NOC:High Performance Computing for Scientists and Engineers (USB)

Media Storage Type : 32 GB USB Stick

NPTEL Subject Matter Expert : Prof. Somnath Roy

NPTEL Co-ordinating Institute : IIT Kharagpur

NPTEL Lecture Count : 40

NPTEL Course Size : 24 GB

NPTEL PDF Text Transcription : Available and Included

NPTEL Subtitle Transcription : Available and Included (SRT)

Lecture Titles:

Lecture 1 - Introduction to High Performance Computing
Lecture 2 - Architecture for Parallel Computing
Lecture 3 - Architecture for Parallel Computing (Continued...)
Lecture 4 - Architecture for Parallel Computing (Continued...)
Lecture 5 - Shared Memory and Distributed Memory in Parallel Computing
Lecture 6 - Shared Memory and Distributed Memory in Parallel Computing (Continued...)
Lecture 7 - Parallel Algorithms
Lecture 8 - Parallel Algorithms (Continued...)
Lecture 9 - Parallel Algorithms (Continued...)
Lecture 10 - Performance Metrics of Parallel Systems
Lecture 11 - Performance Metrics of Parallel Systems (Continued...)
Lecture 12 - Introduction to OpenMP
Lecture 13 - Introduction to OpenMP (Continued...)
Lecture 14 - Introduction to OpenMP (Continued...)
Lecture 15 - Essentials of OpenMP Programming
Lecture 16 - Essentials of OpenMP Programming (Continued...)
Lecture 17 - Data sharing and synchronization
Lecture 18 - Efficient OpenMP programming for matrix computing
Lecture 19 - Introduction to MPI and Distributed Memory Parallel Programming
Lecture 20 - Introduction to MPI and Distributed Memory Parallel Programming (Continued...)
Lecture 21 - Communication using MPI
Lecture 22 - Communication using MPI (Continued...)
Lecture 23 - Communication using MPI (Continued...)
Lecture 24 - Matrix Representation of Physical Systems - Matrix Solvers
Lecture 25 - Domain Decomposition Technique
Lecture 26 - Domain decomposition based parallelization of matrix solvers
Lecture 27 - Domain decomposition based parallelization of matrix solvers (Continued...)
Lecture 28 - Domain decomposition based parallelization of matrix solvers (Continued...)
Lecture 29 - MPI routines for parallel matrix solvers
Lecture 30 - Introduction to GPGPU and CUDA
Lecture 31 - Introduction to GPGPU and CUDA (Continued...)
Lecture 32 - Introduction to GPGPU and CUDA (Continued...)
Lecture 33 - Introduction to GPGPU and CUDA (Continued...)
Lecture 34 - Introduction to CUDA programming
Lecture 35 - Introduction to CUDA programming (Continued...)
Lecture 36 - Thread execution in CUDA program - scheduling and memory access
Lecture 37 - Thread execution in CUDA program (Continued...)
Lecture 38 - Matrix multiplications in CUDA
Lecture 39 - OpenACC programming for GPU-s
Lecture 40 - Hybrid parallelization and exascale computing