What is this book about? Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your ...

Today Nvidia announced that growing ranks of Python users can now take full advantage of GPU acceleration for HPC and Big Data analytics applications by using the CUDA parallel programming model. As a ...

An end-to-end data science ecosystem, open source RAPIDS gives you Python dataframes, graphs, and machine learning on Nvidia GPU hardware Building machine learning models is a repetitive process.

Nvidia earlier this month unveiled CUDA Tile, a programming model designed to make it easier to write and manage programs for GPUs across large datasets, part of what the chip giant claimed was its ...

ML Language Playground: Multi-Language Neural Network Benchmark A multi-language machine learning benchmark comparing neural network implementations across C, Rust, and Python. Two model families --- ...

Every few years or so, a development in computing results in a sea change and a need for specialized workers to take advantage of the new technology. Whether that’s COBOL in the 60s and 70s, HTML in ...

PyTorch 1.0 shines for rapid prototyping with dynamic neural networks, auto-differentiation, deep Python integration, and strong support for GPUs Deep learning is an important part of the business of ...

The word supercomputer gets thrown around quite a bit. The original Cray-1, for example, operated at about 150 MIPS and had about eight megabytes of memory. A modern Intel i7 CPU can hit almost ...