[ONLINE] PARALLEL COMPUTING on GPUs with CUDA
Zoom
Please click here to access the recordings of the training.
The presentations are available at the bottom of the page.
Content:
- Introduction to Parallel Computing
- Introduction to GPUs and their Architecture
- CUDA Programming Model
- Using Multiple GPUs and Multiple Streams
- Debugging and Profiling Performance
- Performance Optimization and Efficiency
- Some Libraries and Remaining Issues
- CUDA Samples
Learning Outcomes:
After this course, the audience will
- have in-depth knowledge about parallel programming on the GPU
- be able to design and develop algorithms on the GPU with CUDA
- be able to distribute the computation to multiple GPUs
- have the ability to assess and improve the parallel performance on a GPU
Language
English
Level
beginner / intermediate
Instructors:
Özcan Dülger is a visiting Asst. Prof. Dr. at the Department of Computer Engineering, Middle East Technical University, Ankara, Turkey. He received his PhD from the same department. He is also Asst. Prof. Dr. at the Department of Computer Engineering, Artvin Coruh University, Artvin, Turkey. He was also visiting scholar in Center for Automotive Research at the Ohio State University, Columbus, OH, USA. His research areas are Parallel Computing, High Performance Computing, CUDA Programming and Target Tracking. He has been working on parallelization of particle filter-based tracking algorithms on GPU.
(https://user.ceng.metu.edu.tr/~odulger/)
Kamer Kaya is an Associate Professor at the Faculty of Engineering and Natural Sciences at Sabancı University. His research interests include Parallel Algorithms, Graph Algorithms, High-Performance Computing, and Cryptography. He is actively working on sparse computations on matrices, graphs, and tensors. His team focuses on implementing efficient algorithms on sparse data structures for cutting-edge HPC hardware such as GPUs and IPUs, especially for ML applications.
(http://people.sabanciuniv.edu/kaya/)
Acknowledgements
This event was supported by the EuroCC project. This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Germany, Bulgaria, Austria, Croatia, Cyprus, the Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, the United Kingdom, France, the Netherlands, Belgium, Luxembourg, Slovakia, Norway, Switzerland, Turkey, Republic of North Macedonia, Iceland, Montenegro.
EuroCC Turkey Social Media Accounts::
https://twitter.com/EuroCC_Turkey
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