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 ...

Programming model moves from managing thousands of low-level threads to working with high-level ‘tiles of data’ ...

OpenAI, the nonprofit venture whose professed mission is the ethical advancement of AI, has released the first version of the Triton language, an open source project that allows researchers to write ...

surpasses CUDA, a general-purpose parallel computing platform for GPUs developed and provided by NVIDIA, has been released. It is a language compiler for creating highly efficient custom deep learning ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Jinsong Yu shares deep architectural insights ...

This repository contains Python code for performing Monte Carlo integration using GPU acceleration via CUDA and Numba. The code is designed for high-dimensional integrals and leverages GPU parallelism ...

Facebook’s AI research team has released a Python package for GPU-accelerated deep neural network programming that can complement or partly replace existing Python packages for math and stats, such as ...

Warp 1.5.0 launches tile-based programming in Python, leveraging cuBLASDx and cuFFTDx for efficient GPU operations, significantly improving performance in scientific computing and simulation. The ...

Developers already have numerous options from the likes of Microsoft and Google for learning how to code in the popular Python programming language. But now budding Python developers can read up on ...