This article is based on findings from a kernel-level GPU trace investigation performed on a real PyTorch issue (#154318) using eBPF uprobes. Trace databases are published in the Ingero open-source ...

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 ...

Engineers from OLX reported that a single-line modification to dependency requirements allows developers to exclude unnecessary GPU libraries, shrinking contain ...

A lot of people will tell you that PyTorch is for NVIDIA GPUs, but that's not actually true. PyTorch is platform-agnostic; it's just that many packages built on PyTorch make heavy use of NVIDIA's CUDA ...

PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.

Nvidia Corporation's parallel computing platform, CUDA, is a key factor in the company's competitive advantage, with exponential growth showcased at COMPUTEX 2023, boasting over four million ...

As Nvidia marks two decades of CUDA, its head of high-performance computing and hyperscale reflects on the platform’s journey ...