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Anvil accelerates genome sequencing for studying psychiatric disorders

  • Science Highlights

Purdue’s Anvil supercomputer has helped one research team better understand how DNA changes relate to psychiatric disorders such as schizophrenia and post-traumatic stress disorder.

Richard Wilton, an associate research scientist at Johns Hopkins University, and his collaborators used Anvil to carry out the analysis of whole-genome DNA sequencing data from over 600 patients with these psychiatric disorders. They used a variety of bioinformatics tools on Anvil, including high-performance computing software that exploited Anvil’s GPU infrastructure to obtain twice the processing speed that they had obtained in comparable work on another national supercomputer.

“The team that put Anvil together has realized what researchers are going to be doing over the next few years and what the need is now for high-performance computing,” says Wilton.

“When we measured how fast we could get the data processed on Anvil, it’s pretty much as fast as you can get it processed anywhere.”

Wilton relied on the expert staff support offered to Anvil users by the Purdue Rosen Center for Advanced Computing.

“Lev [Gorenstein] and Steve [Kelley] were really responsive and helpful whenever I didn’t understand something about the way things were running,” says Wilton. “They had great suggestions and helped me troubleshoot problems.”

Anvil, which was recently named the 143rd fastest supercomputer in the world, has now completed its early user testing phase and is available for the general public to use. Researchers may request access to Anvil via the XSEDE allocation process.

Anvil consists of 1,000 nodes with two 64-core third-generation AMD EPYC processors each, and will deliver over 1 billion CPU core hours to XSEDE each year, with a peak performance of 5.1 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.

Research on Anvil will be able to leverage a diverse set of storage technologies, anchored by a 10-plus PB parallel filesystem, boosted with over 3 PB of flash disk. Novel workflows will benefit from block and object storage systems also supported by Anvil. More information about Anvil is available on Purdue’s Anvil website. Anyone with questions should contact anvil@purdue.edu. Anvil is funded under NSF award No. 2005632.

Writer: Adrienne Miller, science and technology writer, Rosen Center for Advanced Computing, mill2027@purdue.edu

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