Mini Projects
Each mini project has a clear set of goals. Explore and understand different concepts practically while working towards achieving those goals.
GPU Accelerated Matrix Multiplication
GitHub - tgautam03/xGeMM: Accelerated General (FP32) Matrix Multiplication
Accelerated General (FP32) Matrix Multiplication. Contribute to tgautam03/xGeMM development by creating an account on GitHub.
Goal: Code matrix multiplication from scratch and (try to) match the performance of cuBLAS SGeMM.
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Mini Project: GPU Accelerated Matrix Multiplication (almost) like cuBLAS
Learn CUDA C/C++ basics by working on a single application: matrix multiplication. To make things interesting, let us try to match the performance of NVIDIA cuBLAS.
GPU Accelerated Image Filters
GitHub - tgautam03/xFilters: GPU accelerated filters for high resolution images.
GPU accelerated filters for high resolution images. - tgautam03/xFilters
Goal: Code 2D convolution from scratch in CUDA C/C++ and use that to apply filters to high-resolution images.
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Mini Project: GPU Accelerated Image Filters using Convolution
Apply filters to high-resolution images using 2D convolution on a GPU. Along the way, learn about caches and using constant, shared, and pinned memory.
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