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Leveraging Large-Scale Data for Efficient Low-Bit CUTLASS GEMM Optimization via Neural Networks

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Published in:Big Data Mining and Analytics
Format: Online Article RSS Article
Published: 2026
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container_title Big Data Mining and Analytics
description
discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
RSS Article
genre Journal Article
id rss_article:15047
institution FRELIP
journal_source_facet Big Data Mining and Analytics
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Leveraging Large-Scale Data for Efficient Low-Bit CUTLASS GEMM Optimization via Neural Networks
— — — — — — database management
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display — — — — — — database management
Computer Science & IT
Engineering & Technology
— — — — — — database management
Computer Science & IT
Engineering & Technology
subject_facet — — — — — — database management
Computer Science & IT
Engineering & Technology
title Leveraging Large-Scale Data for Efficient Low-Bit CUTLASS GEMM Optimization via Neural Networks
title_auth Leveraging Large-Scale Data for Efficient Low-Bit CUTLASS GEMM Optimization via Neural Networks
title_full Leveraging Large-Scale Data for Efficient Low-Bit CUTLASS GEMM Optimization via Neural Networks
title_fullStr Leveraging Large-Scale Data for Efficient Low-Bit CUTLASS GEMM Optimization via Neural Networks
title_full_unstemmed Leveraging Large-Scale Data for Efficient Low-Bit CUTLASS GEMM Optimization via Neural Networks
title_short Leveraging Large-Scale Data for Efficient Low-Bit CUTLASS GEMM Optimization via Neural Networks
title_sort leveraging large-scale data for efficient low-bit cutlass gemm optimization via neural networks
topic — — — — — — database management
Computer Science & IT
Engineering & Technology
url http://ieeexplore.ieee.org/document/11373500