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We are self-hosting our GPUs
- not_your_vase 2y ago> AMD 5700x processor I find it to be an odd choice. I mean the CPU itself is perfectly fine (typing this myself on a 5600G, which I very much like), but AM4 socket is pretty much over - there is no upgrade path anymore once it starts getting long on the tooth. (Unlike the other parts, which can be bumped: RAM, GPU, storage...)
- adityapatadia 2y agoProbably yes but we just built it to be cheaper. AM5 is on the costlier side and we don't plan to upgrade these machines. Our calculation is we can retire them by the end of 3 years.
- mobilio 2y agoI'm using same processors (and 5600) and they're FASTEST on single thread i've ever seen!
- mrweasel 2y ago> Our calculation is we can retire them by the end of 3 years. I was going to say, business just needs server to last 3 years, they are normally written off after 3 years and you don't do upgrade plans. Currently we're aiming more for 5 years, but budgeting for 3, that way anything beyond the 3 years is basically free. No one plans to purchase upgrade parts for their old Dell servers either. You can also move some of these machines into other roles like QA later on.
- softfalcon 2y agoAs soon as the AM4 vs AM5 conversation started, I immediately thought "price". The cost of swapping a mobo to AM5 in a few years is minimal compared to bulk price savings you can get using "good enough" AM4 now. Seeing AM4 boards and cpus easily 1/2 the price of AM5 gear in consumer sector. Imagine it's similar in the professional sector.
- Baeocystin 2y agoI'm still building more AM4 machines than AM5 for clients, FWIW, even for folks that want relatively performant desktops. The price/performance just isn't better enough yet to do otherwise for most.
- drio 2y agoHow do you feel about their GPU selection? I understand the 2U rack limits their choices, but what would you recommend as a good GPU that strikes a balance between performance and price?
- Baeocystin 2y agoMy honest opinion is that until the software situation drastically changes, there is zero reason to get anything other than nvidia cards, because the cost of hardware will always be dwarfed by engineering hours in dev, and ROCm isn't there yet by a long shot. I'm very much looking forward to this changing, for VRAM reasons in particular. But it's not going to happen any time soon.
- bitfilped 2y agoTypically components are never upgraded in a server: you spec it, buy it, write it off in 3-5 years, then throw it away.
- erichileman 2y agoWhy not run something like 8 x L40's for $4,750 a month from a bare metal provider like latitude.sh? This seems far more cost efficient and flexible.
- deleted 2y ago[deleted]
- 015a 2y agoI think you're reading that page wrong; but their pricing page is so confusing that its giving me red flags already. It says that would cost $6.51/hr and $4752/yr: I think you pay both of those things. I think the first number is the hourly cost, and the second number is the annual commitment. So its $56,246/year if you're running 24x7 + $4,756 = $61,002/year total.
- guisalberto 2y agoI am sorry if you are finding our pricing page confusing. We had a recent update to that page and we had a glitch for prices for the GPUs. Anyway, the correct price for a 8 x L40S is $4752/mo when paid a year upfront.
- 015a 2y agoSo, when the page now says "$6.51/hr // $4,752/mo", that's really just presenting the same actual cost you'd have to pay, across two different time metrics? As in, you pay $6.51/hr, or you pay $4,752/mo, same thing, but not both? I think you need to consider: Your competitors (e.g. AWS) generally structure annual commitments as an upfront (or monthly) payment + a reduced cost per hour/minute for the resource being reserved; that's the lens through which most people viewing this page will be thinking. If that is not how you structure annual commitments, then that should be made very clear. If my first paragraph is correct (and again, the page is still confusing, its not obvious to me that this interpretation is correct): You should list one price, and give a dropdown at the top to change the computation of that price across whatever timeframe the user wants ($/hr, $/day, $/month, etc). That would also free up some space in-line to put a chip that says something like "-15% discount!".
- BonoboIO 2y agoHetzner has RTX 4000 for 185€ per month. Is your solution cheaper?
- teaearlgraycold 2y agoSeems like it should break even around a year in
- adityapatadia 2y agoInterestingly, we tried that RTX4000 before we decided to buy our own. Yes, ours will break even in 14 months. ($2300 cost + $40 per month datacenter cost)
- rorra 2y agoIt would be nice if you can add numbers, like what would be the cost in your cloud provider, what was the total investment made, how much are you saving, which other options did you have in mind and why were discarded Still it was a nice post to read
- perryh2 2y ago> We however found that our co-working space - WeWork has an excellent server hosting solution. We could put the servers on the same floor as our office and they would provide redundant power supply, cooling and internet connection. This entire package is available at a much cheaper rate and we immediately jumped on this. Right now all servers are securely running in our office. Nice! How much does this cost?
- adityapatadia 2y ago$40 per server per month. Includes bandwidth, cooling and internet.
- nh2 2y agoWhat connection deal do you get for that? Does it have uninterruptible power supply?
- adityapatadia 2y agoYes, UPS + 2 independent power lines. Our server has a dual power input PSU. If either power fails, the other one keeps it running.
- CommanderData 2y agoSounds like a bargain. Any idea how long your servers will last until you need to upgrade to the latest GPU/HW?
- adityapatadia 2y ago3 years is what we planned. Any extra time we get will be a plus.
- JojoFatsani 2y agoHow bout compliance concerns? SOC and some of those are going to want to see super sophisticated datacenter ops/security/etc
- teaearlgraycold 2y agoAt my last job we did the same thing but for AI training hardware. It was definitely the right call cost-wise, with our little cluster breaking even after 8 months. We found a cheap data center in Texas.
- drio 2y agoWould you mind sharing the name of the data center?
- teaearlgraycold 2y agoTRG
- dangoodmanUT 2y agoHow did you expose the servers to the internet, if at all? I'd personally have these on tailscale, not exposed to the internet, but at some point in self hosting, clients have to be able to talk to something. I know tailscale has their endpoints but I can't expect this to be able to server a production API at scale.
- dangoodmanUT 2y ago"tailscale funnel"
- dangoodmanUT 2y agothis gives me an idea...
- aborsy 2y agoNo ACLs in front. I don’t know how much that could be done, but at least IP filtering.
- adityapatadia 2y agoTailscale :) We, fortunately, don't need these exposed to the internet so Tailscale works beautifully.
- CommieBobDole 2y agoI think generally the benefit of cloud is either where your demands are very elastic, or if you are essentially a fractional user - a single server or GPU would be overkill. Once you have heavy and/or unconventional compute needs, it's likely cheaper to self-host or colo purchased hardware.
- LarsDu88 2y agoHow many GPU servers are we talking about here exactly?
- adityapatadia 2y agoWe bought 21. This is just a start.
- LarsDu88 2y agoDoes each machine have just 1 gpu per rig or is it multiple? Do you network them to do DDP or is it just 1 inference job per card?
- deleted 2y ago[deleted]
- godelski 2y agoAs a ML person who's also worked on HPC stuff, you will most certainly save money by doing this and there are plenty of benefits. It is generally a good idea, but there is a bit more barrier to entry and you need in house expertise. So important piece of advice. If you can, hire an admin with HPC experience. If you can't, find ML people with HPC experience. Things you can ask about are slurm, environment modules (this clear sign!), what a flash buffer is, zfs, what they know about pytorch DDP, their linux experience, if they've built a cluster before, adminning linux, and so on. If you need a test, ask them to write a simple bash script to run some task and see if everything has functions and if they know how to do variable defaults. With these guys, they won't know everything but they'll be able to pick up the slack and probably enjoy it. As long as you have more than one. Adminning is a shitty job so if you only have one they'll hate their life. There are plenty of ML people who have this experience[0], and you'll really reap rewards for having a few people with even a bit of this knowledge. Without this knowledge it is easy to buy the wrong things or have your system run far from efficient and end up with frustrated engineers/researchers. Even with only a handful of people running experiments schedulers (like slurm) still have huge benefits. You can do more complicated sweeps than wandb, batch submit jobs, track usage, allocate usage, easily cut up your nodes or even a single machine into {dev,prod,train,etc} spaces, and much more. Most importantly, a scheduler (slurm) will help prevent your admin from quitting as it'll help prevent them from going into a spiral of frustration. [0] At least in my experience these tend to be higher quality ML people too, but not always. I think we can infer why there would be a correlation (details).
- adityapatadia 2y agoNice ideas, but we have chosen a really simple Kubernetes deployment. We only install the host OS (ubuntu server) and then join the self-hosted GPUs as workers in a Kubernetes cluster. No other task is needed and our Grafana monitors if the server (and its containers) are up and running.
- godelski 2y agoSorry, my suggestion was if you need to do training. If you're only serving then the suggestions I made aren't as valuable and something like what you've done probably make more sense. But you want a proper cluster setup to do multigpu and especially multi node stuff
- briandilley 2y agoI skimmed to the part about "We host it in our WeWork office" and thought WTF?
- adityapatadia 2y agowe know but it’s actually pretty good.
- kendallgclark 2y agohttps://www.stardog.com/blog/skathe-is-a-private-gpu-cloud/ https://www.stardog.com/blog/skathe-is-a-private-gpu-cloud/
- rkwasny 2y agoRTX 4000 ADA? That's a very under powered card: https://github.com/mag-/gpu_benchmark https://github.com/mag-/gpu_benchmark
- qmarchi 2y agoTangential to the post: Was going to toss an application your way since it sounds like interesting work, but it looks like the Google Form on your Careers page was deleted.
- adityapatadia 2y agoaditya [at] Gumlet.com
- p0w3n3d 2y agoShouldn't they be named VPU (vector processing units) as they are no longer to produce graphics?
- rurban 2y agoWe also do, and you'd need to add a couple more zero's for the cost. For administration it paid out that I'm a trained architect, because all the work is in cooling the room. Lots of temperature shielding and air and water flow, monitors, ...
- ThinkBeat 2y agoThis does not make sense to me. They are processing 2.5 Billion images and videos in a single day. They decided to self host their GPUs. The solution uses off-the-shelf hardware, with GPU per "server", add it all together into a single rack? And that is the GPU compute needed to process all the videos 24/7? Then they have this rack in the office, but they cant find a place to put it. That might be a decent thing to start out with, before the build. Where do we put it? But no. Planning for multiple network links, multiple redundant power, cooling, security, monitoring, and backup generators, handling backups, fire suppression, and failover to a different region if something fails was not necessary. Because Google book? But our (insert ad here) WeWork let us put our servers in a room on the same floor, (their data centerish capabilities seem limited) There are so many additional costs that are not factored into the article. I am sure once they accrue serious downtime a few times and irate customers, then paying for hosting in a proper data center might start making sense. Now I am basing this comment on the assumption that the company is providing continuous real-time operations for their clients. If it is more batch operated, where downtime is fine as long as results are delivered let us say within 12 hours.
- adityapatadia 2y agoThese servers are indeed job processing servers. They are critical but not milliseconds critical. Cooling, security, monitoring, backup generators, and backup of data all are taken care of.
- drio 2y agoDo you mind sharing the details of the rack mount you use?