Topic

NVIDIA

A collection of 4 issues

NVIDIA GPU & Proxmox

If you've wondered ever why is it easy to create abstractions like Virtual CPU, RAM, Disk, but not GPU and get equivalent performance? Indeed I did. Why is it that for GPUs the standard tutorials suggested to simply pass through the entire GPU (using PCIe Passthrough) or simply add virtual

Folding @ Home on TX2

Let me clarify first that this post is not about running GPU enabled folding. For that, some hardware enablement is missing, and thus it'll be really hard to port it, though I may attempt that in future. For CPU performance, TX2 packs decent power, specially with 2 Denver Cores, 4

TX2 Hashing Performance

I recently got 3 TX2(s) donated to me by my friend Sri Krishna Acharya. I did flash it using a comprehensive tutorial provided by him plus slight modifications using an old Macbook Pro running Ubuntu 18.04 (so many NVIDIA quirks here, that this deserves it own blog post)

Getting started with Tegra K1 in 2021

> TLDR: Don’t get a TK1 in 2021. TX1 and higher support TensorRT so may be more interesting. This post is a repost from Medium. I consider myself somewhat of an IoT enthusiast, since I work professionally on the north-side (cloud) and play around with a lot of microprocessor boards