diff --git a/GPU-Cluster Requirements.md b/GPU-Cluster Requirements.md index 6d90db48167875dd8a3ac019fa7bf465c36999c2..cf7a19ebc26eda87c4498065ed29e91dba11d46e 100644 --- a/GPU-Cluster Requirements.md +++ b/GPU-Cluster Requirements.md @@ -30,4 +30,4 @@ copy | paste | this | line | ! 1.3 | Machine learning for numerical modelling, data assimilation and data inversion | Double precision GPU with > 10 GB GPU memory (e.g., V100) | Nvidia driver, cuda, Python, R, Tensorflow and Keras libs, NetCDF support (+ ncview), Climate Data Operators (CDO), tmux | -- 2.4 | Full waveforms inversion for seismic wave propogation simulation | Single precison GPU with around 20 GB GPU memory | Nvidia driver,conda, hdf5, netcdf 3.6 | Atomistic simulation of (Geo-)materials | DP GPU preferred over SP | Nvidia drv, cuda, Python, MKL | for us at least 192 GB main memory, preferably more. Also, why not consider AMD EPYC instead of xeon? From a price/performance point of view - +1.4 | Machine learning for Sentinel-1 SAR data | Double precision GPU with > 10 GB GPU memory | Nvidia driver with cuda, tensorflow, Python | !