hgpu.org
In this paper, we focus on three sparse matrix operations that are relevant for machine learning applications, namely, the sparse-dense matrix multiplication (SPMM), the sampled dense-dense matrix multiplication (SDDMM), and the composition of the SDDMM with SPMM, also termed as FusedMM. We develop optimized implementations for SPMM, SDDMM, and FusedMM operations utilizing Intel oneAPI’s Explicit
Scratchapixel 3.0, Learn Computer Graphics Programming
Free learning resources to gradually introduce you to the field of computer graphics. We follow an application programming approach, leading you through small, readily compilable programs. We've chosen to use everyday language rather than unnecessary technical terms, making the content more accessible and user-friendly to a broader audience, including those who may not have the privilege of advanc
Resource for Computer Graphics - Ke-Sen Huang's Home Page
I got my Ph. D from the Department of Computer Science of National Tsing-Hua University, Taiwan. My research interests include: animation synthesis, animation summarization, and motion retrieval. My Web Changelog Paper Collection / Resources Open Access to ACM SIGGRAPH-Sponsored Content: For both SIGGRAPH and SIGGRAPH Asia, conference content is freely accessible in the ACM Digital Library for a o
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Publications | Visual Computing Group - Prof. Dr. Oliver Deussen
