GPU & CUDA4 Sparse Matrix Format Sparse Matrix Sparse matrix requires lot more consideration than when dealing with dense data, especially on GPUs. A sparse matrix is a matrix in which most of the elements are zero. It is important to understand the sparse matrix because a lot of data, for example, social network representing relationships between nodes or point clouds storing 3D-points information are sparse. Matrix Representa.. 2021. 7. 6. Accelerating Matrix Multiplication Using GPU Matrix Multiplication Matrix Multiplication is a simple but requires many computing resources. When Computing C = A x B, to calculate a element of C, we need to dot product of the row vector of A and the column vector of B. Since this has to be performed for all elements, it may take a considerable amount of time if the size of the matrix is large. Matrix multiplication is an operation suitable .. 2021. 6. 27. CUDA CUDA The CUDA is a parallel computing platform and application programming interface model supported by NVIDIA. CUDA programmers can program general purpose parallel program using C/C++ like language. CUDA Toolkit includes many functions such as libraries for GPU accelerating, monitors, profilers and etc. So if you want to customize or optimize your GPU application, it is very advantageous if yo.. 2021. 6. 25. GPU Architecture What is GPU? A GPU(Graphic Processing Unit) is a specialized device to accelerate the graphics and image processing. Simply GPU is different from CPU in that it has many cores. So the most important characteristic of GPU is parallelism. To fully utilize the device, we have to know the basic architecture and concept. Why GPU? Object detection Fluid Simulation The GPU is ofter used in applications.. 2021. 6. 20. 이전 1 다음
