MICRO 2023 Tutorial: GeneSys
Overview
This tutorial will present a discussion on emerging deep learning models along with a comprehensive walkthrough of our newly developed system, GeneSys. Attendees will gain valuable insights into our cutting-edge technology and its wide-ranging applications in the field of DNN acceleration systems.
Goals
We aim for attendees to gain a thorough understanding of the functionalities of our innovative system. They will learn how it can be effectively implemented in various applications and be equipped with the knowledge to harness its potential for their own projects and research in deep learning and DNN acceleration systems.
Who Should Attend?
Researchers and developers interested in deep learning systems, compiler development, and hardware/software design for DNN acceleration systems.
Date/Location
N/A
Tutorial Schedule
- [Time]: Overview of emerging deep learning models
- [Time]: Compiler
- [Time]: Accelerator architecture
- [Time]: Runtime and device driver
- [Time]: FPGA implementation
- [Time]: Hands-on session to compile and execute BERT
Presenters
- Hadi Esmaeilzadeh: Halicioğlu Chair in computer architecture and associate professor at the University of California, San Diego
- Rohan Mahapatra: Ph.D. student in computer science and engineering at the University of California, San Diego
- Hanyang Xu: Ph.D. student in computer science and engineering at the University of California, San Diego
- Christopher Priebe: Ph.D. student in computer science and engineering at the University of California, San Diego
Resources
[Links to slides, code samples, etc.]
Contact
[Contact information for the tutorial organizers]