On Wed, 29 Apr 2020 09:49:54 +0200 SeongJae Park <sjpark@xxxxxxxxxx> wrote: > On Tue, 28 Apr 2020 17:17:13 +0100 Jonathan Cameron <Jonathan.Cameron@xxxxxxxxxx> wrote: > > > On Tue, 28 Apr 2020 15:23:42 +0200 > > SeongJae Park <sjpark@xxxxxxxxxx> wrote: > > > > > On Tue, 28 Apr 2020 13:27:04 +0100 Jonathan Cameron <Jonathan.Cameron@xxxxxxxxxx> wrote: > > > > > > > On Mon, 27 Apr 2020 14:04:27 +0200 > > > > SeongJae Park <sjpark@xxxxxxxxxx> wrote: > > > > > > > > > From: SeongJae Park <sjpark@xxxxxxxxx> > > > > > > > > > > Introduction > > > > > ============ > > > > > > > > > > Memory management decisions can be improved if finer data access information is > > > > > available. However, because such finer information usually comes with higher > > > > > overhead, most systems including Linux forgives the potential benefit and rely > > > > > on only coarse information or some light-weight heuristics. The pseudo-LRU and > > > > > the aggressive THP promotions are such examples. > > > > > > > > > > A number of data access pattern awared memory management optimizations (refer > > > > > to 'Appendix A' for more details) consistently say the potential benefit is not > > > > > small. However, none of those has successfully merged to the mainline Linux > > > > > kernel mainly due to the absence of a scalable and efficient data access > > > > > monitoring mechanism. Refer to 'Appendix B' to see the limitations of existing > > > > > memory monitoring mechanisms. > > > > > > > > > > DAMON is a data access monitoring subsystem for the problem. It is 1) accurate > > > > > enough to be used for the DRAM level memory management (a straightforward > > > > > DAMON-based optimization achieved up to 2.55x speedup), 2) light-weight enough > > > > > to be applied online (compared to a straightforward access monitoring scheme, > > > > > DAMON is up to 94,242.42x lighter) and 3) keeps predefined upper-bound overhead > > > > > regardless of the size of target workloads (thus scalable). Refer to 'Appendix > > > > > C' if you interested in how it is possible, and 'Appendix F' to know how the > > > > > numbers collected. > > > > > > > > > > DAMON has mainly designed for the kernel's memory management mechanisms. > > > > > However, because it is implemented as a standalone kernel module and provides > > > > > several interfaces, it can be used by a wide range of users including kernel > > > > > space programs, user space programs, programmers, and administrators. DAMON > > > > > is now supporting the monitoring only, but it will also provide simple and > > > > > convenient data access pattern awared memory managements by itself. Refer to > > > > > 'Appendix D' for more detailed expected usages of DAMON. > > > > > > > > [...] > > > > > > > > > > Future Plans > > > > > ============ > > > > > > > > > > This patchset is only for the first stage of DAMON. As soon as this patchset > > > > > is merged, official patchsets for below future plans will be posted. > > > > > > > > [...] > > > > > > > > > > Support Various Address Spaces > > > > > ------------------------------ > > > > > > > > > > Currently, DAMON supports virtual memory address spaces using PTE Accessed bits > > > > > as its access checking primitive. However, the core design of DAMON is not > > > > > dependent to such implementation details. In a future, DAMON will decouple > > > > > those and support various address spaces including physical memory. It will > > > > > further allow users to configure and even implement the primitives by > > > > > themselves for their special usecase. Monitoring of page cache, NUMA nodes, > > > > > specific files, or block devices would be examples of such usecases. > > > > > > > > > > An RFC patchset for this plan is already available > > > > > (https://lore.kernel.org/linux-mm/20200409094232.29680-1-sjpark@xxxxxxxxxx/). > > > > > > > > [...] > > > > > > > > > > Patch History > > > > > ============= > > > > > > > > > > The most biggest change in this version is support of minimal region size, > > > > > which defaults to 'PAGE_SIZE'. This change will reduce unnecessary region > > > > > splits and thus improve the quality of the output. In a future, we will be > > > > > able to make this configurable for support of various access check primitives > > > > > such as PMUs. > > > > > > > > That is a good improvement. Might be interesting to consider taking > > > > hugepages into account as well. > > > > > > Thanks! Kudos to Stefan and you for giving me the comments for the change. > > > > > > As abovely mentioned in 'Future Plans' section, DAMON will be highly > > > configurable. You can see the plan in more detail via the RFC patchset[1]. > > > Thus, the minimal region size will also be able to configured as users want, > > > including the size of the hugepage. > > > > > > [1] https://lore.kernel.org/linux-mm/20200409094232.29680-1-sjpark@xxxxxxxxxx/ > > > > > > > > > > > One issue I've noted is that we have a degeneracy problem with the current > > > > region merging and splitting that perhaps could do with a small tweak. > > > > > > > > Currently we can end with a very small number of regions because there > > > > is no limit on how many regions can be merged in a give pass for merging. > > > > However, splitting only doubles the number of regions. > > > > > > > > I've been experimenting with a few loops of the splitting algorithm to ensure > > > > we don't end up stuck with limited regions. I think the problem we are working > > > > around can be roughly described as: > > > > > > > > 1) Program allocates a lot of memory - not really touching much of it. > > > > 2) Damon fuses the large memory allocations in to one region because the > > > > access counts are always near 0. > > > > 3) Program finishes setup. > > > > 4) Program accesses a few pages in the huge reason a lot, but not that much > > > > for most of the rest. Taking an extreme option, the page in the middle > > > > gets all the accesses and the other 1G on either side gets none. > > > > 5) As a split always breaks the page in two, the chances of significantly > > > > different values for the two resulting regions is low (as we only sample > > > > the hot page occasionally). > > > > > > > > If we just run the splits twice if the number of regions < max regions / 4 > > > > then over time we should eventually get a region with the single hot page in it. > > > > We will get there faster if we split more (keeping below max regions). > > > > > > > > As we always remain below max regions, we are still obeying the fixed > > > > maximum overhead and actually monitoring at closer to the desired granularity. > > > > > > Good point. However, as you also mentioned, DAMON will slowly, but eventually > > > adjust the regions appropriately. > > > > > > And yes, your suggested solution will work pretty well. Indeed, my one > > > previous colleague found this problem on a few of special workloads and tried > > > the solution you suggested. The improvement was clear. > > > > > > However, I didn't adopt the solution due to below reasons. > > > > > > First, IMHO, this is an accuracy improvement, rather than bug fix. But the > > > extent of the enhancement didn't seem very critical to me. Most of other > > > workloads didn't show such problem (and thus improvement). Even with the > > > workloads showing the problem, the problem was not seem so critical. > > > > > > Second, if the low accuracy is problem, users could get higher accuracy by > > > simply adjusting the sampling interval and/or aggregation interval to lower > > > value. This is the supposed way to trade the accuracy with the overhead. > > > > I disagree. There is very little chance of getting out of this situation with the > > current splitting. Changing sampling and aggregation intervals doesn't actually help. > > > > Let's draw out an example to discuss. > > > > Toy state - taking just one block of memory. > > > > 0 = not accessed page (very cold) > > X = accessed page (extremely hot) > > > > First few cycles - no accesses > > > > in X.Regions list average value estimated by damon. > > > > Region C is needed to set the max and will never be aggregated. > > > > aggregation cycle then state. > > 0.start > > 0.accessed 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 X X X > > 0.regions (percent)| A (0) | B (0) | C(1)| > > 0.merge | A | C | > > 0.split | A | B | C | > > > > After a few cycles, hot page > > 1.start > > 1.accessed 0 0 0 0 0 0 0 0 0 0 0 X 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > > 1.regions (acc_cnt)| A (1/18) | B (0) | C(1)| > > ^ not count but ratio, right? oops. Absolutely. > > > 1.merge | A | C | > > 1.split | A | B | C | > > 2.start > > 2.accessed 0 0 0 0 0 0 0 0 0 0 0 X 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > > 2.regions (acc_cnt)| A (1/12) | B (0) | C(1)| > > 2.merge | A | C | > > 2.split | A | B | C | > > 3.start > > 3.accessed 0 0 0 0 0 0 0 0 0 0 0 X 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > > 3.regions (acc_cnt)| A (0) | B (1/21) | C(1)| > > 3.merge | A | C | > > 3.split | A | B | C | > > > > Now make that 1000 pages long with the hot page at page 500. > > So the average best case we will ever get is a 1/500 * number of sample period > > between aggregations. > > So nice example, thank you! Now I understand the point. > > So, the problem is that we cannot find the small hot region near the _middle_ > because we split each region into only two subregions. Exactly. Pathological case :( > > > > > So what are the chances of failing to aggregate on the sample after we split > > at that optimal point? We need to successfully sample that one page enough that > > we get it 10% of the time. > > > > I 'think' this a case of where the 10% point is on the CDF of a binomial > > f(1/N, M) where N is number of bins and Mis number of samples. > > > > Using matlab online I think the best chance you ever get is when you take 10 samples > > and need just one of them to be in the region. > > > > p = 1 - binocdf(0,10,1/N) > > For N = 500, p = 0.0198 > > For N = 1000, p = 0.0099 > > > > Someone with better maths than me can check. > > > > Now this just got us to the point where we won't aggregate the region for one > > round of aggregation. We may split it again and if the resulting region is small > > enough might not merge it the next aggregation cycle. > > > > So I'd argue that allowing at least 2 repeats of splitting is well worth while. > > It is just a couple of additional lines of code. > > Nice suggestion, I will apply this suggestion in the next spin. It might be as > below: > > if (nr_regions() < nr_max_regions / 4) > split_into_4_regions(); > else if (nr_regions() < nr_max_regions / 2) > split_into_2_regions(); > > If this pseudo-code is missing some of your point, please let me know. That's it. My prototype was less efficient in that it just ran the 2 way split twice if we still had too few regions, but result is very nearly the same (potentially some changes in the location of the split as 10-90% both times vs whatever limits you put in the 4 region version). > > > > > > > > > Finally, I would like to keep code as simple as it can. > > > > > > For same reasons, I would like to keep the code as currently is until real user > > > problem is reported. If you have different opinions, please feel free to yell > > > at me. > > > > :) > > Appreciate your explanations and suggestions. You are welcome. Out of interest, do you have any comparative data on how 'accurate' the resulting estimates are vs a more precise heatmap from a memory trace? I'm looking at gathering such data but much happier to leverage your work if you've already done it! Thanks, Jonathan > > > Thanks, > SeongJae Park
