Hi all,
Trying to build a machine for both media storage and deep learning. Thinking of the following setup, not sure if it makes any sense:
2x E5-2670
128GB DDR3
ASUS 2070 Turbo
4xPM953 NVMe MIRROR (Scratch)
4xHUSML1640201 RAIDZ2 (VM OS)
6xWD EasyStores RAIDZ2 (Large storage)
The idea is to run ESXi baremetal and virtualize FreeNAS which will export the SSD RAIDZ2 over iSCSI which will be imported by ESXi as datastore for VM OS.
The spinners will be used for large files, exported as NFS and Plex.
GPU passthrough to a Ubuntu VM which will be used to run tensorflow. Currently unsure if I should import the NVMe as iSCSI or pass it directly to the VM.
Will the 8 vCPU limitation on free ESXi be a bottleneck?
Thoughts and criticisms appreciated.
Thanks!
Trying to build a machine for both media storage and deep learning. Thinking of the following setup, not sure if it makes any sense:
2x E5-2670
128GB DDR3
ASUS 2070 Turbo
4xPM953 NVMe MIRROR (Scratch)
4xHUSML1640201 RAIDZ2 (VM OS)
6xWD EasyStores RAIDZ2 (Large storage)
The idea is to run ESXi baremetal and virtualize FreeNAS which will export the SSD RAIDZ2 over iSCSI which will be imported by ESXi as datastore for VM OS.
The spinners will be used for large files, exported as NFS and Plex.
GPU passthrough to a Ubuntu VM which will be used to run tensorflow. Currently unsure if I should import the NVMe as iSCSI or pass it directly to the VM.
Will the 8 vCPU limitation on free ESXi be a bottleneck?
Thoughts and criticisms appreciated.
Thanks!