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This is a first course in parallel programming and does not require any previous parallel computing experience. Data structures and Operating Systems are required. L-T-P: 3-0-2.

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.

 


Module/Lecture Details

Topics

Module 1:  Parallel Computing

Lecture 1

Introduction

Lecture 2

Parallel Programming Paradigms

Lecture 3

Parallel Architecture

Lecture 4

Parallel Architecture (case studies)

Lecture 5

Open MP

Lecture 6

Open MP(Contd.)

Lecture 7

Open MP(Contd..)

Lecture 8

Open MP&PRAM Model of Computation

Lecture 9

PRAM

Lecture 10

Models of Parallel Computation, Complexity

Lecture 11

Memory Consistency

Lecture 12

Memory Consistency & Performance Issues

Lecture 13

Parallel Program Design

Lecture 14

Shared Memory & Message Passing

Lecture 15

MPI

Lecture 16

MPI(Contd.)

Lecture 17

MPI(Contd..)

Lecture 18

Algorithmic Techniques

Lecture 19

Algorithmic Techniques(Contd.)

Lecture 20

Algorithmic Techniques(Contd..)

Lecture 21

CUDA

Lecture 22

CUDA(Contd.)

Lecture 23

CUDA(Contd..)

Lecture 24

CUDA(Contd...)

Lecture 25

CUDA(Contd....)

Lecture 26

CUDA(Contd.....)

Lecture 27

CUDA(Contd......)

Lecture 28

Algorithms,Merging & Sorting

Lecture 29

Algorithms,Merging & Sorting(Contd.)

Lecture 30

Algorithms,Merging & Sorting(Contd..)

Lecture 31

Algorithms,Merging & Sorting(Contd...)

Lecture 32

Algorithms,Merging & Sorting(Contd....)

Lecture 33

Lower Bounds Lock Free Synchronization,Load Stealing

Lecture 34

Lock Free Synchronization,Graph Algorithms

  1. Parallel Programming in C with MPI and OpenMP by M J Quinn
  2. Introduction to Parallel Computing by Ananth Grama, George Karypis, Vipin Kumar, and Anshul Gupta.
  3. Programming Massively Parallel Processors by D. Kirk and W. Hwu



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