Results 1 to 10 of about 21,441,590 (245)
Fiber Clustering Acceleration With a Modified Kmeans++ Algorithm Using Data Parallelism [PDF]
Frontiers in Neuroinformatics, 2021 Fiber clustering methods are typically used in brain research to study the organization of white matter bundles from large diffusion MRI tractography datasets.
Isaac Goicovich +8 more
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Optimistic Data Parallelism for FPGA-Accelerated Sketching [PDF]
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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The Parallelism Motifs of Genomic Data Analysis [PDF]
Philosophical Transactions of the Royal Society A, 2020 Genomic data sets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share this data with the research community, but some of these genomic data ...
Awan, Muaaz +13 more
core +4 more sources
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
openalex +3 more sources
Algebraic data parallelism implementation in HPF
Lietuvos Matematikos Rinkinys, 2002 There is not abstract.
Valdona Judickaitė +2 more
doaj +3 more sources
Safe Data Parallelism for General Streaming [PDF]
IEEE transactions on computers, 2014 Streaming applications process possibly infinite streams of data and often have both high throughput and low latency requirements. They are comprised of operator graphs that produce and consume data tuples.
Scott Schneider +3 more
openalex +2 more sources
High Throughput Virtual Screening with Data Level Parallelism in Multi-core Processors [PDF]
, 2013 Improving the throughput of molecular docking, a computationally intensive phase of the virtual screening process, is a highly sought area of research since it has a significant weight in the drug designing process.
Prabuddha, Rahal +2 more
core +2 more sources
An efficient algorithm for data parallelism based on stochastic optimization
Alexandria Engineering Journal, 2022 Deep neural network models can achieve greater performance in numerous machine learning tasks by raising the depth of the model and the amount of training data samples.
Khalid Abdulaziz Alnowibet +3 more
doaj +2 more sources
, 2013 To define and identify a region-of-interest (ROI) in a digital image, the shape descriptor of the ROI has to be described in terms of its boundary characteristics. To address the generic issues of contour tracking, the yConvex Hypergraph (yCHG) model was
Agarwal, Tejaswi +2 more
core +3 more sources
Adaptive memory reservation strategy for heavy workloads in the Spark environment [PDF]
PeerJ Computer ScienceThe rise of the Internet of Things (IoT) and Industry 2.0 has spurred a growing need for extensive data computing, and Spark emerged as a promising Big Data platform, attributed to its distributed in-memory computing capabilities.
Bohan Li +6 more
doaj +3 more sources