key factors in MBP such as material quantities, tank and pipe capacities, conditional cleaning and storage location. To schedule the MBP, we propose an improved MCTS-based approach that is tailored for the MBP and is able to find the optimal firing sequence to to bring the system from its initial marking to a destination marking. The improved MCTS approach is able to find global optimal or near optimal solutions efficiently and doesn't need heuristic functions for node evaluation. The effectiveness of the proposed approach is illustrated with the help of an example of a chemical MBP. © 2024 IEEE.

关键词： batch data processing

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batch Process Monitoring with Attention-Based Two-Dimensional Stacked Graph Convolutional Autoencoder 6

Batch Process Monitoring with Attention-Based Two-Dimensiona...

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Gao, Xingke Zhang, Zheng Gao, Furong Zhu, Jinlin School of Artificial Intelligence and Computer Science Jiangnan University Wuxi China Hong Kong University of Science and Technology Department of Chemical and Biological Engineering Hong Kong School of Food Science and Technology Jiangnan University State Key Laboratory of Food Science and Resources Wuxi China

ISBN: (纸本)9798350356618

In batch processes, the efficacy of statistical control is reportedly sensitive to the dynamics and nonlinearity found in the batch data, which can hamper the valid feature extraction for statistical analysis. Normally, a two-way window is applied to aggregate the samples across the batch and time direction to assuage this challenge. However, samples in the window are generally processed on par with each other such that irrelevant features can cause redundancy and make window size critical to be tediously tune during the training phase. In this paper, a linear correlation aided method is proposed to first determine the effective size of a regular-shaped sliding window, and, a Euclidean distance-based measure is used to construct a graph prior to the phase of feature extraction. With these efforts, we presented the Attention-based Two-dimensional Stacked Graph Convolutional Autoencoder (2D-ASGCA) for enhanced learning in the Statistical Process Control (SPC) of batch processes. Moreover, a technique called Deep Reconstruction-based Contribution (DRBC) chart has been applied to perform the variable-wise root cause diagnosis, when a fault is signaled. Finally, two case studies are provided to demonstrate the model validity. © 2024 IEEE.

关键词： batch data processing

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Enhancing FHE Over the Integers: Beyond Binary Numbers and batch processing

Enhancing FHE Over the Integers: Beyond Binary Numbers and...

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International Conference on. Cryptology and Network Security with Machine Learning, ICCNSML 2023

作者： Upadhyay, Rohitkumar R. Padhye, Sahadeo Department of Mathematics Motilal Nehru National Institute of Technology Allahabad Uttar Pradesh Prayagraj211004 India

ISBN: (纸本)9789819706402

Fully Homomorphic Encryption (FHE) schemes enable secure computations on encrypted data. Following Gentry’s groundbreaking result, the AGCD problem-based FHE scheme, also known as Fully Homomorphic Encryption over the Integers (FHE-OI), was introduced by Dijk et al. Over the time, several improvements have been made to FHE-OI, including the CS scheme proposed by Cheon and Stehlé. This paper presents two significant enhancements to CS scheme. The first contribution involves extending their FHE scheme to support message space Zg, removing the previous constraint limited to binary numbers as described in Cheon and Stehlé’s work. Building upon this advancement, the second enhancement further extends the scheme to encompass batch fully homomorphic encryption. This extension empowers the scheme to efficiently encrypt and perform homomorphic operations on entire vectors of plaintext bits using a single ciphertext, thereby enhancing its applicability and utility in various practical scenarios. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

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