WARNING: Only use with M1/M2-series for now. This plugin has not been fully tested on Intel Macs and seems to cause bugs there.
This plugin adds the Metal platform that accelerates OpenMM on Metal 3 GPUs. It supports Apple, AMD, and Intel GPUs running macOS 13* or higher. The current implementation uses Apple's OpenCL compatiblity layer (cl2Metal) to translate OpenCL kernels to AIR. Its current focus is implementing patches for OpenMM's code base that improve performance on macOS. It distributes the patches in a way easily accessible to most users, who would otherwise wait for them to be upstreamed. As a beta version of the patches, this may cause unexpected bugs or performance regressions.
* The current version supports macOS Monterey. Ventura will only be required after the transition to Metal.
The Metal plugin will eventually transition kernels directly to the Metal API. Doing so enables optimizations like SIMD-group reductions and indirect command buffers, but removes double precision support on AMD GPUs. Before the transition, double and/or mixed precision will be deactivated. The plugin will eventually use double-single FP64 emulation to bring back mixed, this time supporting all GPUs.
Another goal is to support machine learning potentials, similar to openmm-torch. This repository should provide a more direct pathway to MPSGraph, the high-level MLIR compiler harnessed by tensorflow-metal and PyTorch. The plugin should create API (e.g. MPSGraphForce) for extracting the MTLBuffer backing an OpenMM class. The API should also facilitate construction of MPSGraphTensor and MPSGraphTensorData instances from the buffer. The ML potential (written in C++) should be made accessible from Swift - the language for using MPSGraph. Swift code will access all other OpenMM APIs through PythonKit.
In Finder, create an empty folder and right-click it. Select New Terminal at Folder from the menu, which launches a Terminal window. Copy and enter the following commands one-by-one.
conda install -c conda-forge openmm
git clone https://github.com/openmm/openmm
git clone https://github.com/philipturner/openmm-metal
cd openmm-metal
bash build.sh
PLUGINS_DIR=/usr/local/openmm/lib/plugins
# requires password
sudo mkdir -p $PLUGINS_DIR
libs=(libOpenMMMetal libOpenMMAmoebaMetal libOpenMMDrudeMetal libOpenMMRPMDMetal)
for lib in $libs; do sudo cp ".build/${lib}.dylib" "$PLUGINS_DIR/${lib}.dylib"; doneNext, you will benchmark OpenCL against Metal. In your originally empty folder, enter openmm/examples. Arrange the files by name and locate benchmark.py. Then, open the file with TextEdit or Xcode. Modify the top of the script as shown below:
from __future__ import print_function
import openmm.app as app
import openmm as mm
import openmm.unit as unit
from datetime import datetime
import argparse
import os
# What you need to add:
mm.Platform.loadPluginsFromDirectory(mm.Platform.getDefaultPluginsDirectory())
# Rest of the code:
def cpuinfo():
"""Return CPU info"""Press Cmd + S to save. Back at the Terminal window, type the following commands:
cd ../
cd openmm
cd examples
python3 benchmark.py --test apoa1rf --seconds 15 --platform OpenCL
python3 benchmark.py --test apoa1rf --seconds 15 --platform HIP
OpenMM's current energy minimizer hard-codes checks for the CUDA, OpenCL, and HIP platforms. The Metal backend is currently labeled HIP everywhere to bypass this limitation. The plugin name will change to Metal after the next OpenMM version release, which fixes the issue. To prevent source-breaking changes, check for both the HIP and Metal backends in your client code.
TODO: For user convenience, attach pre-compiled binaries and install.sh to the first official release. The installer automatically finds the best binary version (based on macOS version compatibility) and the correct architecture. Then, it downloads and checks SHA256. Finally, make a way to query the version of each currently installed binary (e.g. a dynamically loaded symbol, text file in installation directory).
Expect a 100-250% speedup depending on your workload.
The Metal Platform uses OpenMM API under the terms of the MIT License. A copy of this license may be found in the accompanying file MIT.txt.
The Metal Platform is based on the OpenCL Platform of OpenMM under the terms of the GNU Lesser General Public License. A copy of this license may be found in the accompanying file LGPL.txt. It in turn incorporates the terms of the GNU General Public License, which may be found in the accompanying file GPL.txt.
The Metal Platform uses VkFFT by Dmitrii Tolmachev under the terms of the MIT License. A copy of this license may be found in the accompanying file MIT-VkFFT.txt.