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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 01 - Introduction

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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