This course aims to teach learners how to program in CUDA and optimize GPU performance. By the end of the course, students will be able to implement various CUDA algorithms efficiently. The course covers topics such as vector addition, matrix multiplication, convolution, and GPU performance optimizations. The teaching method includes hands-on programming assignments and demonstrations. This course is intended for programmers and developers interested in parallel computing and GPU programming using CUDA.
Overview
Syllabus
CUDA Crash Course: Vector Addition.
CUDA Crash Course: Unified Memory Vector Add.
CUDA Crash Course: Matrix Multiplication.
CUDA Crash Course: Cache Tiled Matrix Multiplication.
CUDA Crash Course: Why Coalescing Matters.
CUDA Crash Course: cuBLAS Vector Add.
CUDA Crash Course: cuBLAS Matrix Multiplication.
CUDA Crash Course: Sum Reduction Part 1.
CUDA Crash Course: Sum Reduction Part 2.
CUDA Crash Course: Sum Reduction Part 3.
CUDA Crash Course: Sum Reduction Part 4.
CUDA Crash Course: Sum Reduction Part 5.
CUDA Crash Course: Visual Studio 2017 Environment Setup.
CUDA Crash Course: Programming in Linux.
CUDA Crash Course: Video Corrections.
CUDA Crash Course: Sum Reduction Part 6.
CUDA Crash Course: Naive 1-D Convolution.
CUDA Crash Course: 1-D Convolution with Constant Memory.
CUDA Crash Course: Tiled 1-D Convolution.
CUDA Crash Course: 1-D Convolution Cache Simplification.
CUDA Crash Course: 2-D Convolution.
CUDA Crash Course: Thinking Spatially.
CUDA Crash Course: Optimizing Histogram Kernels.
CUDA Crash Course: Comparing Matrix Multiplication Implementations.
CUDA Crash Course: Comparing Sum Reduction Implementations.
CUDA Crash Course: Handling Non-Perfect Input Sizes.
CUDA Crash Course: OpenACC Matrix Multiplication.
CUDA Crash Course: Device Properties.
CUDA Crash Course: Profiling with clock().
CUDA Crash Course: GPU Performance Optimizations Part 1.
Taught by
CoffeeBeforeArch
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Reviews
5.0 rating, based on 1 Class Central review
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Nick's course is a very intensive and complete course to get introduced into CUDA C++ programming. I enjoyed both the video lessons and the code available on GitHub and I enjoyed his very clear way of teaching CUDA and going into the details of GPU architecture. I absolutely suggest this course!
