I was looking for mini PCs with SFP+ and found a lot of fairly expensive small servers that were tempting. Then I got lucky and saw a new product coming out from minisforum, the MS-01, which had everything I needed at a much lower pricepoint.
I went with the 20 core intel i9-13900H but I think any of the three would have been fine for my needs.
Please note, it's easier to just use a recovery flash drive/dvd disk!
I just wanted a new challenge, and I found it:
My friend has switched from Windows to Fedora. Somehow in the process, Windows Bootloader went missing from EFI partition (I would love to know how did that happen as much as you do or don't, but I wasn't supervising at the moment, so... no idea)
This will result in a routable mesh network that can survive any one node failure or any one cable failure. Alls the steps in this section must be performed on each node
Using IPv6 to take advantage of not needing to use addresses - does make things simpler
dont buy ASUS motherboard for this topology - many of their motherboard do not implement full SW Connection Manager required for full spec USB4 / TB4 required for this topology and they are unable to articulate which motherboard do and do not have the required features and keep saying 20Gbp/s is the max speed of connection on intel NUCS - this is wrong. 13th and 14th Gen NUCs that implement a SW connection manager for USB4 / TB4 will work fine..
aka what i did to get from nothing to done.
note: these are designed to be primarily a re-install guide for myself (writing things down helps me memorize the knowledge), as such don't take any of this on blind faith - some areas are well tested and the docs are very robust, some items, less so). YMMV
vSphere 6 Enterprise Plus: | |
1C20K-4Z214-H84U1-T92EP-92838 | |
1A2JU-DEH12-48460-CT956-AC84D | |
MC28R-4L006-484D1-VV8NK-C7R58 | |
5C6TK-4C39J-48E00-PH0XH-828Q4 | |
4A4X0-69HE3-M8548-6L1QK-1Y240 | |
vSphere with Operations Management 6 Enterprise: | |
4Y2NU-4Z301-085C8-M18EP-2K8M8 | |
1Y48R-0EJEK-084R0-GK9XM-23R52 |
Your company's GPU computing strategy is essential whether you engage in 3D visualization, machine learning, AI, or any other form of intensive computing.
There was a time when businesses had to wait for long periods of time while deep learning models were being trained and processed. Because it was time-consuming, costly, and created space and organization problems, it reduced their output.
This problem has been resolved in the most recent GPU designs. Because of their high parallel processing efficiency, they are well-suited for handling large calculations and speeding up the training of your AI models.
When it comes to deep learning, good Cloud GPUs can speed up the training of neural networks by a factor of 250 compared to CPUs, and the latest generation of cloud GPUs is reshaping data science and other emerging technologies by delivering even greater performance
There is already a guide on scaling your Mastodon server up. This is a short guide on scaling your Mastodon server down.
I.e., maybe you want to run a small instance of <100 active users, and you want to keep your cloud costs reasonable.
So you might be running everything on a single machine, with limited memory and CPU. (In my case, I was using a t3.medium
instance with 2 vCPUs and 4GB of RAM.) How
do you do this?
Note that I'm not a Ruby or Sidekiq expert, and most of this stuff I figured out through trial and error.
Syncing an Ethereum node is largely reliant on latency and IOPS, I/O Per Second, of the storage. Budget SSDs will struggle to an extent, and some won't be able to sync at all. IOPS can roughly be used as proxy of / predictor for latency. Measuring latency directly is arguably better.
This document aims to snapshot some known good and known bad models.
The drive lists are ordered by interface and then by capacity and alphabetically by vendor name, not by preference. The lists are not exhaustive at all. @mwpastore linked a filterable spreadsheet in comments that has a far greater variety of drives and their characteristics. Filter it by DRAM yes, NAND Type TLC, Form Factor M.2, and desired capacity.
For size, 4TB is a very conservative choice. The smaller 2TB drive should last an Ethereum full node until at least sometime 2026, with the [pre-merge history expiry](https://hackmd.io/@hBXHLw_9Qq2va4pRt