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CUDA-Computational Engine

Implemented

  • Vector addition and dot product with shared memory.
  • Matrix multiplication, Gaussian elimination, inversion, and exponentiation.
  • 2D convolution with shared-memory tiling for fast image processing.

Concepts Learned

  • Thread and block hierarchy, memory types (global, shared, constant).
  • Memory coalescing, bank conflict avoidance, synchronization, and warp efficiency.

TODO: implement a makefile and polish the project

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CUDA projects implementing high-performance matrix and image computations on the GPU

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