Explore how to use Numba the just-in-time, type-specializing Python function compiler to accelerate Python programs to run on massively parallel NVIDIA GPUs.

Learn how to accelerate and optimize existing C/C++ CPU-only applications to leverage the\npower of GPUs using the most essential CUDA techniques and the Nsight Systems profiler. You’ll learn how to write code, configure code parallelization with\nCUDA, optimize memory migration between the CPU and GPU accelerator, and implement the workflow that\nyou’ve learned on a new task—accelerating a fully functional, but CPU-only, particle simulator for observable\nmassive performance gains

Find out how to write and configure code parallelization with OpenACC, optimize memory movements between the CPU and GPU accelerator, and apply the techniques to accelerate a CPU-only Laplace Heat Equation to achieve performance gains.