Achievement

Lecture Series in Parallel Computing and CUDA-C to introduce IGERT trainees and others to use of computational cluster:

Lecture 1 : Why Parallel Programming? Parallel Architectures and Programming Models. Lecture 2 : Parallelization Techniques Lectures 3 - 4 : Programming in a Shared Memory Environment - Introduction to OpenMP Lecture 5 : CUDA-C fundamentals. Compiler, kernels, host-device data transfer Lecture 6 : Time execution tuning, catching error and hardware evaluation Lectures 7 - 8 : GPU memory types Lectures 9 - 11 : Distributed Memory - MPI Paradigm Lecture 12 : Using High Performance Parallel Libraries : An Example - Parallel Matrix Inversion.