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Igor Sfiligoi sent in a story submission which was the inspiration for:

Second GPU Cloudburst Experiment Yields New Findings

In late 2019, researchers at the San Diego Supercomputer Center (SDSC) and the Wisconsin IceCube Particle Astrophysics Center (WIPAC) caught the attention of the high-performance computing community and top commercial cloud providers by successfully completing a bold experiment that marshalled all globally available-for-sale GPUs (graphics processing units) for a brief run which proved it is possible to elastically burst to very large scales of GPUs using the cloud, even in this pre-exascale era of computing.

[...] Fast forward to early February 4, 2020, when the same research team conducted a second experiment with a fraction of the remaining funding left over from a modest National Science Foundation EAGER grant.

[...] "We drew several key conclusions from this second demonstration," said SDSC's Sfiligoi. "We showed that the cloudburst run can actually be sustained during an entire workday instead of just one or two hours, and have moreover measured the cost of using only the two most cost-effective cloud instances for each cloud provider."

The team managed to reach and sustain a plateau of about 15,000 GPUs, or 170 PFLOP32s (i.e. fp32 PFLOPS[*]) using the peak fp32 FLOPS provided by NVIDIA specs. The cloud instances were provisioned from all major geographical areas, and the total integrated compute time was just over one fp32 exaFLOP[*] hour. The total cost of the cloud run was roughly $60,000.

[*] fp32 (floating point, 32-bit operands aka single precision)
FLOPS: Floating-point OPerations per Second
PFLOPS; Petaflops 10¹⁵ (i.e. 1,000,000,000,000,000) floating point operations per second.
exaFLOPS; 10¹⁸ (i.e. 1,000,000,000,000,000,000) floating point operations per second.

Disclaimer: The original story was apparently submitted by a participant in the research.

Original Submission