Rebuild for CUDA 12#148
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The transition to CUDA 12 SDK includes new packages for all CUDA libraries and build tools. Notably, the cudatoolkit package no longer exists, and packages should depend directly on the specific CUDA libraries (libcublas, libcusolver, etc) as needed. For an in-depth overview of the changes and to report problems [see this issue]( conda-forge/conda-forge.github.io#1963 ). Please feel free to raise any issues encountered there. Thank you! 🙏
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Hi! This is the friendly automated conda-forge-linting service. I just wanted to let you know that I linted all conda-recipes in your PR ( |
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@conda-forge-admin, please rerender |
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Hi! This is the friendly automated conda-forge-linting service. I just wanted to let you know that I linted all conda-recipes in your PR ( |
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@conda-forge-admin, please rerender |
…nda-forge-pinning 2024.08.09.05.46.50
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Haven't seen such a failure before: Looks like this is a known issue and we need to point to |
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I gather from the diff that the changes here cover Windows but Windows support isn't added? |
The migrator would be adding CUDA 12.0 builds on windows, if windows weren't skipped completely here. That's okay though, it's just the default title of PRs opened by this migrator. Actual windows enablement should be done independently from this PR. |
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OK, moved past the I cannot tell from the recipe where things would refer to |
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Sorry for the slow reply here Axel Discussed this with my colleagues today When we have seen similar issues before, they have tended to trace back to using the legacy CMake Am not entirely sure the right place to look at the source code for ambertools, but was able to find the Amber-MD GitHub org, which references the webpage ( https://ambermd.org/ ) used in downloads here ambertools-feedstock/recipe/meta.yaml Line 15 in 725d666 Looking in that org do see usage of As an interesting note did see this comment in that ambertools code: # With CMake 3.7, FindCUDA.cmake crashes when crosscompiling.
if(CROSSCOMPILE)
message(STATUS "CUDA disabled when crosscompiling.")
set(CUDA FALSE)
else()One of the things the CMake team solved by adding the CUDA language and Think to move this forward, would recommend working with upstream to adopt these changes. Possibly the build here can be patched to use those upstream changes (though it may be simpler to update to a new release with the build fixes) cc @robertmaynard @bdice (for awareness & in case revisions to the above are needed) |
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As far as I recall, the canonical source code is non-public and on GitLab. But it's several projects stapled together, including cc: @dacase who is likely the best person to coordinate making any needed changes away from deprecated calls |
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Thanks for the analysis John! |
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So I downloaded the tarball (man there's a lot of stuff in there; a cool 3GB when unpacked, and a mass of vendored bits), and searched for the occurrences of Given that there's only 4, this sounds quite patchable. |
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Am renaming the PR to avoid further confusion. Hope that is ok |
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Well, I'm several patches deep into trying to make this work, and I think I'm hitting a CMake bug. Surely it would be better to do less hacky changes in AmberTools upstream; I was mainly trying to see what would be necessary to unblock the build and tried to keep patching ~minimal, at least conceptually (feel free to pick up anything, though these were not really written with being upstreamed in mind - not least because there's no public repo to contribute to - but rather as the most immediately necessary fixes to overcome the failures here). |
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Just to avoid any confusion - this PR would have to be for AmberTools 23 until #141 or a similar build is complete, so using the |
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Am deeply impressed by the amount of effort you spent patching here Axel! 🙏 Subscribed to that issue. Though it looks like my colleague Rob already replied to you over there. Agree with him we likely need That all being said, agree this is work probably best taken on upstream. Think the other pieces you included here are a good starting point for anyone wanting to push this forward Agreed Matt. Was trying to capture that in my comments above. Apologies if that was too muddled with other details |
This is what I've been doing, the sources are unchanged in this PR. |
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👍 yep just wanted to be sure we were all on the same page, that comment was mostly to explain to David why this is being applied to 23, not 24 |
while languages usually get defined around where the (sub)project has its own CMakeLists.txt, this still doesn't work, so move it to the very top
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Well, I got things to build, but then run into: |
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Does the header in question have That seems like the kind of thing we would need. It is also covered in this blogpost Also worth noting this header lives in |
There was a problem hiding this comment.
Does the header in question have
#include <cooperative_groups.h>?
Actually, looking at the source code, it does something like this:
#ifdef USE_LEGACY_ATOMICS
QUICKULL val1 = (QUICKULL) (fabs( _tmp * OSCALE) + (QUICKDouble)0.5);
if ( _tmp * weight < (QUICKDouble)0.0)
val1 = 0ull - val1;
QUICKADD(devSim_dft.DFT_calculated[0].Eelxc, val1);
#else
atomicAdd(&devSim_dft.DFT_calculated[0].Eelxc, _tmp);
#endifThe header is missing though, so realistically only the USE_LEGACY_ATOMICS branch has a chance of working.
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@conda-forge-admin, please rerender |
…nda-forge-pinning 2024.10.10.05.31.44
looks like there is an extra or missing |
* test if we can build 23 still * MNT: Re-rendered with conda-build 24.3.0, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.07.19.05.24 * MNT: Re-rendered with conda-build 25.1.1, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.07.19.05.24 * see if things work without installing csh into the env * MNT: Re-rendered with conda-build 25.1.1, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.07.19.05.24 * turn off gui build * MNT: Re-rendered with conda-build 25.1.2, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.07.19.05.24 * don't skip older cuda builds, lets see if we can patch it * MNT: Re-rendered with conda-build 25.1.2, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.10.18.05.55 * build build number * pull in changes from #148 (thanks @h-vetinari ) * MNT: Re-rendered with conda-build 25.1.2, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.10.18.05.55 * add cuda 12.6 support * lets see what happens if we allow newer clang * that didn't fix the cxx detection issue * pin cmake to older version that worked in the past * don't pin cmake and use newest clang * MNT: Re-rendered with conda-build 25.1.2, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.12.12.48.03 * see if the patches are doing more harm then good * still need to remove nab2c * naive find and replace mtune with march * didn't end up needed to use FC in host tools, but added for completness * replace mtune with mcpu * crazy hack to check PoC * see if -march=armv8.3-a works for clang and gfortran * do a verbose build to try and figure out where we are missing an arch flag * guard if cd fails, but also cd into correct dir before we build the package * try setting LDFLAGS -arch arm64 * fix LDFLAGS export (not sure why { was treated as literal * see if any hacks are hurting us here * try adding -arch arm64 to help ld understand what arch we are trying to build * set correct arch * TODO patch cmake/TargetArch.cmake * try and patch cmake/TargetArch.cmake * fix patch * forgot we need to fix with our hack arm64-apple-darwin20.0: error: unsupported argument 'native' to option '-mtune=' * see if telling cmake we are crosscompling helps -- it this doesn't work I have another idea * see if setting TARGET_TRIPLE is enough * if these cmake flags don't work we will do plan b * see if it likes armv8.3-a more than arm64 * it this doesn't work we will add the linker flags by hand * switch around flags to correct ones * see if this gets us back to linker error * yolo * bump ci * see if adding the arch flags to setup.py for sander and cpptraj fixes it * don't reset CC and CXX in setup.py files * skip cuda builds * MNT: Re-rendered with conda-build 25.1.2, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.19.18.36.33 * see if adding mkl to run will fix issues with linux openmpi builds * check python 3.13 builds * MNT: Re-rendered with conda-build 25.1.2, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.19.18.36.33 * skip python 3.13 builds and add mkl as a run time dep --------- Co-authored-by: conda-forge-webservices[bot] <91080706+conda-forge-webservices[bot]@users.noreply.github.com>
This PR has been triggered in an effort to update cuda120.
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