GPUaccelerated computing in Bioconductor
Scientific Responsible for the Department: Davide Risso
Funder: Chan-Zuckerberg Initiative “Essential Open Source Software for Science”
Objectives: The project aims to support GPU-accelerated Bioconductor packages through continuous integration, user-friendly packaging of system-level dependencies, and foundational packages for Bioconductor GPU programming.
Partners:
- University of Padova
- CUNY Graduate School of Public Health and Health Policy
Duration: 2024-2025