Quantum data parallelism in quantum neural networks
Physical Review ResearchQuantum neural networks hold promise for achieving lower generalization error bounds and enhanced computational efficiency in processing certain datasets.
Sixuan Wu, Yue Zhang, Jian Li
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Distributed Machine Learning Using Data Parallelism on Mobile Platform
J. Mobile Multimedia, 2020 Machine learning has many challenges, and one of them is to deal with large datasets, because the size of them grows continuously year by year. One solution to this problem is data parallelism. This paper investigates the expansion of data parallelism to
Máté Szabó
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A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training [PDF]
International Conference on Supercomputing, 2023 Mixture-of-Experts (MoE) is a neural network architecture that adds sparsely activated expert blocks to a base model, increasing the number of parameters without impacting computational costs.
Siddharth Singh +5 more
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Efficient tree-traversals: reconciling parallelism and dense data representations [PDF]
Proc. ACM Program. Lang., 2021 Recent work showed that compiling functional programs to use dense, serialized memory representations for recursive algebraic datatypes can yield significant constant-factor speedups for sequential programs.
Chaitanya Koparkar +4 more
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Optimistic Data Parallelism for FPGA-Accelerated Sketching
Proceedings of the VLDB Endowment, 2023 Sketches are a popular approximation technique for large datasets and high-velocity data streams. While custom FPGA-based hardware has shown admirable throughput at sketching, the state-of-the-art exploits data parallelism by fully replicating resources ...
Martin Kiefer +3 more
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Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism [PDF]
Knowledge Discovery and Data Mining, 2020 In this paper, we consider hybrid parallelism---a paradigm that employs both Data Parallelism (DP) and Model Parallelism (MP)---to scale distributed training of large recommendation models.
Vipul Gupta +8 more
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Achieving new SQL query performance levels through parallel execution in SQL Server [PDF]
E3S Web of Conferences, 2023 This article provides an in-depth look at implementing parallel SQL query processing using the Microsoft SQL Server database management system. It examines how parallelism can significantly accelerate query execution by leveraging multi-core processors ...
Nuriev Marat +3 more
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Collision Detection Based on Data Parallelism [PDF]
Jisuanji gongcheng, 2017 The application of accurate collision detection in Building Information Modeling(BIM) is facing the increasingly large amount of data,but the serial execution cannot continue to accelerate with the increasing frequency of the processor.Aiming at this ...
PENG Zhen,WU Baifeng
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Parallelizing the Data Cube [PDF]
, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dehne, Frank +3 more
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Parallel Optimization Method of Unstructured-grid Computing in CFD for DomesticHeterogeneous Many-core Architecture [PDF]
Jisuanji kexue, 2022 Sunway TaihuLight ranked first in the global supercomputer top 500 list 2016－2018 with a peak performance of 125.4 PFlops.Its computing power is mainly attributed to the domestic SW26010 many-core RISC processor.CFD unstructured-grid computing has always
CHEN Xin, LI Fang, DING Hai-xin, SUN Wei-ze, LIU Xin, CHEN De-xun, YE Yue-jin, HE Xiang
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