Hard forks and easier access to GPU computing hold the potential to alleviate developers’ work, which can offset the ...

You're currently following this author! Want to unfollow? Unsubscribe via the link in your email. At a data-science conference in midtown Manhattan early this month, the Nvidia exhibitor table had a ...

Most infrastructure decisions look fine on paper until real AI workloads begin running at scale. Then performance issues ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

GPU resource management and scheduling represent a critical research area that underpins high-performance computing in an era of increasingly diverse and intensive workloads. As GPUs evolve beyond ...

The global GPU server market size was estimated at USD 174.3 billion in 2025 and is projected to reach USD 1,545.2 billion by ...

AI data centers and cloud computing are demanding strong investment from countries all over the world. The word "Sovereign AI" has become popular with countries building out their own AI ...

CPUs can successfully do GPU jobs, but there is one important caveat.

Nvidia (NVDA 1.00%) made a major quantum computing announcement when it launched its collection of open-source artificial intelligence (AI) models, called Ising, designed to make ...