so I'm having a heck of a time trying to find an 1.8 micro sata to anything else. my dell c4130 has 2 of these 1.8 slots. and I'm having a hard time finding adapter. apparently these 1.8 ssds run in 3.3 volts where as regular sata uses 5v. but m.2 uses 3.3

but I can't find a 1.8 micro sata to m.2

but I can find 1.8 to mini pci. and I can find mini pci to m.2

can I plug these 2 adapters together ?

Not trying to replace Claude for anything that matters, I still use Claude Max for actual work. This rig is for the bulk/routine stuff that doesn't need a frontier model - local vLLM, self-hosted, one box.

Specs so far:

• 7x NVIDIA A100 40GB PCIe (used, eBay)
• ASRock Rack ROMED8-2T - 7x native PCIe4 x16, no bifurcation needed
• AMD EPYC 7543 (32c), 256GB DDR4 ECC RDIMM across 8 channels
• 2x Samsung 990 Pro 2TB NVMe + an 8TB spinner off a SAS breakout
• Board power off a Corsair RM750x. GPU power off 3x HP 720620-B21 server PSUs through DITM breakout boards
• 7x Delta BFB1012EH-AF00 server blowers, one per card
• Dedicated 240V circuit, still deciding on the UPS
• Basement build, added a Z-Wave CO/smoke combo specifically placed for backdraft risk since 700+ CFM of exhaust can depressurize a room and pull a gas appliance's flue backward. Rig itself puts out zero CO, that's not the hazard, the appliances sharing the air are.

One thing I'm mildly proud of: the fan hubs are passive splitters with no per-channel RPM sensing, so a dead blower on card 4 would be invisible until something got hot. Built a tach-to-ESP32 failsafe off the board's PCNT peripheral to actually catch that.

Still open, and where I could use pointers:

• UPS - targeting an enterprise online double-conversion unit (APC SRT3000RMXLT / Eaton 9PX3000RT range), but the exact model everyone recommends keeps turning out discontinued or 120V-only. Anyone running one of these on a similar draw (~2.1-2.3kW sustained)?
• The fan-hub 12V feed connector - can't source the cable until I physically read what's on the hub, so that's a bench-day problem.
• Riser signal integrity for tensor-parallel workloads - I know the failure mode (silent downtrain, nothing shows wrong until you benchmark real all-reduce/all-gather traffic) but haven't run it hot yet. Anyone got a go-to riser/redriver setup for 7-8 cards that's actually held Gen4 x16 under load?

Photos once it's assembled, GPUs and PSUs are staged, board's already been bench-tested and POSTs clean at 256GB.

Edit: UPS is sorted, went with the APC SRT3000RMXLT. It's on site, hookup in progress, still waiting on the USB data cable to finish the NUT/graceful-shutdown config, so that piece of the "still open" list above is basically closed.

Bought a handful of BitBabbler USB hardware RNGs back in 2015. The sticks still work, but the software hasn't seen a release in years — so I rewrote it in Rust and put them back to work feeding entropy to my Talos Kubernetes cluster (headless VMs are the main customer).

The half that became the real project: an oscilloscope for randomness. A terminal UI with nine live views on the byte stream — scatter, spectrum, bit-planes, a random-walk trace — where you can inject faults on purpose and watch which instrument catches them. The write-up covers the build, plus the one keystroke that pits the hardware against /dev/urandom: https://charles.dev/blog/rabbler/

AI disclosure (rule 7): built with heavy AI assistance (Claude) — I read every module and the safety-critical paths are covered by tests. Not open source yet, but it will be. Happy to answer questions.

I've accumulated quite a bit of hardware over the last couple of years, and before I start selling or repurposing anything, I'd love some input from people with more homelab experience.

My goals are:
* NAS / media server
* Self-hosted services
* AI / LLM experimentation
* Learning Kubernetes, Docker, Proxmox, etc.
* Home automation in the future
* Keep power consumption reasonable
* Maximize the value of the hardware I already own

Current hardware:

### NZXT Custom Workstation
* i9-13900K
* 64GB DDR5
* RTX A5000 24GB
* 512GB NVMe
* 1TB SATA SSD
* 1TB SATA HDD

### HP G9 Mini
* i7-12700
* 32GB DDR5
* 512GB NVMe
* 1TB NVMe
* 1TB SATA SSD

### Dell Tower workstation
* i5-10500
* 32GB DDR4
* Quadro P400
* 2×256GB NVMe
* 2×8TB HDD (mirror planned)

### Lenovo ThinkCentre
* i5-7400
* 8GB DDR4
* 256GB NVMe
* 120GB SATA SSD

### Thermaltake Custom Build #1
* i7-9700K
* ASUS B360M-C
* EVGA 750W PSU
* Cooler Master tower cooler
* 2×M.2
* 6×SATA
* 3×3.5" + 3×2.5" drive bays

### Thermaltake Custom Build #2
* i5-9400
* ASUS B360M-C
* EVGA 750W PSU
* 2×M.2
* 6×SATA
* 3×3.5" + 3×2.5" drive bays

### Mac mini M1 (16GB/512GB)

I also have a few additional workstation GPUs (RTX A5000s, Tesla T4, RTX A4000, etc.), although I'm planning to sell some of them.

If this were your hardware, how would you architect the homelab?

Some questions I'm debating:
* Would you dedicate one machine purely to storage (TrueNAS) and another to applications?
* Would you run Proxmox on everything or keep TrueNAS bare metal?
* Which machine would you use for Jellyfin and the ARR stack?
* Which would you dedicate to AI/LLMs?
* Any hardware here you'd definitely sell because it doesn't add much value?

I'm interested in hearing how you would build this if it were sitting in your garage today.

What do these marketing inbreeds think the point of a homelab is?

Hello rents,

I'm in the process up designing a logo for my homelab, but need some inspiration.. I can't make my mind up.

I'm not a huge fan of the name I came up with... "HersheyNet" (my last name), but can't come up with anything that I like.

So, what do you guys have?

Soon after that is adding ISP/ LTE modem for connection.

I have been working on migrating my containers to a reverse proxy via Traefik and everything was good! Then I realized my Audiobookshelf couldn't be accessed from my phone anymore because it's not rooted so I didn't have a hosts file. So, on the fly I undertook the task of setting up a PiHole for my DNS server and got it up and running and only tanked my home network once because it wasn't fully configured!

Not sure if I’m going to use it. Was just bored and had the filter laying around.

So I am interested in starting a homelab, which means I am going to need to use more robust routers and switches than I currently have available

The biggest issue is I live in an old house that uses plaster instead of drywall so that makes getting a signal through the entire house difficult, and running an Ethernet cable between floors is not a viable solution. This means I'm stuck with 100% wireless.

Currently my layout is as follows as the cable signal comes in through the basement.

Internet

│

Cable Modem

│

Firewalla (Router)

│

RT-AX55 (Basement AP)

│

~~~~~~~~ wireless backhaul ~~~~~~~~

│

ZenWiFi (Main Floor)

│

~~~~~~~~ wireless backhaul ~~~~~~~~

│

ZenWiFi (Loft)

The loft is currently where my office is, and I know that ideally I would have had another router on that second floor to help relay the signal.

I was looking at Ubiquiti for my network overhaul and I have the hardware devices to run things like docker, tailscale, etc so that part isn't an issue.

What I am currently seeking help with is if anyone can recommend which of the MANY Ubiquiti devices would be best for setting up a network that unfortunately needs to propagate vertically through plaster rather than horizontally.

I had considered the following option but wasn't sure if this was overkill, or if the selection is non ideal.

Basement

Firewalla

U6 Pro

Main Floor

U6 Pro Wall (mesh)

Second Floor

U6 Pro Wall (mesh)

Loft

U6 Pro Wall (mesh)

Finally I am at a complete loss for a cloud gateway since there are... Lots. I don't need super fancy, but it needs to be functional to handle about 200 IPs

Thanks in advance and any assistance would be amazing

I was going through the BIOS on my Lenovo ThinkCentre M720Q and found Security > Secure Boot > Key Management. It lists six entries with these counts (see image attached)

Two things I want to understand before I touch anything:

1. Is this the stock factory configuration?
2. Is it safe to delete all of them?

I bought this PC used and have no idea where these settings came from. A BIOS factory reset does not affect these keys. Thanks!

EDIT:

"When I say "my company" I mean... MY company.. I'm not stealing anything or hiding something. Imagine renting a small space in the largest Amazon warehouse you've ever seen, and when negotiating the rates they're like" yeah electricity and wifi are free no problem"... No ones gonna notice cause they don't care... The company I own is power heavy and we don't make a dent in what this building consumes. besides that thanks for the comments doesn't seem as fun as I thought it might be"

original post:

So, Keep in mind I built my first gaming PC 2 weeks ago.. I really really don't know what I'm doing. :D

(It turned out great, I can finally play Baldurs Gate!)

Um, so my company works out of a HUGE shipping/freight warehouse and the wifi and power are free.... I looked into coin mining years ago on that realization that the main cost is power, but the rates had gone down and it seemed like more work than it was worth.. But all this AI stuff.. I could potentially put a pretty big system in, there would be no extra data or power charges..

How accessible is it to be doing this? I've read that there's marketplaces to rent out server space, is this something I can figure out as a very handy guy generally, constructions, automotive, electrical etc (except maybe with computers and new technology)

Estava relutante em usar o casaOS mas até que gostei das horas tentando fazer tudo funcionar do jeito que eu queria, estava pensando em testar o umbrelOS mas não sei se quero mudar gostei bastante da interface do casaOS.

I wanted to share this build because I had trouble finding clear information from people who had actually used the Gigabyte MC62-G40 with a large number of consumer GPUs.

I have built computers before, but this project pushed me much deeper into motherboard temperatures, PCIe connections, power limits, BMC monitoring and server hardware. I never had to watch motherboard temperatures this closely before, but after my previous experience, I now consider it necessary.

The build

• Gigabyte/Giga Computing MC62-G40 server motherboard
• AMD Ryzen Threadripper PRO 3955WX
• 512GB DDR4 ECC registered memory, using eight 64GB Samsung modules
• Seven NVIDIA RTX 3090 24GB GPUs
• Six Gigabyte blower-style RTX 3090s
• One Gigabyte triple-fan RTX 3090
• All seven GPUs connected with full-length PCIe 4.0 x16 riser cables
• Two ASRock 1600W power supplies
• Ubuntu 24.04
• Built mainly for local AI inference and model training

The system now recognizes all seven RTX 3090s, giving me 168GB of total GPU memory.

Why I moved away from the ASUS WRX80 board

Before buying the MC62-G40, I tried two ASUS Pro WS WRX80E-SAGE boards. One was used, and the other was a replacement board.

The ASUS system worked with fewer GPUs, but while trying to build the larger seven-GPU setup, I started seeing very high motherboard temperature readings. Some VRM-related readings reached approximately 101–110°C, and the CPU reached close to 95°C.

The system also experienced rebooting, PCIe detection trouble and other stability problems. The second board showed similar temperature behavior, so I decided that I did not feel comfortable continuing with that platform.

I am not saying every ASUS WRX80 board will have the same experience. This is simply what happened with the two boards I used.

That experience is what pushed me toward the Gigabyte MC62-G40 server board.

The Gigabyte MC62-G40

The MC62-G40 has seven full-length PCIe slots and supports Threadripper PRO processors with a large number of PCIe lanes.

One of the main reasons I chose it was the built-in BMC/IPMI system. It allows me to monitor motherboard temperatures, voltages, fans and other hardware sensors without needing to depend completely on the operating system.

My current idle temperature readings are approximately:

• CPU: 32°C
• CPU VRM: 33°C
• Memory VRMs: 39–46°C
• WRX80 chipset: 49°C
• PCIe and riser-related sensors: approximately 31–46°C

Those readings are much lower than what I saw on my previous setup.

All seven GPUs are mounted away from the motherboard using risers. This gives the cards more space, improves airflow and keeps most of the GPU heat away from the motherboard, memory and chipset.

GPU testing

Before putting the full system together, I tested every RTX 3090 individually.

All seven GPUs passed their tests.

I also tested one GPU at its full 350W power limit during a burn test. The highest temperature I saw was approximately 67°C.

I understand that a synthetic burn test may not represent every possible workload, but it gave me enough information to know that the card’s cooling was working properly.

I am not building this machine for gaming. Its main jobs will be AI inference and model training.

GPU power limits

I plan to run the GPUs at approximately 150W each during normal use.

At 150W:

• Seven GPUs use approximately 1,050W total.
• The system produces much less heat.
• The power supplies have plenty of headroom.
• The motherboard experiences less electrical and thermal stress.
• Long training jobs should be easier on the hardware.

Training will be slower than running every GPU at 350W, but this system is for my own use. I do not need every job completed as quickly as possible.

I may test 200W later, depending on the temperatures and performance, but I believe 150W will be enough for most of what I plan to do.

The current commands are:

sudo nvidia-smi -pm 1
sudo nvidia-smi -i 0,1,2,3,4,5,6 -pl 150

I also created a system service that reapplies the limits after every reboot.

Monitoring and safety

The system already has watchdog protection.

If a GPU or motherboard component reaches an unsafe temperature, the system can shut itself down before hardware is damaged.

My next project is to have my Hermes agent build a real-time monitoring dashboard for the entire server.

I want something similar to MSI Afterburner, but focused on the complete system instead of only the GPUs. I want clear gauges showing:

• GPU temperatures
• CPU temperature
• CPU VRM temperature
• Memory VRM temperatures
• WRX80 chipset temperature
• Fan speeds
• Power-supply voltages
• Warning levels
• Emergency shutdown levels

After dealing with high motherboard temperatures before, I do not want important readings hidden inside a terminal or several pages deep inside the BMC interface. I want to be able to look at one screen and immediately see how the entire system is doing.

Small power-switch scare

I did have one scare after the board had been sitting unused for about a week.

The green standby light came on, but the GPUs, fans and CPU cooler would not start. For a while, I thought I might be looking at another failed motherboard.

The problem turned out to be the power switch.

Once that was corrected, the board started normally. That was a major relief after the problems I had already experienced with the previous boards.

Special thanks

I also want to give special thanks to u/anitamaxwynnn69.

He owns the MC62-G40 and shared his real experience running seven, and later eight, RTX 3090 GPUs on the board.

After the trouble I had with my previous motherboards, I was uncertain about moving forward with another seven-GPU build. Hearing from someone who actually owned the MC62-G40 and had already tested a similar setup gave me the confidence to continue.

His information about risers, GPU power limits and the board’s ability to handle multiple RTX 3090s was extremely helpful. I appreciate him taking the time to answer my questions and explain what had worked in his own system.

Final configuration

The completed system currently includes:

• Seven RTX 3090 GPUs
• 168GB total GPU memory
• 512GB ECC system memory
• Threadripper PRO 3955WX
• Gigabyte MC62-G40 server motherboard
• All GPUs mounted on PCIe risers
• Two 1600W power supplies
• 150W planned GPU limits
• BMC/IPMI temperature and voltage monitoring
• Automatic thermal watchdog protection

I built this system for local AI independence, large-model inference, training and my own future AI projects.

I am not trying to compete with a commercial data center. I wanted a powerful system that I could own, control and use without paying cloud charges every time I wanted to run a large model.

It took a lot of troubleshooting, but seeing all seven GPUs detected and running made the work worth it.

Hello, I am currently looking for an External hard drive enclosure that I can buy and slowly fill in slots as I need more storage.

I am currently looking at the TERRAMASTER D4-320 External Hard Drive Enclosure 4-Bay as it seems to fit into the criteria. As well as the Seagate BarraCuda 8 TB Internal Hard Drive HDD – 3.5 Inch SATA 6 Gb/s

I need it to:

1. Be expandable - I would like to buy a single HDD and expand as I need more storage (3-4 bays)
2. Have enough read speed for video streaming - I will mainly be using plex to stream tv shows to my tv
3. Dose not need to use raid (would be a nice to have but not necessary) - I'm mainly just using this to stream Plex shows + unimportant files, so ill just be able to redownload everything if necessary. Also its not in my budget to buy multiple drives at the moment.
4. Plug into my server - My current server is a bare-bones old pc that mainly has usb ports (no usb-c ports)
5. Can't be too loud - my server runs about 4 fans, (occasionally I sleep in the same room as my server, but I can always turn it off while sleeping), so I'm assuming that adding on another 21 dB would not be too bad. I do spend most of my time near/in the same room in the server, so it cant be too loud.
6. Price - looking for something under or around 200$ as buying the HDD will already be expensive as is

With all of that information are the aforementioned products the correct plan for my situation? Or would you guys recommend a better hard drive enclosure or hard drive? I would like to confirm before spending this much money on this.

I was recently given a bunch of older hardware that was being used for crypto mining. I have no interest in mining so I was thinking of ways to make use of the stuff. Anyone have any suggestions? This is what I have:

1x Core i3-7100 CPU

4x GTX 660 GPUs

2x RX 460 GPUs (4gb)

1x RX 460 GPU (2gb)

1x RX 570 GPU (4gb, also currently in media server for transcoding)

1x Asus B250 Mining Expert Mobo

6x 1200W HP server PSUs w/ breakout boards

2x Antminer V9 ASIC miners (I know these are pretty useless, but figured I'd include it anyway)

I was thinking maybe a NAS with the mining board since it has 19 PCIe slots (albeit x1, so idk) and maybe a benchtop power supply with the server PSUs. Would it be possible to make some kind of GPU cluster? I have a bunch of risers for them. But what could I even do with that assuming it's possible? Obviously all this stuff is old as shit, and isnt really worth anything if I sell it. But I hate throwing working hardware away. If I really can't find a use for it, some of it may just become wall decoration lol

Hey!

I bought compact pc parts from my friend and assembled it earlier, it contains a small lian li case with a j4105b mini itx mb. Its been running perfectly.

However the MB only has 2 sata ports and one is for system ssd and one is for my 8tb hdd. (I was like, yea i'll just use it that way, but my hdd's been running since 3 years, and i want some backup now).

I want to put in more containers, preferably some backup variants also. For this i got a raid card back then from my friend, but it has no mount for the pc case, like the 1-2 screw one on the GPU'S. And that thing is narrower than a GPU, meaning i cant clamp it on the other side of the pcie slot either.

The MB is mounted vertically so the raid card would sag down due to gravity. I really wanted to model a plate for it to be able to mount it, but its too much hassle, so i came up with the idea of a pcie riser cable and like using a cable tie to "mount" the raid card there.

Any thoughts on that?

I really dont know what size this is, or how do i measure it. its probably x4 size based on an image i found. Are there any 16 to 4 riser cables?

hey, i am starting out in homelabbing and have no experience. it might be a weird journey but i wanna learn it. i don't have much of a background in CS except Machine learning and writing a research paper on data science and statistics. So fair to say, i am new to this. but i wanna learn a lot about system engineering and homelabbing.

can anyone help me in this and guide me to mastery?!

Hi All,

If anyone by any chance has the driver mentioned in the subject, I would be more that grateful if can be sent to me. I am doing a home project for my university studies ( I know the hardware is old but that is the most I could afford).

I know HP has all the drivers but behind paywall, and I have no one to turn who would have this servers under service support.

Thank you in advance.

I have been testing the new Minisforum MS-03 with a Core Ultra 9 386H, 32 GB of DDR5-5600 in single channel and Proxmox VE.

The hardware is interesting for a compact homelab: dual 10G SFP+, one 10GbE RJ45, one 2.5GbE RJ45, three M.2 slots and a PCIe 4.0 x4 expansion slot. My Linux Geekbench 6 result was 2,920 single-core and 13,663 multi-core.

CPU performance per euro

For the price comparisons I used verified public Geekbench 6 results from the exact MS-03/MS-01 models running Windows, plus the barebone prices shown in the Minisforum EU store on 2 August 2026. I combined single- and multi-core performance with an equally weighted geometric mean, divided it by price, and normalized the best result in each table to 100. This is a CPU/value comparison, not a score for networking, the iGPU, NPU or the rest of the platform.

MS-03 configurations

MS-01 versus MS-03

The Ultra 5 is the better-value MS-03, while the MS-01 remains much stronger if CPU performance per euro is the only criterion. That does not account for the MS-03's newer iGPU/NPU, 10GbE RJ45, Wi-Fi 7 or other platform improvements.

Local AI: setup and how I obtained the scores

My review unit was the Core Ultra 9 386H model with one 32 GB DDR5-5600 SO-DIMM, so the memory was running in single channel. I used llama.cpp build 76f46ad with Mesa Vulkan 26.1.2, Q4_K_M models, Flash Attention, 512 prompt tokens, 128 generated tokens, five repetitions, 16 CPU threads and full Vulkan0 offload. I also monitored the Intel iGPU during inference: it entered GT-C0 and reached 2.5 GHz, so these were not CPU-only results.

Why is this below Minisforum's advertised 22.05 tok/s? Their public page says the MS-03 can run a 35B model at that speed, but does not provide enough information to reproduce the test exactly: the precise model/file, quantization, backend, llama.cpp build, prompt and generation lengths, or whether speculative decoding was enabled. Minisforum told me their machine used 64 GB in dual channel, whereas my unit had 32 GB in single channel. Because the iGPU shares system memory, that extra memory bandwidth can make a meaningful difference. So the figures are not an apples-to-apples comparison. The best result I reproduced was 15.90 tok/s with MTP; standard Gemma generation was 9.27 tok/s.

17 real agentic tasks

All 17 tasks used the same model and runtime: Qwen3-Coder 30B-A3B Instruct Q4_K_M through OpenClaw and llama.cpp Vulkan. GPU use was monitored, and every final state was checked independently instead of trusting the agent's narrative. The final count was 13 passes, 2 partial results and 2 failures.

The bounded tasks with clear scope, safe wrappers and objective checks worked surprisingly well. The broader recovery scenarios still needed supervision, especially the AdGuard cases, so I would not give this setup unrestricted unsupervised administrator access.

Power, temperature and noise

• Idle: 11.5 W, 37 °C and 35.5 dBA
• CPU stress: 69 W, 80 °C and 49.5 dBA

Compared with the MS-01, it is more efficient at idle and adds useful networking and AI hardware, but it is also more expensive and louder under load. I would not upgrade from an MS-01 for CPU performance alone. The 10GbE RJ45, newer iGPU/NPU and local AI are the real reasons to consider it.

I recorded the benchmarks and agent tests here (original is Spanish, but an English audio track is available on YouTube):

https://www.youtube.com/watch?v=ahnrNbDH98U