2013
Pluralsight
Dmitri Nesteruk
4:12
English

This introductory course on CUDA shows how to get started with using the CUDA platform and leverage the power of modern NVIDIA GPUs. It covers the basics of CUDA C, explains the architecture of the GPU and presents solutions to some of the common computational problems that are suitable for GPU acceleration.

GPU Architecture Overview
16m 9s
Course Outline 2m 41s
History of GPU Computation 4m 27s
GPGPU Frameworks 2m 47s
Graphics Processor Architecture 2m 41s
Compute Capability 1m 2s
Choosing a Graphics Card 2m 29s
Tools of The Trade
16m 52s
Tools Overview 5m 4s
Using NSight 2m 59s
Running CUDA Apps 3m 29s
Debugging 2m 49s
Profiling 2m 29s
Introduction to CUDA C
30m 14s
Overview 1m 7s
Compilation Process 3m 1s
Hello, CUDA 13m 52s
Location Qualifiers 1m 34s
Execution Model 2m 12s
Grid and Block Dimensions 3m 2s
Error Handling 0m 46s
Device Introspection 4m 36s
Parallel Programming Patterns
52m 30s
Overview 2m 49s
Element Addressing 2m 14s
Map 11m 54s
Gather 12m 39s
Scatter 0m 50s
Reduce 12m 9s
Scan 9m 53s
The Many Types of Memory
12m 42s
Overview 1m 23s
Global Memory 2m 19s
Constant & Texture Memory 1m 53s
Shared Memory 4m 43s
Register & Local Memory 1m 32s
Summary 0m 50s
Thread Cooperation and Synchronization
23m 46s
Overview 1m 14s
Barrier Synchronization 1m 4s
Thread Synchronization Demo 18m 20s
Warp Divergence 2m 7s
Summary 1m 0s
Atomic Operations
22m 53s
Overview 0m 44s
Why Atomics? 1m 4s
Atomic Functions 1m 57s
Atomic Sum 7m 55s
Monte Carlo Pi 10m 37s
Summary 0m 33s
Events and Streams
35m 58s
Overview 0m 55s
Events 1m 14s
Event API 1m 13s
Event example 2m 14s
Pinned memory 8m 17s
Streams 0m 52s
Stream API 1m 27s
Example (single stream) 12m 30s
Example (multiple streams) 6m 17s
Summary 0m 55s
CUDA in Advanced Scenarios
41m 32s
Overview 0m 44s
Inline PTX 1m 34s
Device API 9m 45s
Pinned Memory 2m 15s
Multi-GPU Programming 20m 16s
Thrust 5m 52s
Summary 1m 1s

Download File Size:1.71 GB

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