Explores GPUs' architecture, CUDA programming, image processing, and their significance in modern computing, emphasizing early start and correctness in GPU programming.
Covers the Conjugate Gradient method for solving linear systems without pre-conditioning, exploring parallel computing implementations and performance predictions.
Explores the Monte Carlo method for thermal radiation, covering radiative energy bundles, flux, surface relations, view factors, and radiative exchange computation.
Covers a review of past exams on distributed algorithms, focusing on key concepts such as Terminating Reliable Broadcast, Consensus, and Leader Election.
