Designing and Generating Efficient FPGA-Based Accelerators for Deep Neural Networks
Lead Research Organisation:
University of Glasgow
Department Name: School of Computing Science
Abstract
The overarching aim of the project will be to produce efficient accelerator designs quickly and in an easy way. We will be able to make many novel improvements to accelerators using the research done through this project. Future researchers will have a platform to develop new techniques and enhancements for FPGA-based accelerators for DNNs.
Organisations
People |
ORCID iD |
| Jose Cano Reyes (Primary Supervisor) | |
| Jude Haris (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513222/1 | 01/10/2018 | 30/09/2023 | |||
| 2441374 | Studentship | EP/R513222/1 | 01/10/2020 | 31/03/2024 | Jude Haris |