Learn · High Performance Computing for Scientists and Engineers
Lecture 33 of 40Week 7
Lecture 33 : Introduction to GPGPU and CUDA (continued)
Prof. Somnath Roy · IIT Kharagpur
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All the lectures
- Lecture 01 : Introduction to High Performance Computing
- Lecture 02 : Architecture for Parallel Computing
- Lecture 03 : Architecture for Parallel Computing (continued)
- Lecture 04 : Architecture for Parallel Computing (continued)
- Lecture 05 : Shared and distributed memory in parallel computing
- Lecture 06 : Shared and distributed memory in parallel computing (continued)
- Lecture 07 : Parallel Algorithms
- Lecture 08 : Parallel Algorithms (continued)
- Lecture 09 : 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