Question 1

How does DDN's partnership with Purdue University benefit data research?

Accepted Answer

DDN’s partnership with Purdue University enhances data research by providing high-performance computing (HPC) infrastructure that supports advanced computational needs across various scientific domains. This collaboration allows researchers at Purdue to efficiently manage and process large data sets, thereby accelerating discoveries and innovations.

Question 2

What are some of the specific research applications supported by the Rosen Center for Advanced Computing at Purdue University?

Accepted Answer

The Rosen Center for Advanced Computing supports a wide range of research applications including aeronautical engineering, mechanical engineering, fluid dynamics, computational chemistry, high energy physics related to the Large Hadron Collider, and data-intensive agriculture using IoT and drones for remote sensing.

Question 3

How is AI impacting the computational workload at Purdue University?

Accepted Answer

AI is increasingly becoming an integral part of various scientific domains at Purdue University. Researchers from diverse fields such as humanities, agriculture, and the business school are applying AI techniques. The demand for AI resources has led to a significant increase in usage, doubling the number of principal investigators (PIs) utilizing AI compute resources in just one year.

Question 4

What are the challenges associated with GPU demands in academic HPC environments as mentioned by Preston Smith?

Accepted Answer

The main challenges include acquiring enough GPUs to meet the high demands despite budget constraints, managing costs effectively without increasing tuition, and addressing the second-order challenges related to facility requirements like power, cooling, and space for housing GPUs.

Question 5

What steps is the Rosen Center taking to incorporate cloud-like experiences in their HPC infrastructure?

Accepted Answer

The Rosen Center is exploring composable Kubernetes-based systems adjacent to their HPC setups, allowing for stateful databases, portals, and inference engines that offer a cloud-like experience. This approach leverages existing HPC investments while providing flexible and efficient resource utilization for diverse research applications.

Question 6

How does DDN help optimize the performance and utilization of GPUs in research centers like Purdue University?

Accepted Answer

DDN optimizes GPU utilization by minimizing overhead times such as data writing during checkpointing, thus ensuring GPUs are used productively. They also focus on providing high-performance storage solutions in compact formats to maximize data center space for GPUs, ensuring efficient access to shared storage as if it were local.

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