The achievement of exascale by the Aurora supercomputer at Argonne National Laboratory marks a significant milestone in the field of high-performance computing.

The Aurora supercomputer, installed in June 2023, is engineered to address some of the world’s most complicated scientific challenges. Aurora is currently the second-fastest supercomputer globally.

With its recent achievement of exascale performance, Aurora unlocks higher levels of accuracy, speed, and power compared to previous generations of supercomputers. This advancement will significantly enhance scientific research in areas such as climate modelling, cancer research and green energy.

To learn more about the Aurora supercomputer, its capabilities, and potential, The Innovation Platform spoke with Mike Papka, Director of the Argonne Leadership Computing Facility and Deputy Associate Laboratory Director of Computing, Environment, and Life Sciences at Argonne National Laboratory, as well as Professor of Computer Science at the University of Illinois Chicago.

Why is Aurora’s achievement of exascale computing a significant milestone? 

Aurora’s achievement of exascale computing is a significant milestone because it marks the ability to perform over a quintillion calculations per second, which is a tremendous leap in computational power. This power enables Aurora to handle diverse scientific tasks, from traditional modelling and simulation to data-intensive workflows and AI/ML applications, all within a single, unified system. Aurora’s architecture, combining powerful CPUs and GPUs, tackles complex problems such as climate modelling, materials discovery, and energy research.

What technological advancements enabled the Aurora supercomputer to surpass the exascale barrier, and how do these innovations contribute to its performance?

Aurora surpassed the exascale barrier thanks to several key technological advancements, including high-bandwidth memory, advanced GPUs, and an interconnect system called Slingshot 11. The Slingshot network, with nearly twice as many end-points as any other large-scale system currently deployed, allows Aurora’s more than 10,000 nodes to deliver massive amounts of data, which is crucial for its performance. This design enables Aurora to be the world’s fastest system for artificial intelligence (AI) (#1 Top500 MxP) and one of the fastest for traditional computing tasks (#2 Top500 HPL).

In what ways can Aurora’s exascale computing power accelerate advancements in artificial intelligence and machine learning?

Aurora’s exascale computing power is driven by its huge amount of memory and many GPUs, which are essential for training large AI models with trillions of parameters. These capabilities were demonstrated in June when Aurora achieved outstanding results in mixed-precision calculations, a key aspect of AI training workloads, even before the full system was operational. This performance highlights Aurora’s ability to accelerate AI and machine learning advancements, allowing researchers to handle massive datasets and develop more sophisticated models that can drive breakthroughs in various scientific fields.

Source: INN

Bachelor’s Degree in Computer Systems Engineering
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