MindSpore SPONGE Documents ============================= MindSpore SPONGE is a computative biology suite based on MindSpore, supporting common functions such as molecular dynamics and protein folding. The molecular simulation or modeling process has a high degree of logic consistency with the AI model training/inferring process, so the molecular simulation can in principle be unified with the AI training/inferring mode. MindSpore SPONGE integrates molecular simulation and AI training/inferring under the same programming structure. The overall structure view is as follows: .. figure:: ./intro/images/archi.png :alt: MindSpore SPONGE Architecture MindSpore SPONGE Architecture Different from traditional molecular simulation software, AI molecular simulation library has completely new features, such as: 1. Instead of manual derivative programming, automatic differential technology provides a unified programming paradigm for different energy functions or the construction of complex scoring functions; 2. Fully compatible with neural network models, supporting AI inferring within molecular simulation, or simulation as an engine for AI training; 3. The end-to-end differentiable modeling method can realize the meta-optimization of the physical model; 4. Hierarchical code architecture, using efficient language operator at the bottom; Provide users with object-oriented Python API to facilitate user customization; 5. Automatic adaptation of multiple back-end. Users only need to write a simple Python code to accelerate execution on multiple back-end, such as GPU and NPU; 6. High-throughput simulation supported by automatic parallel. Users do not need to distinguish between single or multi-machine execution of code, can concurrently simulate multiple systems on a single hardware unit, without special MPI programming. Combined with these new features, the unified framework of molecular simulation and AI can support a wide range of molecular modeling and application scenarios, such as: - Molecular simulation based on AI improved force field or enhanced sampling; - Data-driven & physics-driven molecular docking; - Protein structure prediction and force field optimization; - High throughput molecular simulation; - Molecular design, etc. Code repository address: Installation ------------ Recommended Hardware ~~~~~~~~~~~~~~~~~~~~ +---------------+-----------------+--------+ | Hardware | os | Status | +===============+=================+========+ | Ascend 910 | Ubuntu-x86 | ✔️ | +---------------+-----------------+--------+ | | Ubuntu-aarch64 | ✔️ | +---------------+-----------------+--------+ | | EulerOS-aarch64 | ✔️ | +---------------+-----------------+--------+ | | CentOS-x86 | ✔️ | +---------------+-----------------+--------+ | | CentOS-aarch64 | ✔️ | +---------------+-----------------+--------+ | GPU CUDA 10.1 | Ubuntu-x86 | ✔️ | +---------------+-----------------+--------+ Dependency ~~~~~~~~~~ - Python>=3.7 - MindSpore>=2.0 Please refer to `MindSpore installation tutorial `__. source code install ~~~~~~~~~~~~~~~~~~~ .. code:: git clone https://gitee.com/mindspore/mindscience.git -b r0.2.0 cd mindscience/MindSPONGE - dependency install .. code:: bash pip install -r requirements.txt - Ascend backend Enable ``c`` if you want to use Cybertron. .. code:: bash bash build.sh -e ascend -c on - GPU backend Enable ``c`` if you want to use Cybertron. Enable ``t`` if you want to use traditional MD. .. code:: bash export CUDA_PATH={your_cuda_path} bash build.sh -e gpu -j32 -t on -c on - Install whl package .. code:: bash cd output/ pip install mindsponge*.whl pip install cybertron*.whl # if "-c on" is used SIG --- CO-CHAIR ~~~~~~~~ - Shenzhen Bay Laboratory `Yi Isaac Yang `__ - Chang Ping Laboratory `Jun Zhang `__ - Chang Ping Laboratory `Sirui Liu `__ Special Interesting Group ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ MindSpore SPONGE SIG (Special Interesting Group) is a team composed of a group of people who are interested and have a mission to make achievements in the field of AI × biological computing. MindSpore SPONGE SIG group provides efficient and easy-to-use AI computational biology software for researchers, teachers and students, and provides a platform for people with strong abilities or strong interests in this field to communicate and cooperate together. At present, the SIG group has six core teachers. After members joining the SIG group, our teachers will lead the team to carry out scientific research and develop the software function development. Of course, members are also welcome to do research on their own topics using MindSpore SPONGE. In the SIG group, we will hold various activities, including summer school, public lecture, technology communication meeting and other large-scale activities. Small-scale activities like weekly meetings, blogs writing will also be held in the group. By joining the activities, there will be lots of chances to communicate with our experts. During the summer school program ended on August 15th, we invited 13 teachers to have a five-day lecture mainly including three themes of MindSpore basics, molecular dynamics and advanced AI × Science courses. You can get the replay `here `__. In the SIG group, we will also release the public intelligence task and `open source internship task `__, welcome everyone to claim it. Core Contributor ~~~~~~~~~~~~~~~~ - `Yi Qin Gao Research Group `__: `Yi Isaac Yang `__, `Jun Zhang `__, `Sirui Liu `__, `Yijie Xia `__, `Diqing Chen `__, `Yu-Peng Huang `__. Contribution Guide ------------------ - Please click here to see how to contribute your code:\ `Contribution Guide `__ .. toctree:: :glob: :maxdepth: 1 :caption: Molecular Simulation Introduction intro/physics_driven intro/data_driven intro/physics_plus_data_driven .. toctree:: :glob: :maxdepth: 1 :caption: User Guide user/simulation user/structure_prediction user/property_prediction user/design user/basic .. toctree:: :maxdepth: 1 :caption: API References mindsponge.cell mindsponge.common mindsponge.data mindsponge.metrics constant .. toctree:: :glob: :maxdepth: 1 :caption: RELEASE NOTES RELEASE