@guolinke @shiyu1994 Just checking in for updates. We are awaiting this fix to unblock a release.

@svotaw will force set export OMP_NUM_THREADS=8 fix the problem in linux?

@svotaw will force set export OMP_NUM_THREADS=8 fix the problem in linux?

Not sure what you are suggesting. Are you suggesting whether that would fix it in my particular case? Or for everyone? I'm not sure we should force a fixed number of threads (and as low as 8). And according to the docs, you can override this by the local annotation in some cases. I'm not sure we should rely on an environment variable being set to fix a bug. Or are you suggesting using OMP_NUM_THREADS env var first instead of OMP_THREAD_LIMIT?

However, in investigating your question, I see an env variable for OMP_DYNAMIC, and it defaults to true. I will test what happens when that is false. That might be our issue, in the sense the multiple threads are maybe allowed to adjust their own max OpenMP threads. If so, maybe that will at least solve it in our particular case for now, but I'd still suggest that we find a permanent solution that does not rely on env var settings. Will reply with results.

okay, I see. Another solution I suggest is to dynamically increase the buffer, when tid is larger than buffer size. But this solution may slow down due to the additional if-else branching.

okay, I see. Another solution I suggest is to dynamically increase the buffer, when tid is larger than buffer size. But this solution may slow down due to the additional if-else branching.

Correct, I didn't want to adversely affect a shared critical pathway with an extra comparison, so I would rather avoid using dynamic buffer size. Also, without a fixed size, you can't generate deterministic thread ids across threads, so it ends up having thread collisions anyways.

I'm taking a better look at the OpenMP APIs now that I understand the issue better and you guys have pointed out some good responses. Should have something up today.

After a more thorough investigation, here's what I found with OpenMP:

As a reminder, what we need is for a constant that represents how many OpenMP threads each external thread will create. With this constant, we can pre-allocate sets of buffers (i.e., 1 set of X buffers for each of Y calling threads, and we need to find X and are given Y).

The ideal candidate would be omp_get_max_threads(). However, this returns a different number depending on the calling thread (our test cases get 3 and 4 respectively on 2 external threads). This seems to only happen in Linux, but that could be coincidence because of something else. They even say in the docs that you should use this if you need to make allocations, but apparently, they weren't considering an external multi-threaded environment. It kinda makes sense since OpenMP would be the multi-threading solution already for most people.

I tried all the APIs that OpenMP has to tweak thread counts: OMP_DYNAMIC, OMP_THREAD_LIMIT, OMP_NUM_THREADS, etc.
(Note: OpenMP actually recommends NOT looking at env vars directly, and using their APIs to access params, so although we discussed using env vars above, OpenMP already exposes APIs for all their params that also take into account defaults and such)

1. omp_set_dynamic() to either 0 or 1 had no effect. Even with dynamic == 0 (which was actually the default), we get different values for omp_get_max_threads() from each external thread.
2. omp_get_thread_limit() was not much use. By default, it actually returned Max(int32), which is not useful for allocation. I see no reason for us to set this manually either to something like 128 or 1024. Docs say default is implementation dependent.
3. I used omp_get_active_level() to make sure there wasn't some weirdness of nesting somehow, but both external threads were on same level.
4. as @guolinke suggested, using omp_set_num_threads(X) or parallel numThreads(X) worked, and omp_get_max_threads() returned a constant X after that. However, I don't like this solution. OpenMP and users should be free to choose thread count based on hardware and other needs, rather than us hardwiring it. We might interfere with users setting the values to other things that they want.

Here's my thoughts for a flexible solution that is better than the static constant from the first iteration of this PR:

1. We create a "new" OpenMP param for LightGBM: omp_get_streaming_max_threads(), and we default it to some reasonable value like 8 or 16. This should work in the vast majority of cases, with no user actions needed, and reduces wasted allocations (from 128 or even 1024).
2. For those special cases where this doesn't work (OpenMP has enough resources to create more threads than that), we allow overriding the default with an env var: OMP_MAX_STREAMING_THREADS. This is kind of how OpenMP already works, with params and overrides.

See the latest iteration for an example of this suggestion. We can still debate details of caching, naming, location of env var utils, etc., but this works from the more extensive testing I did. It works out-of-the-box, and still is flexible for corner cases.

@guolinke Actually, having looked at it and thought about it for another day, it might be better to choose another way to set this value. Since this isn't really an OpenMP setting, perhaps it doesn't make sense to set it in openmp_wrapper. Also, I don't really like the static var.

I can think of 2 other options:

1. As an optional argument to LGBM_InitStreaming(), defaulting to 8 or 16, and stored as a private class var in Dataset.
2. As a config option, defaulting to 8 or 16 and again stored as private class var in Dataset

I will implement #1 in another iteration when I get a chance.

@svotaw Thank you, I agree with #1

@svotaw Thank you, I agree with #1

@guolinke Done. Ready for final review then.

@guolinke @shiyu1994

I think this is the best fix, although of course you are free to comment. I believe it's ready for checkin, other than your comment on whether we should use 8 or 16 as a default (see TODO in dataset.h). Note the failing R test is most likely a flake.

It seems that some cpp tests are failing. Will look into this tomorrow.

Let us fix the CI next

Thanks for the signoff and feedback! Just to be clear, is this a general CI problem, or something related to this PR? (I assume the former, but making sure)

is this a general CI problem, or something related to this PR

Please update to latest master. If you see any CI failures after doing that, they're likely related to this PR's changes, and you'll need to address them.

To be clear, we never merge PRs in this repo where CI is failing, even if the failures seem unrelated to the PR's changes.

sure, I guess I meant is this something I need to merge a fix for or something that the backend pipeline just needs to be re-run? I merged from master.

After sync with main, seeing the below error in a few R tests. I will try a re-run to confirm it's real.

The downloaded binary packages are in
C:\Users\runneradmin\AppData\Local\Temp\RtmpgztNMe\downloaded_packages
Downloading https://github.com/microsoft/LightGBM/releases/download/v2.0.12/miktexsetup-5.2.0-x64.zip
Setting up MiKTeX
miktexsetup_standalone: Timeout was reached
miktexsetup_standalone: Data: code="28", url="https://api2.miktex.org/hello"
Error: Process completed with exit code -1.

I fixed all the tests, except for the R tests which are failing due to MikTeX failing somehow. If that's something related to this PR, can someone point me to a possible cause? I don't know anything about MikTeX.

except for the R tests which are failing due to MikTeX failing somehow

That looks unrelated to this PR's changes, as we're seeing it elsewhere on PRs and master. See #5600.

@jameslamb Can this be checked in?

I'll merge this, based on @guolinke 's approval.

Normally I'd label a change like this, which adds a new required argument to a public API in c_api.h, a "breaking" change, but I think fix is a fine categorization given that the LGBM_DatasetInitStreaming() was just introduced in #5299 and has never been part of a LightGBM release.

Thanks for the help!

This pull request has been automatically locked since there has not been any recent activity since it was closed. To start a new related discussion, open a new issue at https://github.com/microsoft/LightGBM/issues including a reference to this.