OpenGLES Acceleration for DL

Deep learning is a subset of machine learning that involves the use of neural networks with multiple layers. Neural networks consist of multiple layers of interconnected nodes, each building upon the previous layer to refine and optimize the prediction. The main goal of the project is to accelerate as many types of layers as possible using OpenGLES and Darknet as deep learning frameworks. Accelerating the performance of deep learning models is crucial for real-time applications. GPUs are widely used to accelerate the computations in deep learning models, as they can perform many operations in parallel.OpenGLES is a widely used graphics API that provides a framework for performing computations on GPUs. By using OpenGLES to perform computations, we can leverage the parallel processing power of the GPU to accelerate the performance of deep learning models.