Purdue gains new AI capabilities with the addition of new Gautschi community cluster
Purdue’s community cluster program has been used by researchers from all Purdue academic departments, which demonstrates not only how integral computing and data are to cutting-edge research, but also how accessible RCAC resources are.
The successful adoption of resources by a growing number of faculty at Purdue has continually driven growth of high-performance computing clusters at Purdue, which has in turn contributed significantly to hiring top researchers. Last year, 73% of Purdue’s grant awards were given to faculty using high-performance computing.
As artificial intelligence becomes more ubiquitous and used in every field of scientific computing, Purdue’s Rosen Center for Advanced Computing (RCAC) is taking a giant leap in terms of the AI capabilities provided to Purdue researchers with the addition of the Gautschi community cluster, which will drive innovation across a number of disciplines.
The Gautschi cluster features cutting-edge technology for traditional modeling and simulation applications, while also offering NVIDIA's top-tier solutions for AI applications. Gautschi, named after Walter Gautschi, professor emeritus of computer science and mathematics, and was dedicated in a campus ceremony earlier this month.
When Gautschi comes online later this fall, it will be Purdue’s most powerful community cluster built so far, with a peak performance of over 1016 floating point operations per second, potentially ranking in the top 150 most powerful supercomputers in the world. Gautschi nodes are already available for pre-purchase.
Gautschi will enable the transformative nature of AI in research by providing state-of-the-art GPUs to faculty involved in Purdue Computes initiative. The 160, 8-way connected H100 GPUs will allow adoption of intensive AI workloads such as major Large Language Models that have become key to research in several disciplines. The H100 utilizes NVIDIA Hopper architecture and a Transformer Engine in order to provide training and speeds that are four times faster than previous generation models.
“These devices will supercharge Purdue's investigation into AI,” says Alex Younts, Principal Research Engineer for RCAC.
“Whether it's customizing the next big LLM for language processing, training bots to drive around, or evaluating the health of fields of crops, Gautschi will have all the resources faculty need.”
In addition to Gautschi, much AI work is already being done on the Gilbreth and Geddes community clusters.
Gilbreth, which has the capacity to support a variety of GPU types, was introduced to do for AI what the original community cluster program did for traditional computing – to centralize campus computing in clusters built and maintained by expert RCAC staff, so researchers can focus solely on the science and not the minutiae of maintaining a supercomputer. Geddes’ most notable contribution to Purdue’s AI capabilities is the fact that it offers Kubernetes composable infrastructure and offers the capability to be used for advanced features such as running existing workflows or helping aid in the construction of AI apps.
All of the current clusters built come preinstalled with NVIDIA’s latest software, along with supporting temporary trials.
To learn more about RCAC's AI capabilities and the upcoming Gautschi cluster, contact rcac-help@purdue.edu.