Holistic computing

Bahar Asgari thinks that high-performance supercomputers (HPCs) could run far more efficiently and consume less energy. That’s particularly possible when crunching sparse datasets — ones with many zeros or empty values — that are often encountered in scientific computing. Her solution: low-cost, domain-specific architecture and hardware, and software co-optimization reminiscent of processes in the human brain.

“If you look at the performance of modern scientific computers used for sparse problems, they achieve the desired speed, but they don’t run efficiently,” says Asgari, a University of Maryland assistant professor of computer science. “So, they end up using more energy than is necessary.”

Asgari is in the first year of a five-year, $875,000 Department of Energy Early Career Research Program award to develop systems enabling intelligent dynamic configurability, which she has been working on since her time as a graduate student at the Georgia Institute of Technology.

One major reason HPCs are not energy efficient lies in their one-size-fits-all design. For the most part, manufacturers have no idea whether their components will be used for modeling nuclear transport, drug discovery, training artificial intelligence models or something else. So, they optimize chip design for the most common use case and make the entire machine programmable so it can be used for a wide range of applications.

“For many years, programmability has been the key to success in high-end computers,” Asgari says. “However, as technology scales upward, we must be more mindful about making these machines waste less energy.”

To improve computation efficiency and resource utilization, architects can employ hardware specialization. But that’s usually impractical because it is such a slow and costly process. Moreover, one specialized solution cannot fit the diverse requirements of various scientific computing workloads. To address this challenge, Asgari is developing a technique called intelligent dynamic reconfigurability, whereby hardware and software are unified in a holistic manner, adapting them together to efficiently run a program or multiple programs.

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