Discover how to accelerate Python data science workflows using GPU-accelerated libraries like cuDF, cuML, and cuGraph for faster data processing and model training.

We're kicking off a new benchmark series with the Ryzen 7 9800X3D vs. Ryzen 5 7600X, testing CPU and GPU scaling across four games, multiple resolutions, and ...

Not sure if your games are stressing the CPU or GPU more? Here’s how to find out and why it matters for smoother gaming.

A team at Stanford has shown that large language models can automatically generate highly efficient GPU kernels, sometimes outperforming the standard functions found in the popular machine learning ...

Read our detailed and comprehensive article on how to force use a dedicated GPU on your laptop or setup to maximize your system performance.

Discover how CPU, GPU, and neural processing unit (NPU) in Windows devices optimize performance, delivering faster speeds and improved graphics for everyday tasks.

Image-to-image translation is the process of transforming an image from one domain to another, where the goal is to learn the mapping between an input image and an output image. This task has been ...

Discover how to leverage GPU acceleration in Python's machine learning libraries for faster model training and improved performance.

This novel software library is crafted to bridge the accessibility gap, enabling LLMs to run efficiently on a broader spectrum of Intel CPUs and GPUs. At its core, IPEX-LLM leverages the Intel ...

If the CPU is bottlenecking the GPU, overclock the CPU to troubleshoot the problem, or keep reading this guide for more info.