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Monday, April 14, 2025

Scientists use Google Cloud AI products for their research


Supercomputing infrastructure solutions for the hardest, most important scientific problems

Scientists use supercomputers to tackle the world’s most challenging compute- and data-intensive problems. Supercomputers are systems such as high performance computing (HPC) clusters that utilize powerful CPUs and often GPUs, like our recently announced A4 and A4X VMs. These resources deliver the massive performance needed for large-scale simulation, data analysis, and AI model training. Simplified access to supercomputing-class resources, HPC cluster software, and AI tools and applications has become vital for scientific discovery and AI innovation.

Today, we’re introducing H4D VMs, Google Cloud’s most powerful CPU-based VMs, designed to enable new levels of performance for scientific applications. H4D VMs are built with the latest AMD CPUs and connected with advanced Titanium network acceleration. Together, these technologies allow scientists to deploy supercomputing-class HPC clusters and scale applications to thousands of processors to solve complex problems more rapidly and accurately. H4D VMs with Titanium network acceleration are available in preview now.

“This leap in computational capability will dramatically accelerate our pursuit of breakthrough therapeutics,” says Petros Koumoutsakos at Harvard University, “bringing us closer to effective precision therapies for blood vessel damage in heart disease.”

To help overcome the challenges of designing, deploying and managing complex clusters, we introduced Cluster Toolkit, which provides simple, reliable and repeatable cluster deployments. Along with the Cluster Director (formerly Hypercompute Cluster), you can deploy and manage a large cluster as a single unit for improved performance, efficiency and resilience.

Scientific and AI applications often have extreme storage demands, and that’s why we’re also announcing Google Cloud Managed Lustre, a new high-performance, fully managed parallel file system built in collaboration with DDN and based on EXAScaler Lustre.



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