Heterogeneous Computing
A new class, Heterogeneous Computing, was offered in the Fall semester in National Tsing Hua University. The topics covered in the class can be roughly divided into four groups:
  1. CUDA basic: CUDA syntax, CUDA memory, GPU architecture.
  2. CUDA optimization: CUDA stream, techniques for performance optimization, CUDA profiler and debugger, performance libraries
  3. Multi-GPU programming: Multi-thread programming and MPI programming.
  4. Others: OpenACC, OpenCL, other accelerators, Kepler and CUDA 5
Another important part of the class is the term project, for which students can team up to find an interested topic to study and to implement it on GPU. Through the project, students demonstrate their ability in CUDA programming and performance tuning on new problems.
  CUDA Programming Contest
Nvidia Taiwan, National Center of High-performance Computing (NCHC), and CCOE co-hosted the third CUDA programming contest in Taiwan to promote the novel usage of CUDA in researches or works. The theme of this year is "Big Data", which is one of the major challenges in many areas. The contest has two stages. In the first stage, contestants submit their proposals; and in the second stage, the selected contestants present and demonstrate their CUDA programs on a GPU cluster, Formosa 5, which is provided by NCHC.
  SCC Training
The student cluster competition (SCC) is one of the student events held in conjunction with the Supercomputing Conference (SC) since 2007. The competition is a two days non-stop marathon for students to run HPL, HPCC, and four high performance computing (HPC) applications on a small cluster assembled by each team. The only limitation of the machine is the total power consumption. From 2010, some HPC applications have CUDA version, such as QMCPack. Since then, the CUDA programming and performace tuning become part of the SCC training.

Some of the video for 2012's final (1) (2).