Title: Hands-on Hardware Accelerators for Machine learning
Credits: 3
CLASS: Tuesday 10:30 - 12:30 Taub 8
Tut : Tuesday 12:30 - 13:30 Taub 8
The course will be given in English if required
The course will focus on the reciprocal relationships between programming styles, machine learning, algorithms, and the hardware accelerators that support them. The course will cover (tentative list)
- CPU based accelerators for machine learning
- GPU based accelerators for machine learning
- Support for low power
- Binarization and quantization
- FPGA and ASIC accelerators
Prerequisites:
- A course in machine learning
- A course in Computer Architecture (or equivalent)
Grade:
20-30% - 3-4 exercises
30% - Presentation of a paper in the field (20-30 minutes)
40% - Final work - handle (individuals)
For more information please send an email to uavi.mendelsonattechnion.ac.il