NVIDIA

This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. Machine learning harnesses computing power to solve a variety of ‘hard’ problems that seemed impossible to program using traditional languages and techniques. Machine learning avoids the need for a programmer to explicitly program the steps in solving […]

This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. It’s important for the model to make accurate predictions when using a deep learning model for production. How efficiently these predictions happen also matters. Examples of efficiency measurements include electrical engineers measuring energy consumption to pick the best

This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. To drive better than humans, autonomous vehicles must first see better than humans. Building reliable vision capabilities for self-driving cars has been a major development hurdle. By combining a variety of sensors, however, developers have been able

This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. The CUDA Fortran compiler from PGI now supports programming Tensor Cores with NVIDIA’s Volta V100 and Turing GPUs. This enables scientific programmers using Fortran to take advantage of FP16 matrix operations accelerated by Tensor Cores. Let’s take