Writing Code That Runs FAST on a GPU

In this video, we talk about how why GPU's are better suited for parallelized tasks. We go into how a GPU is better than a CPU at certain tasks. Finally, we setup the NVIDIA CUDA programming packages to use the CUDA API in Visual Studio. GPUs are a great platform to executed code that can take advantage of hyper parallelization. For example, in this video we show the difference between adding vectors on a CPU versus adding vectors on a GPU. By taking advantage of the CUDA parallelization framework, we can do mass addition in parallel. 🏫 COURSES 🏫 Check out my new courses at 🙌 SUPPORT THE CHANNEL 🙌 Become a Low Level Associate and support the channel at