(2020) From FLOPS to IOPS: The New Bottlenecks of Scientific Computing Источник: https://www.sigarch.org/from-flops-to-iops-the-new-bottlenecks-of-scientific-computing/ Автор: by Spyros Blanas on Jan 3, 2020
QUOTE | More than a decade ago, the pioneering computer scientist Jim Gray envisioned a fourth paradigm of scientific discovery that uses computers to solve data-intensive scientific problems. Today, scientific discovery, whether observational, in-silico or experimental, requires sifting through and analyzing complex, large datasets. For example, plasma simulation simulates billions of particles in a single run, but analyzing the results requires sifting through a single frame (a multi-dimensional array) that is more than 50 TB big—and that is for only one timestep of a much longer simulation. Similarly, modern observation instruments also produce large datasets: a two-photon imaging of a mouse brain yields up to 100 GB of spatiotemporal data per hour and electrocorticography (ECoG) recordings yield 280 GB per hour. |
QUOTE | Given the exponential growth trend in data volumes, the bottleneck for many scientific applications is no longer floating point operations per second (FLOPS) but I/O operations per second (IOPS). |
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