Purdue 5.2 Petaflop Supercomputer

Purdue University has a new 5.2 petaflop AI Anvil supercomputer. It will enable new discoveries in fields ranging from hypersonics and deep learning to archeological reconstruction and bone biomechanics. Anvil was funded by a $22.5 million grant from the National Science Foundation. Early users are working on projects in key areas of research such as:…
Purdue 5.2 Petaflop Supercomputer


Purdue University has a new 5.2 petaflop AI Anvil supercomputer. It will enable new discoveries in fields ranging from hypersonics and deep learning to archeological reconstruction and bone biomechanics. Anvil was funded by a $22.5 million grant from the National Science Foundation.

Early users are working on projects in key areas of research such as:

Hypersonics: Addressing the scientific challenges of predicting and controlling the extreme aerothermal loads that occur in flight at high Mach numbers.


Deep learning theory: Combining traditional graph algorithms and neural network methods to learn latent vertex representation in a graph. Applications include recommender systems, object relationship reasoning robotic, drug design, and logical rule extraction.


Archaeological reconstruction: A novel procedural (or generative) approach to creating detailed 3D models of existing or previously existing urban spaces for use in various exploratory, what-if design scenarios.


Bone biomechanics: Research combining structural geometry and material science. The research will study enhanced bone hydration as novel pathway to reduce bone fragility.

It has 1,000 nodes with two 64-core third-generation AMD Epyc processors each, and will eventually deliver over 1 billion CPU core hours to XSEDE each year, with a peak performance of 5.3 petaflops. Anvil’s nodes are interconnected with 100 Gbps Mellanox HDR InfiniBand. The supercomputer ecosystem also includes 32 large memory nodes, each with 1 TB of RAM, and 16 nodes each with four NVIDIA A100 Tensor Core GPUs providing 1.5 PF of single-precision performance to support machine learning and artificial intelligence applications.

Anvil uses a diverse set of storage technologies. It has 10-plus PB parallel filesystem and over 3 PB of flash disk. Novel workflows will benefit from block and object storage systems also supported by Anvil.

SOURCES -Purdue University


Written by Brian Wang, Nextbigfuture.com

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