Consider linking to Accelerate in Apple Silicon ARM64 wheels
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Hello! I recently got a new MacBook Pro with an M2 Pro CPU (ARM64). When I ran some numerical computations (ICA to be precise), I was surprised how slow it was - way slower than e.g. my almost 10 year old Intel Mac. It turns out that the default OpenBLAS, which is what you get when installing the binary wheel with pip (i.e. "pip install numpy"), is the reason why computations are so slow. When installing NumPy from source (by using "pip install --no-binary :all: --no-use-pep517 numpy"), it uses the Apple-provided Accelerate framework, which includes an optimized BLAS library. The difference is mind-boggling, I'd even say that NumPy is pretty much unusable with the default OpenBLAS backend (at least for the applications I tested). In my test with four different ICA algorithms, I got these runtimes with the default OpenBLAS: - FastICA: 6.3s - Picard: 26.3s - Infomax: 0.8s - Extended Infomax: 1.4s Especially the second algorithm is way slower than on my 10 year old Intel Mac using OpenBLAS. Here are the times with Accelerate: - FastICA: 0.4s - Picard: 0.6s - Infomax: 1.0s - Extended Infomax: 1.3s Given this huge performance difference, my question is if you would consider distributing a binary wheel for ARM64-based Macs which links to Accelerate. Or are there any caveats why you do not want to do that? I know that NumPy moved away from Accelerate years ago on Intel Macs, but maybe now is the time to reconsider this decision. Thanks! Clemens
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On Thu, Mar 23, 2023 at 1:55 AM Clemens Brunner <clemens.brunner@gmail.com> wrote:
Hi Clemens, thanks for the suggestion and benchmarks. We actually discussed this in the last community meeting. Accelerate as of today is supported when building from source, and that will use 32-bit BLAS/LAPACK (the LP64 interface). Since NumPy 1.22 we're shipping our wheels with the 64-bit (ILP64) interface, which Accelerate doesn't provide. That's about to change though, in macOS 13.3: https://developer.apple.com/documentation/macos-release-notes/macos-13_3-rel.... That release will also upgrade to LAPACK 3.9.1, which means we can re-enable it for SciPy too. For macOS 14 we will most likely, if things go well, ship wheels linked against the new ILP64 Accelerate build. Due to packaging limitations (the `packaging` library ignores minor versions of macOS), we can't ship wheels for >=13.3, only >=14. Cheers, Ralf
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Thanks Ralf, this sounds great! Just making sure I understand, this means that for macOS 13, we have to enable Accelerate by building NumPy from source. Once macOS 13.3 is out, building SciPy from source will also link to Accelerate. Finally, Accelerate support will be enabled by default in binary wheels for NumPy and SciPy once macOS 14 is out (presumably some time in October this year). Correct? Clemens
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On Thu, Mar 23, 2023 at 10:43 AM Clemens Brunner <clemens.brunner@gmail.com> wrote:
Indeed. Either that, or use a packaging system that's more capable in this regard - conda-forge for example will give you runtime switching of BLAS and LAPACK libraries out of the box ( https://conda-forge.org/docs/maintainer/knowledge_base.html#switching-blas-i...). Several Linux distros support this too, via mechanisms like `update-alternatives` - but that won't help you much on macOS of course. Once macOS 13.3 is out, building SciPy from source will also link to
Yes, if I had to guess now then I'd say that this will be the default in NumPy 2.0 at the end of the year. Cheers, Ralf
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This sounds terrific. Is there a technique to get such a performance improvement with Accelerate? We tried: pip install numpy==1.24.3 --no-binary numpy with and without a ~/.numpy-site.cfg file that sets [accelerate] libraries = Accelerate, vecLib on Intel and M2 Macs on macOS 13.3. While np.show_config() reports that numpy is linked to Accelerate, a large dot product runs maybe twice as fast as with OpenBLAS, and our full bio simulation's performance is within measurement noise. Trying the --no-use-pep517 argument had no obvious impact. Best, Jerry On Thu, Mar 23, 2023 at 3:52 AM Ralf Gommers <ralf.gommers@gmail.com> wrote:
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On Tue, May 9, 2023 at 5:11 AM Jerry Morrison < jerry.morrison+numpy@gmail.com> wrote:
From the release notes: "To use the new interfaces, define ACCELERATE_NEW_LAPACK before including the Accelerate or vecLib headers". So you are still using the old version of the library if you did not do that. This is not entirely trivial to do now; I expect we'll see a PR to enable the new libraries quite soon. Cheers, Ralf
![](https://secure.gravatar.com/avatar/5f88830d19f9c83e2ddfd913496c5025.jpg?s=120&d=mm&r=g)
On Thu, Mar 23, 2023 at 1:55 AM Clemens Brunner <clemens.brunner@gmail.com> wrote:
Hi Clemens, thanks for the suggestion and benchmarks. We actually discussed this in the last community meeting. Accelerate as of today is supported when building from source, and that will use 32-bit BLAS/LAPACK (the LP64 interface). Since NumPy 1.22 we're shipping our wheels with the 64-bit (ILP64) interface, which Accelerate doesn't provide. That's about to change though, in macOS 13.3: https://developer.apple.com/documentation/macos-release-notes/macos-13_3-rel.... That release will also upgrade to LAPACK 3.9.1, which means we can re-enable it for SciPy too. For macOS 14 we will most likely, if things go well, ship wheels linked against the new ILP64 Accelerate build. Due to packaging limitations (the `packaging` library ignores minor versions of macOS), we can't ship wheels for >=13.3, only >=14. Cheers, Ralf
![](https://secure.gravatar.com/avatar/7dd120ff91318b892bc7315d4d433a4d.jpg?s=120&d=mm&r=g)
Thanks Ralf, this sounds great! Just making sure I understand, this means that for macOS 13, we have to enable Accelerate by building NumPy from source. Once macOS 13.3 is out, building SciPy from source will also link to Accelerate. Finally, Accelerate support will be enabled by default in binary wheels for NumPy and SciPy once macOS 14 is out (presumably some time in October this year). Correct? Clemens
![](https://secure.gravatar.com/avatar/5f88830d19f9c83e2ddfd913496c5025.jpg?s=120&d=mm&r=g)
On Thu, Mar 23, 2023 at 10:43 AM Clemens Brunner <clemens.brunner@gmail.com> wrote:
Indeed. Either that, or use a packaging system that's more capable in this regard - conda-forge for example will give you runtime switching of BLAS and LAPACK libraries out of the box ( https://conda-forge.org/docs/maintainer/knowledge_base.html#switching-blas-i...). Several Linux distros support this too, via mechanisms like `update-alternatives` - but that won't help you much on macOS of course. Once macOS 13.3 is out, building SciPy from source will also link to
Yes, if I had to guess now then I'd say that this will be the default in NumPy 2.0 at the end of the year. Cheers, Ralf
![](https://secure.gravatar.com/avatar/21f3f2d3ca8271d707aefc296052f21f.jpg?s=120&d=mm&r=g)
This sounds terrific. Is there a technique to get such a performance improvement with Accelerate? We tried: pip install numpy==1.24.3 --no-binary numpy with and without a ~/.numpy-site.cfg file that sets [accelerate] libraries = Accelerate, vecLib on Intel and M2 Macs on macOS 13.3. While np.show_config() reports that numpy is linked to Accelerate, a large dot product runs maybe twice as fast as with OpenBLAS, and our full bio simulation's performance is within measurement noise. Trying the --no-use-pep517 argument had no obvious impact. Best, Jerry On Thu, Mar 23, 2023 at 3:52 AM Ralf Gommers <ralf.gommers@gmail.com> wrote:
![](https://secure.gravatar.com/avatar/5f88830d19f9c83e2ddfd913496c5025.jpg?s=120&d=mm&r=g)
On Tue, May 9, 2023 at 5:11 AM Jerry Morrison < jerry.morrison+numpy@gmail.com> wrote:
From the release notes: "To use the new interfaces, define ACCELERATE_NEW_LAPACK before including the Accelerate or vecLib headers". So you are still using the old version of the library if you did not do that. This is not entirely trivial to do now; I expect we'll see a PR to enable the new libraries quite soon. Cheers, Ralf
participants (3)
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Clemens Brunner
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Jerry Morrison
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Ralf Gommers