Výsledky vyhledávání - Computing methodologies Distributed computing methodologies Distributed programming languages

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    MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems Autor Hsia, Samuel, Golden, Alicia, Acun, Bilge, Ardalani, Newsha, DeVito, Zachary, Wei, Gu-Yeon, Brooks, David, Wu, Carole-Jean

    Vydáno: IEEE 29.06.2024
    “…Training and deploying large-scale machine learning models is time-consuming, requires significant distributed computing infrastructures, and incurs high operational costs…”
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    Skywalker: Efficient Alias-Method-Based Graph Sampling and Random Walk on GPUs Autor Wang, Pengyu, Li, Chao, Wang, Jing, Wang, Taolei, Zhang, Lu, Leng, Jingwen, Chen, Quan, Guo, Minyi

    Vydáno: IEEE 01.09.2021
    “…Graph sampling and random walk operations, capturing the structural properties of graphs, are playing an important role today as we cannot directly adopt computing-intensive algorithms on large-scale graphs…”
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    Gluon-Async: A Bulk-Asynchronous System for Distributed and Heterogeneous Graph Analytics Autor Dathathri, Roshan, Gill, Gurbinder, Hoang, Loc, Jatala, Vishwesh, Pingali, Keshav, Nandivada, V. Krishna, Dang, Hoang-Vu, Snir, Marc

    ISSN: 2641-7936
    Vydáno: IEEE 01.09.2019
    “…Distributed graph analytics systems for CPUs, like D-Galois and Gemini, and for GPUs, like D-IrGL and Lux, use a bulk-synchronous parallel (BSP…”
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    AdaGL: Adaptive Learning for Agile Distributed Training of Gigantic GNNs Autor Zhang, Ruisi, Javaheripi, Mojan, Ghodsi, Zahra, Bleiweiss, Amit, Koushanfar, Farinaz

    Vydáno: IEEE 09.07.2023
    “…Distributed GNN training on contemporary massive and densely connected graphs requires information aggregation from all neighboring nodes, which leads to an explosion of inter-server communications…”
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    Auto-parallelizing stateful distributed streaming applications Autor Schneider, Scott, Hirzel, Martin, Gedik, Bugra, Wu, Kun-Lung

    Vydáno: ACM 01.09.2012
    “… They are comprised of operator graphs that produce and consume data tuples. The streaming programming model naturally exposes task and pipeline parallelism, enabling it to exploit parallel systems of all kinds, including large clusters…”
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    Optimizing Distributed ML Communication with Fused Computation-Collective Operations Autor Punniyamurthy, Kishore, Hamidouche, Khaled, Beckmann, Bradford M.

    Vydáno: IEEE 17.11.2024
    “…Machine learning models are distributed across multiple nodes using numerous parallelism strategies…”
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    Legate Sparse: Distributed Sparse Computing in Python Autor Yadav, Rohan, Lee, Wonchan, Elibol, Melih, Patti, Taylor Lee, Papadakis, Manolis, Garland, Michael, Aiken, Alex, Kjolstad, Fredrik, Bauer, Michael

    ISSN: 2167-4337
    Vydáno: ACM 11.11.2023
    “… The standard implementation of SciPy is restricted to a single CPU and cannot take advantage of modern distributed and accelerated computing resources…”
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    Introduction to Parallel and Distributed Programming using N-Body Simulations Autor Van Craen, Alexander, Breyer, Marcel, Pfluger, Dirk

    Vydáno: IEEE 17.11.2024
    “…This paper describes how we use n-body simulations as an interesting and visually compelling way to teach efficient, parallel, and distributed programming…”
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    Legate NumPy: Accelerated and Distributed Array Computing Autor Bauer, Michael, Garland, Michael

    ISSN: 2167-4337
    Vydáno: ACM 17.11.2019
    “… Legate works by translating NumPy programs to the Legion programming model and then leverages the scalability of the Legion runtime system to distribute data and computations across an arbitrary sized machine. Compared to similar programs written in the distributed Dask array library in Python, Legate achieves speed-ups of up to 10X on 1280 CPUs and 100X on 256 GPUs…”
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    A Sparsity-Aware Distributed-Memory Algorithm for Sparse-Sparse Matrix Multiplication Autor Hong, Yuxi, Buluc, Aydin

    Vydáno: IEEE 17.11.2024
    “… Distributed-memory parallel algorithms for SpGEMM have mainly focused on sparsity-oblivious approaches that use 2D and 3D partitioning…”
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    Towards an Optimized Heterogeneous Distributed Task Scheduler in OpenMP Cluster Autor Neveu, Remy, Ceccato, Rodrigo, Leite, Gustavo, Araujo, Guido, Diaz, Jose M. Monsalve, Yviquel, Herve

    Vydáno: IEEE 17.11.2024
    “…This paper addresses the challenges of optimizing task scheduling for a distributed, task-based execution model in OpenMP for cluster computing environments…”
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    CUDASTF: Bridging the Gap Between CUDA and Task Parallelism Autor Augonnet, Cedric, Alexandrescu, Andrei, Sidelnik, Albert, Garland, Michael

    Vydáno: IEEE 17.11.2024
    “…Organizing computation as asynchronous tasks with data-driven dependencies is a simple and efficient model for single- and multi-GPU programs. Sequential Task…”
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    Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling Autor Barwey, Shivam, Balin, Riccardo, Lusch, Bethany, Patel, Saumil, Balakrishnan, Ramesh, Pal, Pinaki, Maulik, Romit, Vishwanath, Venkatram

    Vydáno: IEEE 17.11.2024
    “…This work develops a distributed graph neural network (GNN) methodology for mesh-based modeling applications using a consistent neural message passing layer…”
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    Accelerating Communications in Federated Applications with Transparent Object Proxies Autor Pauloski, J. Gregory, Hayot-Sasson, Valerie, Ward, Logan, Hudson, Nathaniel, Sabino, Charlie, Baughman, Matt, Chard, Kyle, Foster, Ian

    ISSN: 2167-4337
    Vydáno: ACM 11.11.2023
    “… Here, we overcome this obstacle with a new programming paradigm that decouples control flow from data flow by extending the pass-by-reference model to distributed applications…”
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    Reshaping High Energy Physics Applications for Near-Interactive Execution Using TaskVine Autor Sly-Delgado, Barry, Tovar, Ben, Zhou, Jin, Thain, Douglas

    Vydáno: IEEE 17.11.2024
    “…High energy physics experiments produce petabytes of data annually that must be reduced to gain insight into the laws of nature. Early-stage reduction executes…”
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    Enhance the Strong Scaling of LAMMPS on Fugaku Autor Li, Jianxiong, Zhao, Tong, Guo, Zhuoqiang, Shi, Shunchen, Liu, Lijun, Tan, Guangming, Jia, Weile, Yuan, Guojun, Wang, Zhan

    ISSN: 2167-4337
    Vydáno: ACM 11.11.2023
    “…Physical phenomenon such as protein folding requires simulation up to microseconds of physical time, which directly corresponds to the strong scaling of…”
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    MPI Progress For All Autor Zhou, Hui, Latham, Robert, Raffenetti, Ken, Guo, Yanfei, Thakur, Rajeev

    Vydáno: IEEE 17.11.2024
    “… The opaque nature of MPI progress poses significant challenges in advancing MPI within modern high-performance computing practices…”
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