Implementing Deep Learning Algorithms on Graphics Processor Units

Autor:	Karol Grzegorczyk, Marcin Kurdziel, Piotr Iwo Wójcik
Rok vydání:	2016
Předmět:	Software Artificial neural network Computer architecture Computer science business.industry Deep learning Artificial intelligence Graphics business Supercomputer Algorithm Implementation Task (project management)
Zdroj:	Parallel Processing and Applied Mathematics ISBN: 9783319321486 PPAM (1)
Popis:	Deep learning has recently become a subject of vigorous research in academia and is seeing increasing use in industry. It is often considered a major advance in machine learning. However, deep learning is computationally demanding and therefore requires highly optimized software and high performance computing hardware. In this paper we share our experience from implementing core deep learning algorithms on a contemporary general-purpose graphics processor units. We describe in details the design decisions and considerations made during the implementation and show that it significantly outperforms high-level matrix-algebra implementations on a typical deep learning task. Finally, we outline a few use cases and research directions that we carried out with this software.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::2a93995cdb822a93d1689927bc2ccd11 https://doi.org/10.1007/978-3-319-32149-3_44 Zobrazit plný text záznamu