{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/hnmtp-conv-optimize-convolution-algorithm-for","title":"ILP-M Conv: Optimize Convolution Algorithm for Single-Image Convolution Neural Network Inference on Mobile GPUs","arxiv_id":"1909.02765","date":"2019-09-06","proceeding":null,"authors":["Zhuoran Ji"],"abstract":"Convolution neural networks are widely used for mobile applications. However, GPU convolution algorithms are designed for mini-batch neural network training, the single-image convolution neural network inference algorithm on mobile GPUs is not well-studied. After discussing the usage difference and examining the existing convolution algorithms, we proposed the HNTMP convolution algorithm. The HNTMP convolution algorithm achieves $14.6 \\times$ speedup than the most popular \\textit{im2col} convolution algorithm, and $2.30 \\times$ speedup than the fastest existing convolution algorithm (direct convolution) as far as we know.","url_abs":"https://arxiv.org/abs/1909.02765v2","url_pdf":"https://arxiv.org/pdf/1909.02765v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"hnmtp-conv-optimize-convolution-algorithm-for","repo_url":"https://github.com/jizhuoran/sj_convolution","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":null,"task_name":"GPU"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}