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Parallel Computing

Parallel Computing. Instructor: Prof. Subodh Kumar, Department of Computer Science and Engineering, IIT Delhi. This is a first course in parallel programming and does not require any previous parallel computing experience. Data structures and Operating Systems are required. With the growing number of cores on a chip, programming them efficiently has become an indispensable knowledge for the future. Modern Parallel Programming is a hands-on course involving significant parallel programming on compute-clusters, multi-core CPUs and massive-core GPUs. (from nptel.ac.in)

Lecture 32 - Algorithms, Merging and Sorting (cont.)


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Lecture 01 - Introduction
Lecture 02 - Parallel Programming Paradigms
Lecture 03 - Parallel Architecture
Lecture 04 - Parallel Architecture (Case Studies)
Lecture 05 - OpenMP
Lecture 06 - OpenMP (cont.)
Lecture 07 - OpenMP (cont.)
Lecture 08 - OpenMP and PRAM Model of Computation
Lecture 09 - PRAM (Parallel Random-Access Machine)
Lecture 10 - Models of Parallel Computation, Complexity
Lecture 11 - Memory Consistency
Lecture 12 - Memory Consistency and Performance Issues
Lecture 13 - Parallel Program Design
Lecture 14 - Shared Memory and Message Passing
Lecture 15 - MPI (Message Passing Interface)
Lecture 16 - MPI (cont.)
Lecture 17 - MPI (cont.)
Lecture 18 - Algorithmic Techniques
Lecture 19 - Algorithmic Techniques (cont.)
Lecture 20 - Algorithmic Techniques (cont.)
Lecture 21 - CUDA
Lecture 22 - CUDA (cont.)
Lecture 23 - CUDA (cont.)
Lecture 24 - CUDA (cont.)
Lecture 25 - CUDA (cont.)
Lecture 26 - CUDA (cont.)
Lecture 27 - CUDA (cont.)
Lecture 28 - Algorithms, Merging and Sorting
Lecture 29 - Algorithms, Merging and Sorting (cont.)
Lecture 30 - Algorithms, Merging and Sorting (cont.)
Lecture 31 - Algorithms, Merging and Sorting (cont.)
Lecture 32 - Algorithms, Merging and Sorting (cont.)
Lecture 33 - Lower Bounds Lock Free Synchronization, Load Stealing
Lecture 34 - Lock Free Synchronization, Graph Algorithms