GPU accelerated programming is becoming more and more important in today's high-performance computing stacks. It is commonly used in fields such as Artificial Intelligence (AI) and Machine Learning (ML). GPUs are commonly used for these tasks because they tend to be excellent for parallel computation.
In this chapter, we will learn about Cgo, GPU accelerated programming, CUDA (short for Compute Unified Device Architecture), make commands, C style linking for Go programs, and executing a GPU enabled process within a Docker container. Learning all of these individual things will help us to use a GPU to power a Go backed CUDA program. Doing this will help us to determine how we can use the GPU effectively to help solve computational problems using Go:
- Cgo – writing C in Go
- GPU-accelerated computing – utilizing the hardware
- CUDA on GCP...
