The primary figure of merit for the ML4NSE (defined in detail in https://doi.org/10.1615/JMachLearnModelComput.2023048607) workflow benchmark is computation throughput (i.e., the inverse of time-to-solution). Some useful secondary figures of merit will be:
The primary figure of merit for the ML4NSE (defined in detail in https://doi.org/10.1615/JMachLearnModelComput.2023048607) workflow benchmark is computational throughput (i.e., the inverse of time-to-solution). Some useful secondary figures of merit will be:
- Exchange bandwidth (ingress) at the gateway node which multiplexes among input streams