Lecture 20 - Frameworks in Complex Multiphysics HPC Applications Lecture 19 - Architecting Parallel Software with Patterns Lecture 13 - Communication Avoiding Algorithms in Dense Linear Algebra Lecture 12 - Dense Linear Algebra: History and Structure, Parallel Matrix Multiplication Lecture 11 - An Introduction to CUDA/OpenCL and Graphics Processors (GPUs) Lecture 10 - Cloud Computing and Big Data Processing Lecture 09 - Performance Debugging Techniques for HPC Applications, Debugging and Optimization Tools Lecture 07 - Distributed Memory Machines and Programming Lecture 06 - Shared Memory Programming with Threads and OpenMP, Tricks with Trees Lecture 05 - Sources of Parallelism and Locality in Simulation (cont.) Lecture 04 - Sources of Parallelism and Locality in Simulation Lecture 03 - Introduction to Parallel Machines and Programming Models Lecture 02 - Single Processor Machines: Memory Hierarchies and Processor Features Go to the Course Home or watch other lectures: Lecture 08 - Partitioned Global Address Space Programming with Unified Parallel C (UPC) and UPC++ CS 267 is intended to be useful for students from many departments and with different backgrounds, although we will assume reasonable programming skills in a conventional (non-parallel) language,Īs well as enough mathematical skills to understand the problems and algorithmic solutions presented. CS 267 is designed to teach students how to program parallel computers to efficiently solve challenging problems in science and engineering, where very fast computers are required either to perform complex simulations or to analyze enormous datasets. CS 267: Applications of Parallel ComputersĬS 267: Applications of Parallel Computers (Spring 2015, UC Berkeley).
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