On 31/01/2024 12:56, David Hildenbrand wrote: > On 31.01.24 13:37, Ryan Roberts wrote: >> On 31/01/2024 11:49, Ryan Roberts wrote: >>> On 31/01/2024 11:28, David Hildenbrand wrote: >>>> On 31.01.24 12:16, Ryan Roberts wrote: >>>>> On 31/01/2024 11:06, David Hildenbrand wrote: >>>>>> On 31.01.24 11:43, Ryan Roberts wrote: >>>>>>> On 29/01/2024 12:46, David Hildenbrand wrote: >>>>>>>> Now that the rmap overhaul[1] is upstream that provides a clean interface >>>>>>>> for rmap batching, let's implement PTE batching during fork when processing >>>>>>>> PTE-mapped THPs. >>>>>>>> >>>>>>>> This series is partially based on Ryan's previous work[2] to implement >>>>>>>> cont-pte support on arm64, but its a complete rewrite based on [1] to >>>>>>>> optimize all architectures independent of any such PTE bits, and to >>>>>>>> use the new rmap batching functions that simplify the code and prepare >>>>>>>> for further rmap accounting changes. >>>>>>>> >>>>>>>> We collect consecutive PTEs that map consecutive pages of the same large >>>>>>>> folio, making sure that the other PTE bits are compatible, and (a) adjust >>>>>>>> the refcount only once per batch, (b) call rmap handling functions only >>>>>>>> once per batch and (c) perform batch PTE setting/updates. >>>>>>>> >>>>>>>> While this series should be beneficial for adding cont-pte support on >>>>>>>> ARM64[2], it's one of the requirements for maintaining a total mapcount[3] >>>>>>>> for large folios with minimal added overhead and further changes[4] that >>>>>>>> build up on top of the total mapcount. >>>>>>>> >>>>>>>> Independent of all that, this series results in a speedup during fork with >>>>>>>> PTE-mapped THP, which is the default with THPs that are smaller than a PMD >>>>>>>> (for example, 16KiB to 1024KiB mTHPs for anonymous memory[5]). >>>>>>>> >>>>>>>> On an Intel Xeon Silver 4210R CPU, fork'ing with 1GiB of PTE-mapped folios >>>>>>>> of the same size (stddev < 1%) results in the following runtimes >>>>>>>> for fork() (shorter is better): >>>>>>>> >>>>>>>> Folio Size | v6.8-rc1 | New | Change >>>>>>>> ------------------------------------------ >>>>>>>> 4KiB | 0.014328 | 0.014035 | - 2% >>>>>>>> 16KiB | 0.014263 | 0.01196 | -16% >>>>>>>> 32KiB | 0.014334 | 0.01094 | -24% >>>>>>>> 64KiB | 0.014046 | 0.010444 | -26% >>>>>>>> 128KiB | 0.014011 | 0.010063 | -28% >>>>>>>> 256KiB | 0.013993 | 0.009938 | -29% >>>>>>>> 512KiB | 0.013983 | 0.00985 | -30% >>>>>>>> 1024KiB | 0.013986 | 0.00982 | -30% >>>>>>>> 2048KiB | 0.014305 | 0.010076 | -30% >>>>>>> >>>>>>> Just a heads up that I'm seeing some strange results on Apple M2. Fork for >>>>>>> order-0 is seemingly costing ~17% more. I'm using GCC 13.2 and was pretty >>>>>>> sure I >>>>>>> didn't see this problem with version 1; although that was on a different >>>>>>> baseline and I've thrown the numbers away so will rerun and try to debug >>>>>>> this. >>> >>> Numbers for v1 of the series, both on top of 6.8-rc1 and rebased to the same >>> mm-unstable base as v3 of the series (first 2 rows are from what I just posted >>> for context): >>> >>> | kernel | mean_rel | std_rel | >>> |:-------------------|-----------:|----------:| >>> | mm-unstabe (base) | 0.0% | 1.1% | >>> | mm-unstable + v3 | 16.7% | 0.8% | >>> | mm-unstable + v1 | -2.5% | 1.7% | >>> | v6.8-rc1 + v1 | -6.6% | 1.1% | >>> >>> So all looks good with v1. And seems to suggest mm-unstable has regressed by ~4% >>> vs v6.8-rc1. Is this really a useful benchmark? Does the raw performance of >>> fork() syscall really matter? Evidence suggests its moving all over the place - >>> breath on the code and it changes - not a great place to be when using the test >>> for gating purposes! >>> >>> Still with the old tests - I'll move to the new ones now. >>> >>> >>>>>>> >>>>>> >>>>>> So far, on my x86 tests (Intel, AMD EPYC), I was not able to observe this. >>>>>> fork() for order-0 was consistently effectively unchanged. Do you observe >>>>>> that >>>>>> on other ARM systems as well? >>>>> >>>>> Nope; running the exact same kernel binary and user space on Altra, I see >>>>> sensible numbers; >>>>> >>>>> fork order-0: -1.3% >>>>> fork order-9: -7.6% >>>>> dontneed order-0: -0.5% >>>>> dontneed order-9: 0.1% >>>>> munmap order-0: 0.0% >>>>> munmap order-9: -67.9% >>>>> >>>>> So I guess some pipelining issue that causes the M2 to stall more? >>>> >>>> With one effective added folio_test_large(), it could only be a code layout >>>> problem? Or the compiler does something stupid, but you say that you run the >>>> exact same kernel binary, so that doesn't make sense. >>> >>> Yup, same binary. We know this code is very sensitive - 1 cycle makes a big >>> difference. So could easily be code layout, branch prediction, etc... >>> >>>> >>>> I'm also surprised about the dontneed vs. munmap numbers. >>> >>> You mean the ones for Altra that I posted? (I didn't post any for M2). The altra >>> numbers look ok to me; dontneed has no change, and munmap has no change for >>> order-0 and is massively improved for order-9. >>> >>> Doesn't make any sense >>>> (again, there was this VMA merging problem but it would still allow for >>>> batching >>>> within a single VMA that spans exactly one large folio). >>>> >>>> What are you using as baseline? Really just mm-unstable vs. >>>> mm-unstable+patches? >>> >>> yes. except for "v6.8-rc1 + v1" above. >>> >>>> >>>> Let's see if the new test changes the numbers you measure. >> >> Nope: looks the same. I've taken my test harness out of the picture and done >> everything manually from the ground up, with the old tests and the new. Headline >> is that I see similar numbers from both. > > I took me a while to get really reproducible numbers on Intel. Most importantly: > * Set a fixed CPU frequency, disabling any boost and avoiding any > thermal throttling. > * Pin the test to CPUs and set a nice level. I'm already pinning the test to cpu 0. But for M2, at least, I'm running in a VM on top of macos, and I don't have a mechanism to pin the QEMU threads to the physical CPUs. Anyway, I don't think these are problems because for a given kernel build I can accurately repro numbers. > > Another thing is, to avoid systems where you can have NUMA effects within a > single socket. Otherwise, memory access latency is just random and depends on > what the buddy enjoys giving you. Yep; same. M2 is 1 NUMA node. On Altra, I'm disabling the second NUMA node to remove those effects. > > But you seem to get the same +17 even after reboots, so that indicates that the > CPU is not happy about the code for some reason. And the weird thing is, that > nothing significantly changed for order-0 folios between v1 and v3 that could > explain any of this. > > I'm not worried about 5% or so, nobody cares. But it would be good to have at > least an explanation why only that system shows +17%. Yep understood. > >> >> Some details: >> - I'm running for 10 seconds then averaging the output > > Same here. > >> - test is bimodal; first run (of 10 seconds) after boot is a bit faster on >> average (up to 10%) than the rest; I could guess this is due to the memory >> being allocated more contiguously the first few times through, so struct >> pages have better locality, but that's a guess. > > I think it also has to do with the PCP lists, and the high-pcp auto tuning (I > played with disabling that). Running on a freshly booted system gave me > reproducible results. > > But yes: I was observing something similar on AMD EPYC, where you get > consecutive pages from the buddy, but once you allocate from the PCP it might no > longer be consecutive. > >> - test is 5-10% slower when output is printed to terminal vs when redirected to >> file. I've always effectively been redirecting. Not sure if this overhead >> could start to dominate the regression and that's why you don't see it? > > That's weird, because we don't print while measuring? Anyhow, 5/10% variance on > some system is not the end of the world. I imagine its cache effects? More work to do to print the output could be evicting some code that's in the benchmark path? > >> >> I'm inclined to run this test for the last N kernel releases and if the number >> moves around significantly, conclude that these tests don't really matter. >> Otherwise its an exercise in randomly refactoring code until it works well, but >> that's just overfitting to the compiler and hw. What do you think? > > Personally, I wouldn't lose sleep if you see weird, unexplainable behavior on > some system (not even architecture!). Trying to optimize for that would indeed > be random refactorings. > > But I would not be so fast to say that "these tests don't really matter" and > then go wild and degrade them as much as you want. There are use cases that care > about fork performance especially with order-0 pages -- such as Redis. Indeed. But also remember that my fork baseline time is ~2.5ms, and I think you said yours was 14ms :) I'll continue to mess around with it until the end of the day. But I'm not making any headway, then I'll change tack; I'll just measure the performance of my contpte changes using your fork/zap stuff as the baseline and post based on that.
