NVidia is a leading Company in the field of Visual Computing and Parallel Computing. ZCOER, Pune has been selected as a GPU Education Center (GEC) in Sept 2015. The Principal Investigator is Prof. Anuradha Yenkikar, Co-PI are Prof. Rahul More, Prof. S. M. Kolekar Computer Engineering Department, ZCOER, Pune
Nvidia has donated to us a CUDA Teaching kit consisting of :
- K40 {active} (1 Unit)
- Titan X GPUs (2 Units)
- Copies of the Programming Massively Parallel Processors book authored by David B. Kirk & Wen-meiHwu (second edition)
NVidia offered us on-line courses by using qwickLABS.
The List of Courses is as follows:
- Developing GPU-accelerated applications with MATLAB
- Getting more Parallelism out of Multiple GPUs
- Introduction to Deep Learning
- Introduction to Interactive Deep Learning GPU Training System
- Accelerating Applications with CUDA Python
- Accelerating Applications with GPU-Accelerated Libraries in Python
- GPU Memory Optimizations (C/C++)
- Accelerating Applications with CUDA C/C++
- Accelerating Applications with GPU-Accelerated Libraries in C/C++
Access to 100 GPU programming labs are available at nvidia.qwiklab.com for free which we can divide among our students. As these labs are self-paced and hosted in the cloud, a student only needs a web-browser and internet access to participate.
NVidia also offered:
- Access to webinars for CUDA and GPU related programming from experts in various fields.
- Access to their technical team for support when needed.
Department of Computer Engineering already has already setup a GPU enabled Lab in A.Y. 2014-15 with the basic configuration of Nvidia GEFORCE GTX 210. All the machines are CUDA Enabled for conduction of programming assignments.
After getting approval of GPU Education Center we have conducted the following activities:
- Workshop on “GPU Programming and Applications” during 28th -30th December 2015 at ZCOER, Pune.
- CUDA sessions conducted as part of Third Year Computer Engineering course for PCDP and PL III lab sessions for students.
- GPU education center worked on GPU cluster setup and how to use Tesla K40 active server class GPU. Also Computer Engineering Final year students worked on their projects.
