Benchmarking GPUs for Mixed Precision Training with Deep Learning
In this tutorial, we examine mixed-precision training to try and understand how we can leverage it in our code, how it fits into the traditional DL algorithmic paradigm, what frameworks support mixed precision training, and performance tips on using GPUs for DL with automatic mixed precision.
A complete anatomy of a graphics card: Case study of the NVIDIA A100
In our latest blogpost, we shine a spotlight on the Nvidia A100 to take a technical examination of the technology behind them, their components, architecture, and how the innovations within have made them the best tool for deep learning.
Top ten cloud GPU platforms for deep learning
In this article, we explore the services of available cloud GPU platforms with a focus on relevant factors such as pricing, infrastructure, design, performance, support, and security. We use this to present the best platforms to consider for your cloud GPU necessities.
AMPT-GA: Automatic Mixed Precision Floating Point Tuning for GPU Applications
In this overview, we look at AMPT-GA: a system that selects application-level data precisions to maximize performance while satisfying accuracy constraints via automatic mixed precision training.
Introducing the Ultimate Guide to GPU Cloud Providers
We've long been frustrated that GPU cloud providers make it so difficult to identify and compare GPU hardware -- so we set out to change that!
Computing GPU memory bandwidth with Deep Learning Benchmarks
In this article, we look at GPUs in depth to learn about memory bandwidth and how it affects the processing speed of the accelerator unit for deep learning and other pertinent computational tasks.