Commit 3e02eabb authored by Maximilian Dolling's avatar Maximilian Dolling

Merge branch 'patch-1' into 'master'

Update GPU-Cluster Requirements.md

See merge request !4
parents d1a2869a 2659b74d
...@@ -28,4 +28,6 @@ copy | paste | this | line | ! ...@@ -28,4 +28,6 @@ copy | paste | this | line | !
2.4 | Deep learning for fast magnitude estimation of earthquakes | Single precision GPU with > 10 GB GPU memory, at least 200 GB main memory, 8 CPU cores | up to date nvidia driver, the rest works fine with conda (cuda, tensorflow, pytorch) | I fear that 2 CPUs for 8 GPUs might be to less. The machine I'm currently running on has two Xeon Gold 5122 and four RTX 2080 Ti and is CPU bound. 2.4 | Deep learning for fast magnitude estimation of earthquakes | Single precision GPU with > 10 GB GPU memory, at least 200 GB main memory, 8 CPU cores | up to date nvidia driver, the rest works fine with conda (cuda, tensorflow, pytorch) | I fear that 2 CPUs for 8 GPUs might be to less. The machine I'm currently running on has two Xeon Gold 5122 and four RTX 2080 Ti and is CPU bound.
2.8 | Deep learning with solar images | Single precision GPU with > 20 GB GPU memory (RTX Titan not 2080Ti) | Nvidia driver. Module loads for standard python software, Virtualenv. Horovod required for multi node computations | I suggest 4 GPUs per node not 8. 2.8 | Deep learning with solar images | Single precision GPU with > 20 GB GPU memory (RTX Titan not 2080Ti) | Nvidia driver. Module loads for standard python software, Virtualenv. Horovod required for multi node computations | I suggest 4 GPUs per node not 8.
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 | -- 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 2.4 | Full waveforms inversion for seismic wave propogation simulation | Single precison GPU with around 20 GB GPU memory | Nvidia driver,conda, hdf5, netcdf
\ No newline at end of file 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
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