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