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UW ARCC is pleased to announce the new HPC environment, MedicineBow (prior working name: Thunderer). This new HPC environment includes new 4th Gen AMD EPYC 9454 compute nodes, and multiple A30, L40S, and H100 GPU nodes. MedicineBow will be available for campus-wide use beginning July 1, 2024. In preparation, UW ARCC is initiating the hosting an Early Adopters Program (EAP) for MedicineBow to facilitate a seamless integration of hardware and software, and to promote exceptional scientific research. The program begins with a Performance Evaluation Phase, focused on assessing applications for their capabilities. This program runs throughout the summer starting June 1st, and ends August 26th, the first day of the Fall 2024 semester.

Early adoption provides researchers with several benefits, including:

• The chance to get a jump start on using the new system with limited competition for resources.

• Prioritized support from ARCC staff

• during EAP.

• Exclusive reserved access to any approved resources over the course of the EAP.

• EAP users will incur no charges throughout the course of the program, and will be able to continue using MedicineBow incurring standard ARCC charges following the end of the program.

Researchers approved for the early access program will get access to their reserved share of 152 GPUs , 4224 CPUs, and 3PB of research data storage over the course of the program.

The new MedicineBow HPC environment includes the following hardware:

The total computational power available to the Medicine Bow cluster per year is as follows:

• 1,331,520 GPU hours

  • 11.86 petaflops @ fp32

  • 2.72 petaflops @ fp64

• 37,002,240 CPU hours

  • 8.24 petaflops @ fp32

  • 2.36 petaflops @ fp64

• 3 Petabytes available for research data storage

ARCC will accept applications through Wednesday Friday May 15th17th, 2024. Applications are open to any applicants without strict prerequisitesall scientific disciplines. To apply, please fill out an application through our portal, here.

The application form will require an abstract associated with your intended work, the technical requirements associated with any computational technologies (if needed), and estimated compute hours and storage needs.