🍏 Make Thinc faster on macOS by calling into Apple's native Accelerate library

Overview

thinc-apple-ops

Make spaCy and Thinc up to 8 × faster on macOS by calling into Apple's native libraries.

Install

Make sure you have Xcode installed and then install with pip:

pip install thinc-apple-ops

🏫 Motivation

Matrix multiplication is one of the primary operations in machine learning. Since matrix multiplication is computationally expensive, using a fast matrix multiplication implementation can speed up training and prediction significantly.

Most linear algebra libraries provide matrix multiplication in the form of the standardized BLAS gemm functions. The work behind scences is done by a set of matrix multiplication kernels that are meticulously tuned for specific architectures. Matrix multiplication kernels use architecture-specific SIMD instructions for data-level parallism and can take factors such as cache sizes and intstruction latency into account. Thinc uses the BLIS linear algebra library, which provides optimized matrix multiplication kernels for most x86_64 and some ARM CPUs.

Recent Apple Silicon CPUs, such as the M-series used in Macs, differ from traditional x86_64 and ARM CPUs in that they have a separate matrix co-processor(s) called AMX. Since AMX is not well-documented, it is unclear how many AMX units Apple M CPUs have. It is certain that the (single) performance cluster of the M1 has an AMX unit and there is empirical evidence that both performance clusters of the M1 Pro/Max have an AMX unit.

Even though AMX units use a set of undocumented instructions, the units can be used through Apple's Accelerate linear algebra library. Since Accelerate implements the BLAS interface, it can be used as a replacement of the BLIS library that is used by Thinc. This is where the thinc-apple-ops package comes in. thinc-apple-ops extends the default Thinc ops, so that gemm matrix multiplication from Accelerate is used in place of the BLIS implementation of gemm. As a result, matrix multiplication in Thinc is performed on the fast AMX unit(s).

Benchmarks

Using thinc-apple-ops leads to large speedups in prediction and training on Apple Silicon Macs, as shown by the benchmarks below.

Prediction

This first benchark compares prediction speed of the de_core_news_lg spaCy model between the M1 with and without thinc-apple-ops. Results for an Intel Mac Mini and AMD Ryzen 5900X are also provided for comparison. Results are in words per second. In this prediction benchmark, using thinc-apple-ops improves performance by 4.3 times.

CPU BLIS thinc-apple-ops Package power (Watt)
Mac Mini (M1) 6492 27676 5
MacBook Air Core i5 2020 9790 10983 9
AMD Ryzen 5900X 22568 N/A 52

Training

In the second benchmark, we compare the training speed of the de_core_news_lg spaCy model (without NER). The results are in training iterations per second. Using thinc-apple-ops improves training time by 3.0 times.

CPU BLIS thinc-apple-ops Package power (Watt)
Mac Mini M1 2020 3.34 10.07 5
MacBook Air Core i5 2020 3.10 3.27 10
AMD Ryzen 5900X 6.53 N/A 53
Comments
  • Pass through Accelerate sgemm/saxpy in Ops.cblas

    Pass through Accelerate sgemm/saxpy in Ops.cblas

    This can be used by e.g. the parser in spaCy 3.4 to use Accelerate's implementations.

    I am not sure how to handle this dependency-wise, since this requires Thinc 8.1, but we still want to people to be able to use thinc-apple-ops with Thinc 8.0.x and spaCy < 3.4. Do we need another minor release that sets thinc < 8.1.0?

    opened by danieldk 5
  • IndexError: Out of bounds on buffer access (axis 1)

    IndexError: Out of bounds on buffer access (axis 1)

    Hi I tried to use this awesome package and I am getting this error. Not sure what it means, maybe you guys could help me?

    I should mention that my data is quite big and I am also using some SWAP space. Could this be the reason of this error?

    [2021-09-28 21:09:01,238] [INFO] Set up nlp object from config
    [2021-09-28 21:09:01,500] [INFO] Pipeline: ['tok2vec', 'ner', 'sentencizer', 'entity_linker']
    [2021-09-28 21:09:01,505] [INFO] Created vocabulary
    [2021-09-28 21:09:01,505] [INFO] Finished initializing nlp object
    Traceback (most recent call last):
      File "/Users/joozty/Documents/kolurbo/venv/bin/spacy", line 8, in <module>
        sys.exit(setup_cli())
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/spacy/cli/_util.py", line 69, in setup_cli
        command(prog_name=COMMAND)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/click/core.py", line 1137, in __call__
        return self.main(*args, **kwargs)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/click/core.py", line 1062, in main
        rv = self.invoke(ctx)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/click/core.py", line 1668, in invoke
        return _process_result(sub_ctx.command.invoke(sub_ctx))
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/click/core.py", line 1404, in invoke
        return ctx.invoke(self.callback, **ctx.params)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/click/core.py", line 763, in invoke
        return __callback(*args, **kwargs)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/typer/main.py", line 500, in wrapper
        return callback(**use_params)  # type: ignore
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/spacy/cli/train.py", line 60, in train_cli
        nlp = init_nlp(config, use_gpu=use_gpu)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/spacy/training/initialize.py", line 84, in init_nlp
        nlp.initialize(lambda: train_corpus(nlp), sgd=optimizer)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/spacy/language.py", line 1272, in initialize
        proc.initialize(get_examples, nlp=self, **p_settings)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/spacy/pipeline/tok2vec.py", line 216, in initialize
        self.model.initialize(X=doc_sample)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc/model.py", line 299, in initialize
        self.init(self, X=X, Y=Y)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc/layers/chain.py", line 86, in init
        layer.initialize(X=curr_input, Y=Y)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc/model.py", line 299, in initialize
        self.init(self, X=X, Y=Y)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc/layers/chain.py", line 90, in init
        curr_input = layer.predict(curr_input)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc/model.py", line 315, in predict
        return self._func(self, X, is_train=False)[0]
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc/layers/concatenate.py", line 44, in forward
        Ys, callbacks = zip(*[layer(X, is_train=is_train) for layer in model.layers])
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc/layers/concatenate.py", line 44, in <listcomp>
        Ys, callbacks = zip(*[layer(X, is_train=is_train) for layer in model.layers])
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc/model.py", line 291, in __call__
        return self._func(self, X, is_train=is_train)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/spacy/ml/staticvectors.py", line 46, in forward
        vectors_data = model.ops.gemm(model.ops.as_contig(V[rows]), W, trans2=True)
      File "/Users/joozty/Documents/kolurbo/venv/lib/python3.9/site-packages/thinc_apple_ops/ops.py", line 25, in gemm
        C = blas.gemm(x, y, trans1=trans1, trans2=trans2)
      File "thinc_apple_ops/blas.pyx", line 37, in thinc_apple_ops.blas.gemm
      File "thinc_apple_ops/blas.pyx", line 53, in thinc_apple_ops.blas.gemm
    IndexError: Out of bounds on buffer access (axis 1)
    

    Info about spaCy

    • spaCy version: 3.1.3
    • Platform: macOS-11.6-arm64-arm-64bit
    • Python version: 3.9.7
    • Pipelines: en_core_web_sm (3.1.0), en_core_web_md (3.1.0)
    opened by Joozty 2
  • Can't compile thinc on Macbook Air M1

    Can't compile thinc on Macbook Air M1

    Hello, I find myself unable to compile this otherwise magnificent tool! Please help, if you can!

    I am on MacOS 12.1, Kernel Version 21.2.0, and have installed the latest Python (3.10.2)

    Here is the error message I get after trying to install with pip (apparently it can't find the Accelerate Libraries, especially Accelerate.h Header ...):

    ERROR: Command errored out with exit status 1: command: /Library/Frameworks/Python.framework/Versions/3.10/bin/python3.10 /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_vendor/pep517/in_process/_in_process.py build_wheel /var/folders/n7/t2plqm6n2jq4khmj0bckswg40000gq/T/tmp0bhlw2sh cwd: /private/var/folders/n7/t2plqm6n2jq4khmj0bckswg40000gq/T/pip-install-wgga78t9/thinc-apple-ops_f5b38888c7a149cd9f99fd524c2bd340 Complete output (34 lines): running bdist_wheel running build running build_py creating build creating build/lib.macosx-10.9-universal2-3.10 creating build/lib.macosx-10.9-universal2-3.10/thinc_apple_ops copying thinc_apple_ops/init.py -> build/lib.macosx-10.9-universal2-3.10/thinc_apple_ops copying thinc_apple_ops/ops.py -> build/lib.macosx-10.9-universal2-3.10/thinc_apple_ops creating build/lib.macosx-10.9-universal2-3.10/thinc_apple_ops/tests copying thinc_apple_ops/tests/init.py -> build/lib.macosx-10.9-universal2-3.10/thinc_apple_ops/tests copying thinc_apple_ops/tests/test_gemm.py -> build/lib.macosx-10.9-universal2-3.10/thinc_apple_ops/tests running egg_info warning: no files found matching '.pxd' under directory 'thinc_apple_ops' warning: no files found matching '.txt' under directory 'thinc_apple_ops' writing manifest file 'thinc_apple_ops.egg-info/SOURCES.txt' copying thinc_apple_ops/blas.pyx -> build/lib.macosx-10.9-universal2-3.10/thinc_apple_ops copying thinc_apple_ops/py.typed -> build/lib.macosx-10.9-universal2-3.10/thinc_apple_ops running build_ext creating build/temp.macosx-10.9-universal2-3.10 creating build/temp.macosx-10.9-universal2-3.10/thinc_apple_ops clang -Wno-unused-result -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -fwrapv -O3 -Wall -arch arm64 -arch x86_64 -g -I/private/var/folders/n7/t2plqm6n2jq4khmj0bckswg40000gq/T/pip-build-env-b0flamc2/overlay/lib/python3.10/site-packages/numpy/core/include -I/Library/Frameworks/Python.framework/Versions/3.10/include/python3.10 -c thinc_apple_ops/blas.c -o build/temp.macosx-10.9-universal2-3.10/thinc_apple_ops/blas.o In file included from thinc_apple_ops/blas.c:706: In file included from /private/var/folders/n7/t2plqm6n2jq4khmj0bckswg40000gq/T/pip-build-env-b0flamc2/overlay/lib/python3.10/site-packages/numpy/core/include/numpy/arrayobject.h:5: In file included from /private/var/folders/n7/t2plqm6n2jq4khmj0bckswg40000gq/T/pip-build-env-b0flamc2/overlay/lib/python3.10/site-packages/numpy/core/include/numpy/ndarrayobject.h:12: In file included from /private/var/folders/n7/t2plqm6n2jq4khmj0bckswg40000gq/T/pip-build-env-b0flamc2/overlay/lib/python3.10/site-packages/numpy/core/include/numpy/ndarraytypes.h:1960: /private/var/folders/n7/t2plqm6n2jq4khmj0bckswg40000gq/T/pip-build-env-b0flamc2/overlay/lib/python3.10/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-W#warnings] #warning "Using deprecated NumPy API, disable it with "
    ^ thinc_apple_ops/blas.c:714:10: fatal error: 'Accelerate/Accelerate.h' file not found #include "Accelerate/Accelerate.h" ^~~~~~~~~~~~~~~~~~~~~~~~~ thinc_apple_ops/blas.c:714:10: note: did not find header 'Accelerate.h' in framework 'Accelerate' (loaded from '/System/Library/Frameworks') 1 warning and 1 error generated. error: command '/Library/Developer/CommandLineTools/usr/bin/clang' failed with exit code 1

    ERROR: Failed building wheel for thinc-apple-ops Failed to build thinc-apple-ops ERROR: Could not build wheels for thinc-apple-ops, which is required to install pyproject.toml-based projects

    ------------------------------------------ END---------------------------------------------------------------------------

    Any help would be greatly appreciated, thanks!

    duplicate 
    opened by amal1us 1
  • AppleOps.gemm: write in-place when `output` is given

    AppleOps.gemm: write in-place when `output` is given

    NumpyOps.gemm (with BLIS) writes the result of matrix multiplication in-place when the output argument is given. This changes AppleOps.gemm to do the same, avoiding allocation of a temporary.

    enhancement 
    opened by danieldk 0
  • Change thinc upper bound to <8.1.0

    Change thinc upper bound to <8.1.0

    thinc-apple-ops will require thinc >= 8.1.0 in the future for the CBLAS passthrough functionality. As discussed in #15, we should first do another minor thinc-apple-ops release specifically for thinc <8.1.0.

    Also bump the version to v0.0.7 to prepare for the release.

    opened by danieldk 0
  • Fix 0-size arrays

    Fix 0-size arrays

    Our bit of Cython code uses memory buffers, which apparently have a bounds-check when the size is 0 when acquiring the pointer. In contrast, in other bits of code we often acquire the buffer by casting the array.data pointer, which has no such bounds check. This led to IndexError being raised when zero shapes were passed through.

    opened by honnibal 0
  • Require thinc with ops registry

    Require thinc with ops registry

    Technically it doesn't require a currently unreleased version of thinc to run, but if people install it into an existing venv, then it's better to require the version of thinc to upgraded so that it's detected and used.

    opened by adrianeboyd 0
Releases(v0.1.3)
Owner
Explosion
A software company specializing in developer tools for Artificial Intelligence and Natural Language Processing
Explosion
Algorand Python API examples

Algorand-Py Algorand Python API examples This repo will hold example scripts to monitor activities on Algorand main net. You can: Monitor your assets

Karthik Dutt 2 Jan 23, 2022
A supercharged version of paperless: scan, index and archive all your physical documents

Paperless-ng Paperless (click me) is an application by Daniel Quinn and contributors that indexes your scanned documents and allows you to easily sear

Jonas Winkler 5.3k Jan 09, 2023
A collection of full-stack resources for programmers.

A collection of full-stack resources for programmers.

Charles-Axel Dein 22.3k Dec 30, 2022
TMTC Commander Core

This commander application was first developed by KSat for the SOURCE project to test the on-board software but has evolved into a more generic tool for satellite developers to perform TMTC (Telemetr

robamu 8 Dec 14, 2022
This is the community maintained fork of ungleich's cdist (after f061fb1).

cdist This is the community maintained fork of ungleich's cdist (after f061fb1). Work is split between three repositories: cdist - implementation of t

cdist community edition 0 Aug 02, 2022
Design-by-contract in Python3 with informative violation messages and inheritance

icontract icontract provides design-by-contract to Python3 with informative violation messages and inheritance. It also gives a base for a flourishing

275 Jan 02, 2023
Project5 Data processing system

Project5-Data-processing-system User just needed to copy both these file to a folder and open Project5.py using cmd or using any python ide. It is to

1 Nov 23, 2021
Here is my Senior Design Project that I implemented to graduate from Computer Engineering.

Here is my Senior Design Project that I implemented to graduate from Computer Engineering. It is a chatbot made in RASA and helps the user to plan their vacation in the Turkish language. In order to

Ezgi Subaşı 25 May 31, 2022
Alternative StdLib for Nim for Python targets

Alternative StdLib for Nim for Python targets, hijacks Python StdLib for Nim

Juan Carlos 100 Jan 01, 2023
Cup Noodle Vending Maching Ordering Queue

Noodle-API Cup Noodle Vending Machine Ordering Queue Install dependencies in virtual environment python3 -m venv

Jonas Kazlauskas 1 Dec 09, 2021
Python language from the beginning.

Python For Beginners Python Programming Language ♦️ Python is a very powerful and user friendly programming language. ❄️ ♦️ There are some basic sytax

Randula Yashasmith Mawaththa 6 Sep 18, 2022
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and

Yimeng.Zhang 968 Dec 29, 2022
An animal facts python module

An animal facts python module

Fayas Noushad 3 Dec 19, 2021
A set of scripts for a two-step procedure to measure the value of access to destinations across several modes of travel within a geographic area.

A set of scripts for a two-step procedure to measure the value of access to destinations across several modes of travel within a geographic area.

Institute for Transportation and Development Policy 2 Oct 16, 2022
Programmatic interface to Synapse services for Python

A Python client for Sage Bionetworks' Synapse, a collaborative, open-source research platform that allows teams to share data, track analyses, and collaborate

Sage Bionetworks 54 Dec 23, 2022
Final Fantasy XIV Auto House Clicker

Final Fantasy XIV Auto House Clicker

KanameS 0 Mar 31, 2022
Discover and load entry points from installed packages

Entry points are a way for Python packages to advertise objects with some common interface. The most common examples are console_scripts entry points,

Thomas Kluyver 69 Jul 05, 2022
Developing a python based app prototype with KivyMD framework for a competition :))

Developing a python based app prototype with KivyMD framework for a competition :))

Jay Desale 1 Jan 10, 2022
personal dotfiles for rolling release linux distros

dotfiles Screenshots: Directions: Deploy my dotfiles with yadm Packages from arch listed in .installed-packages Information on osu! see ~/Games/osu!/.

-pacer- 0 Sep 18, 2022
A simple way to read and write LAPS passwords from linux.

A simple way to read and write LAPS passwords from linux. This script is a python setter/getter for property ms-Mcs-AdmPwd used by LAPS inspired by @s

Podalirius 36 Dec 09, 2022