{"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/dll-a-blazing-fast-deep-neural-network","title":"DLL: A Blazing Fast Deep Neural Network Library","arxiv_id":"1804.04512","date":"2018-04-11","proceeding":null,"authors":["Baptiste Wicht","Jean Hennebert","Andreas Fischer"],"abstract":"Deep Learning Library (DLL) is a new library for machine learning with deep\nneural networks that focuses on speed. It supports feed-forward neural networks\nsuch as fully-connected Artificial Neural Networks (ANNs) and Convolutional\nNeural Networks (CNNs). It also has very comprehensive support for Restricted\nBoltzmann Machines (RBMs) and Convolutional RBMs. Our main motivation for this\nwork was to propose and evaluate novel software engineering strategies with\npotential to accelerate runtime for training and inference. Such strategies are\nmostly independent of the underlying deep learning algorithms. On three\ndifferent datasets and for four different neural network models, we compared\nDLL to five popular deep learning frameworks. Experimentally, it is shown that\nthe proposed framework is systematically and significantly faster on CPU and\nGPU. In terms of classification performance, similar accuracies as the other\nframeworks are reported.","url_abs":"http://arxiv.org/abs/1804.04512v1","url_pdf":"http://arxiv.org/pdf/1804.04512v1.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":"dll-a-blazing-fast-deep-neural-network","repo_url":"https://github.com/wichtounet/dll","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":null,"task_name":"CPU"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":null,"task_name":"GPU"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}