[HN Gopher] Boosting Computational Fluid Dynamics Performance wi...
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Boosting Computational Fluid Dynamics Performance with AMD MI300X
Author : latchkey
Score : 43 points
Date : 2025-01-15 23:22 UTC (3 days ago)
(HTM) web link (rocm.blogs.amd.com)
(TXT) w3m dump (rocm.blogs.amd.com)
| thomasfedb wrote:
| Our team has access to multiple systems that either have MI250Xs
| or H100s. Getting stuff to work with AMD/ROCm is substantially
| more effort than the NVIDIA/CUDA experience.
|
| Some of this is lack of groundwork/engineering by packages or
| system administrators, but it seems a decent amount is the
| relative lack of effort by AMD to make things work well OOTB.
| BoingBoomTschak wrote:
| The real question is: is this from lack of effort or simply
| from NVidia's headstart? Will it get better?
| noch wrote:
| > Will it get better?
|
| It won't, not in any way that will make AMD approximately
| competitive with Nvidia.
|
| AMD, unlike Nvidia, seems unable to prioritize developers.
| Here's a summary of last week's charlie-fox when the TinyGrad
| team attempted to get 2 MI300s for on-premises testing and
| was rebuffed by an AMD representative.
| https://x.com/dehypokriet/status/1879974587082912235
| latchkey wrote:
| Installing ROCm is easy and well documented [0].
|
| Anush (AMD VP of AI software) has had a fire lit under his butt
| after the recent SemiAnalysis article [1] and is actively
| taking feedback on improving the experience. If you have
| specific things you'd like to see, I'm more than happy to
| forward them onto him (contact in my profile).
|
| [0] https://rocm.docs.amd.com/en/latest/
|
| [1]
| https://semianalysis.com/2024/12/22/mi300x-vs-h100-vs-h200-b...
| lukasb wrote:
| warning - no pretty videos in this post
| gymbeaux wrote:
| Now if only I could purchase one*
|
| *I realize enterprise "GPUs" are difficult to purchase as an
| individual whether they're AMD or Nvidia, but AMD might be well-
| served to mimic their RX 480 strategy ("make a competitive mid-
| range GPU, distribute it through several board partners, and sell
| it at rock-bottom prices to get it to as many customers as
| possible"). If there's a compelling reason to use AMD hardware
| over Nvidia, the software support will come. As an extreme
| example, if one could purchase an MI300X for $50 a pop, surely
| FAANG and others would invest time and effort into the software
| side to leverage the cost savings vs Nvidia, who is
| unquestionably price-gouging due to their monopolistic hold on
| the enterprise GPU market.
| mpreda wrote:
| It seems AMD has to choose between monetizing the GPUs _right
| now_ by selling them at the maximum effective price, or
| forgoing that gain and selling the GPUs _at cost_ and
| increasing GPU market share in the future. The choice between
| short-term gain and long-term gain.
| mpreda wrote:
| And the splitting into CDNA and RDNA comes from the same
| direction: market segmentation, to allow much higher prices
| for the CDNA data-center GPUs, while keeping the gamer-
| focused RDNA GPUs affordable for mere mortals. Of coures this
| backfires by making the powerful GPUs not available for
| mostly anybody anymore to experiment on.
|
| For example this blog post, about how great MI300X is.
| Really, what do I care -- I'm not a billionaire.
| tormeh wrote:
| They're unifying the architectures. AMD will move to UDNA
| for both gaming and data center. The next graphics cards
| after RDNA4 will be UDNA. Makes sense given how ML-heavy
| graphics has become.
| kouteiheika wrote:
| The point is they shouldn't have done it in the first
| place. It was obvious right from the start it's a bad
| idea, except maybe for temporarily boosting short term
| profits.
|
| The whole AMD AI/ML strategy feels like this - prioritize
| short term profits and completely shoot themselves in the
| foot in the long term.
| Cumpiler69 wrote:
| _> The whole AMD AI/ML strategy feels like this -
| prioritize short term profits and completely shoot
| themselves in the foot in the long term._
|
| That's what the stock market rewards.
| dragontamer wrote:
| ROCm was clearly designed with Wave64 in mind. It was
| going to take years for ROCm to be reworked for Wave32 of
| RDNA.
|
| DirectX shaders however were already ready for Wave32,
| and other architectural changes that RDNA had. In fact,
| RDNA was basically AMD changing their architecture to be
| more "NVidia-like" on many regards (32-wide execute being
| the most noticeable).
|
| CDNA existed because HPC has $Billion+ contracts with
| code written for Wave64 and still needing ROCm support.
| That means staying on the older GCN-like architecture and
| continuing to support say, DPP instructions or other
| obscure features of GCN.
|
| ---------
|
| Remember how long it took for RDNA to get ROCm support?
| Did you want to screw the HPC customers for that whole
| time?
|
| Splitting the two architectures, focusing ROCm on HPC
| (where the money was in 2018 for GPU Compute research
| dollars), and focusing on better video game performance
| for RDNA (where money is for video game / consumer cards)
| just makes sense.
| dragontamer wrote:
| > And the splitting into CDNA and RDNA comes from the same
| direction: market segmentation
|
| Not really.
|
| Wave64 on CDNA is provably more throughput. But with most
| video game code written for NVidia's Wave32, RDNA being
| reworked to be more NVidia-like and Wave32 is how you reach
| better practical video game performance.
|
| HPC will prefer the wider execute, 64-bit execution, and
| other benefits.
|
| Video Gamers will prefer massive amounts of 32MB+ of
| "Infinity cache", which is used in practice for all kinds
| of screen-space calculations. But this would NEVER be used
| for fluid dynamics.
| 42lux wrote:
| You mean hard in regards of pricing? Because otherwise it's not
| really hard to buy enterprise gpus at all.
| latchkey wrote:
| Depends on what country you are in. These are technically
| export controlled.
| ieidkeheb wrote:
| Nope ... IMO AMD cannot compete on software with nvidia. I
| bought an rx580 to test rocm/tensorflow ... Only for it to be a
| buggy mess that was discontinued for support in the next
| version.
|
| AMD needs to invest a Fsck load of money in software... Until
| then they can have the greatest compute cards in the world.but
| it will.mean nothing
| bavell wrote:
| Isn't rx580 like 4 gens behind now? It was released in 2017.
| Probably not the right card for anything AI.
| imtringued wrote:
| Why would anyone buy a new AMD card if the expectation is
| that the new one won't work either after support runs out?
| I use AMD at home and Nvidia A100s at work. There is no
| need to upgrade an old GPU to a new GPU if all it does is
| act as a fancy iGPU.
| KeplerBoy wrote:
| Because only the new ones are officially supported by
| AMDs compute stack?
| latchkey wrote:
| Disclosure, I have a business in this.
|
| This is what I saw as well. As a developer, I wanted access to
| enterprise HPC compute, but I'm also not going to do a PhD just
| to play around with these things. So, I got funding, started a
| business and bought 8 of them as a PoC test. We got customers,
| we got more funding, got a real datacenter, we bought 128 more.
| Crawl, walk, run.
|
| You can now rent them by the minute from us for a few bucks an
| hour. Currently limited to docker containers for individual
| GPUs, but you can get a full bare metal 8x box too (with BIOS
| too!). Support for VM's is coming. If you want multiple boxes,
| we have the full 8x400G NICs too. The boxes are fully loaded
| with tons of enterprise NVMe, RAM and top core/clock Intel CPUs
| (not AMD cause Dell didn't have that as a solution).
|
| Our model is to follow AMD's roadmap and buy/release their
| products as they come. We're currently debating the 325x and
| looking forward to / planning for the 355x.
|
| Despite your desire, it will be a long time before there is a
| consumer version of these things. Especially as they move to
| more and more complex deployments. Look at the NV72 and the
| requirements around that... we can all guess where AMD is
| going. DC rails in the racks, DLC cooling, massive power
| requirements. It is only getting more and more capex/opex
| intensive.
|
| Let's also not forget that AMD is really just a hardware
| manufacturer. When you buy a RX480 (I had 130,000 of these
| previously), it was from an OEM, like Sapphire, that could
| handle all the end user support.
|
| This is why the whole NeoCloud industry has sprung up. Large
| clouds can only handle this pace by selling thousands at a time
| in multi-year contracts. We are taking the long tail and built
| a business around that. Short of doing everything we are doing
| yourself (which trust me, is not easy), your best bet is to
| work with companies like mine to get you access to this gear.
|
| You can now rent them by the minute from us for a few bucks an
| hour. Currently limited to docker containers for individual
| GPUs, but you can get a full bare metal 8x box too. Support for
| VM's is coming. If you want multiple boxes, we have the full
| 8x400G NICs too. The boxes are fully loaded with tons of
| enterprise NVMe, RAM and top core/clock Intel CPUs (not AMD
| cause Dell didn't have that as a solution).
| LtdJorge wrote:
| You're doing good work on your subreddit!
| latchkey wrote:
| Thank you! https://www.reddit.com/r/AMD_MI300/
| latchkey wrote:
| (sorry that last paragraph got duplicated somehow)
| LtdJorge wrote:
| I'm pretty sure they're selling at capacity
| JorgeGT wrote:
| It's tangential, but this is the first time I've seen Fluent
| installed by simply decompressing a tar, instead of executing
| their big installer.
| semi-extrinsic wrote:
| This looks like a really stupid benchmark, no? 4 million cells in
| a standard aerodynamic simulation isn't enough work to even
| saturate the host CPUs on these systems, never mind the GPUs
| which have far "worse" roofline models from a CFD algorithm point
| of view.
|
| I would not be surprised at all if these benchmarks ran faster if
| you removed the GPUs completely.
| shihab wrote:
| That's the smallest of 4 experiments. It goes upto 140 million
| cells, where MI300X retains similar performance advantage of
| around 10% over Nvidia's H100.
| semi-extrinsic wrote:
| Yeah, but the lack of comparison to a CPU-only system is
| suspicious. (As is the exaggerated plot without ticks and
| labels on the y-axis.)
|
| I've never seen a non-reactive incompressible flow simulation
| get substantial speedup on GPUs. There are well understood
| fundamental reasons why this is the case.
| shihab wrote:
| I helped develop a hydro solver coupled with radiation at
| Los Alamos this summer. We observed from 7x upto 15x
| performance improvement on a single GPU compared to 64-core
| intel CPU. [1]
|
| Now granted, the flops to byte ratio for this program might
| be better than an avg fluid simulator. Also, our
| performance tanked when we moved to multi-node system. But
| I am aware of underlying reasons behind the scalibility
| issues and they don't feel like problems that can't be
| overcome.
|
| [1] https://github.com/lanl/HARD/tree/main
| semi-extrinsic wrote:
| Nice, interesting solver! But yes, compressible/density-
| based solvers work a lot better on GPUs than
| incompressible/pressure-based solvers. When 80% of the
| runtime is spent solving a Poisson equation, GPU is not
| worth it.
|
| Especially if you do the comparison on equivalent cost
| basis, i.e. "what is the walltime difference if I run on
| a $60k all-CPU cluster versus a $60k GPU cluster". Or in
| terms of cloud compute cost / HPC allocation spend.
| KeplerBoy wrote:
| Those are some sketchy bar charts. If the bar doesn't start at
| y=0 and you don't even have axis ticks, it's meaningless and just
| a colorful blob on your slide.
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