Media Storage Type : 32 GB USB Stick
NPTEL Subject Matter Expert : Prof. Soumyajit Dey
NPTEL Co-ordinating Institute : IIT Kharagpur
NPTEL Lecture Count : 63
NPTEL Course Size : 13 GB
NPTEL PDF Text Transcription : Available and Included
NPTEL Subtitle Transcription : Available and Included (SRT)
Lecture Titles:
Lecture 1 - Review of basic COA w.r.t. performance
Lecture 2 - Review of basic COA w.r.t. performance
Lecture 3 - Review of basic COA w.r.t. performance
Lecture 4 - Review of basic COA w.r.t. performance
Lecture 5 - Intro to GPU architectures
Lecture 6 - Intro to GPU architectures
Lecture 7 - Intro to GPU architectures
Lecture 8 - Intro to GPU architectures
Lecture 9 - Intro to CUDA programming
Lecture 10 - Intro to CUDA programming (Continued...)
Lecture 11 - Intro to CUDA programming (Continued...)
Lecture 12 - Intro to CUDA programming (Continued...)
Lecture 13 - Multi-dimensional mapping of dataspace; Synchronization
Lecture 14 - Multi-dimensional mapping of dataspace; Synchronization (Continued...)
Lecture 15 - Multi-dimensional mapping of dataspace; Synchronization (Continued...)
Lecture 16 - Warp Scheduling and Divergence
Lecture 17 - Warp Scheduling and Divergence (Continued...)
Lecture 18 - Warp Scheduling and Divergence (Continued...)
Lecture 19 - Memory Access Coalescing
Lecture 20 - Memory Access Coalescing (Continued...)
Lecture 21 - Memory Access Coalescing (Continued...)
Lecture 22 - Memory Access Coalescing (Continued...)
Lecture 23 - Memory Access Coalescing (Continued...)
Lecture 24 - Memory Access Coalescing (Continued...)
Lecture 25 - Memory Access Coalescing (Continued...)
Lecture 26 - Memory Access Coalescing (Continued...)
Lecture 27 - Memory Access Coalescing (Continued...)
Lecture 28 - Optimizing Reduction Kernels
Lecture 29 - Optimizing Reduction Kernels (Continued...)
Lecture 30 - Optimizing Reduction Kernels (Continued...)
Lecture 31 - Optimizing Reduction Kernels (Continued...)
Lecture 32 - Optimizing Reduction Kernels (Continued...)
Lecture 33 - Optimizing Reduction Kernels (Continued...)
Lecture 34 - Optimizing Reduction Kernels (Continued...)
Lecture 35 - Kernel Fusion, Thread and Block Coarsening
Lecture 36 - Kernel Fusion, Thread and Block Coarsening (Continued...)
Lecture 37 - Kernel Fusion, Thread and Block Coarsening (Continued...)
Lecture 38 - Kernel Fusion, Thread and Block Coarsening (Continued...)
Lecture 39 - Kernel Fusion, Thread and Block Coarsening (Continued...)
Lecture 40 - Kernel Fusion, Thread and Block Coarsening (Continued...)
Lecture 41 - OpenCL - Runtime System
Lecture 42 - OpenCL - Runtime System (Continued...)
Lecture 43 - OpenCL - Runtime System (Continued...)
Lecture 44 - OpenCL - Runtime System (Continued...)
Lecture 45 - OpenCL - Runtime System (Continued...)
Lecture 46 - OpenCL - Runtime System (Continued...)
Lecture 47 - OpenCL - Runtime System (Continued...)
Lecture 48 - OpenCL - Heterogeneous Computing
Lecture 49 - OpenCL - Heterogeneous Computing (Continued...)
Lecture 50 - OpenCL - Heterogeneous Computing (Continued...)
Lecture 51 - OpenCL - Heterogeneous Computing (Continued...)
Lecture 52 - OpenCL - Heterogeneous Computing (Continued...)
Lecture 53 - OpenCL - Heterogeneous Computing (Continued...)
Lecture 54 - Efficient Neural Network Training/Inferencing
Lecture 55 - Efficient Neural Network Training/Inferencing (Continued...)
Lecture 56 - Efficient Neural Network Training/Inferencing (Continued...)
Lecture 57 - Efficient Neural Network Training/Inferencing (Continued...)
Lecture 58 - Efficient Neural Network Training/Inferencing (Continued...)
Lecture 59 - Efficient Neural Network Training/Inferencing (Continued...)
Lecture 60 - Efficient Neural Network Training/Inferencing (Continued...)
Lecture 61 - Efficient Neural Network Training/Inferencing (Continued...)
Lecture 62 - Efficient Neural Network Training/Inferencing (Continued...)
Lecture 63 - Efficient Neural Network Training/Inferencing (Continued...)