Accelerated and Reproducible Fiji for image processing using GPUs on the cloud

Autor:	Ling-Hong Hung, Evan Straw, Zachary Colburn, Ka Yee Yeung
Rok vydání:	2022
DOI:	10.1101/2022.07.15.500283
Popis:	SummaryGraphical processing units can greatly accelerate image processing but adoption has been hampered by the need for specialized hardware and software. The cloud offers inexpensive on-demand instances that can be pre-configured with the necessary software. Specifically, we use the Biodepot-workflow-builder (Bwb) to deploy a containerized version of Fiji that includes the CLIJ package to use GPUs on the cloud. In addition, we provide an Amazon Machine Image (AMI) with the correct drivers and Docker images pre-loaded. We demonstrate the portability and reproducibility of the platform by deploying an interactive Fiji/CLIJ workflow on both Amazon Web Services and IBM cloud. The workflows produce identical results while providing a 29-fold reduction in execution time.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d340a2083000742c437413d813a78c1b https://doi.org/10.1101/2022.07.15.500283 Zobrazit plný text záznamu