GPUs on Frontera: RTX 5000
Steve Lantz
Cornell Center for Advanced Computing
Revisions: 5/2023, 12/2021, 5/2021 (original)
It's fine to have a general understanding of what graphics processing units can be used for, and to know conceptually how they work. But at the actual hardware level, what does a particular GPU consist of, if one peeks "under the hood"? Sometimes the best way to learn about a certain type of device is to consider one or two concrete examples. Here we'll be taking a detailed look at the Quadro RTX 5000, a GPU which is found in TACC's Frontera. In a previous topic, we did a similar deep dive into the Tesla V100, one of the NVIDIA models that has been favored for HPC applications.
Objectives
After you complete this topic, you should be able to:
- List the main architectural features of GPUs and explain how they differ from comparable features of CPUs
- Discuss the implications for how programs are constructed for General-Purpose computing on GPUs (or GPGPU), and what kinds of software ought to work well on these devices
- Describe the names, sizes, and speeds of the computational and memory components of specific models of NVIDIA GPU devices
Prerequisites
- Familiarity with High Performance Computing (HPC) concepts could be helpful, but most terms are explained in context.
- Parallel Programming Concepts and High-Performance Computing could be considered as a possible companion to this topic, for those who seek to expand their knowledge of parallel computing in general, as well as on GPUs.