To join the sprint, please bring your laptop and sign up. You are also very welcome to bring your project. Please contact us if you have any questions.
Scisprint, hosted by the sciwork community, is a monthly coding sprint. It is a place to facilitate discussions and exchange information among people in the fields of science, numerical computation, and engineering. Participants, regardless of experience level, can gain valuable development insights in this event.
We would like to provide a supportive and friendly environment for all attendees to support more developers to join in the open-source communities.
This event includes a hacking session.
It aims to encourage collaboration and interaction among developers through project participation. The projects cover various fields, including but not limited to science, numerical computation, and engineering. You are also encouraged to share your own projects in scisprint. Refer to project list below for more details.
modmesh seamlessly mixes C++ and Python through pybind11, allowing you to leverage the strengths of both programming languages for efficient PDE solving. We use Qt and Python to visualize the computation results to give you a better understanding of your PDE solution. modmesh also supports mesh visualization, currently in the Gmsh mesh file format. We have recently made efforts to improve the modmesh UI/UX.
The design allows it to run on Windows, Linux, and MacOS. Everyone can use or contribute to modmesh.
uTensor is an extremely lightweight machine learning inference framework built on C++11. It simplifies model deployment by seamlessly converting TensorFlow-trained models into efficient C++ files that can be used to infer on the embedding device and integrate with optimized libraries such as CMSIS-NN by ARM with ease. Compared with the binary files, C++ source code will provide greater flexibility to modify the trained model for the embedding engineers.
We provide the defaults for tensors, operators, and memory allocation. Just like the booming development of machine learning, we are also actively developing the above functions. Welcome to join us.
sciwork portal is a project for maintaining our official website - sciwork.dev, which was built by Pelican with tailwindCSS, and deployed by Netfliy. We create the promotional pages for meetup and sprint events. Our team also maintains the sciwork conference page - conf.sciwork.dev.
We have always been actively trying to provide users a better web browsing experience, including information presentation and visual experience. Welcome to join us if you are interested in website maintence.
pyLiteracy is a linguistics-based Mandarin grammar checker built primarily with Python. Unlike how current mainstream large-language models, human natural language operates under a hierarchical framework rather than a linear-structured network. Moreover, the task of grammar checking focuses on the relation between words rather than the stochasticity between tokens.
Therefore, we aim to encode the primary phrase structures of Mandarin in order to achieve efficient Mandarin grammar checking with minimal resources in a fashion that best echoes a human being.
Cytnx (pronounced as sci-tens) is a tensor network library designed for classical/quantum physics simulations. It supports C++ and Python with almost identical interface and syntax, such that users can effortlessly switch between the two languages. Aiming at a quick learning process for new users of tensor network algorithms, the interfaces resemble the popular scientific libraries such as numpy, Scipy, and PyTorch. Symmetries present in physical systems can be easily defined and implemented in tensors.
In addition, we provide a useful class called Network that allows users to store large tensor networks and perform the contractions in an optimal order that can be automatically computed. There are still many physics applications and GPU support backend being developed. Welcome to join us to contribute to Cytnx.
Please register at kktix.
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Center for Theory and Computation (Rm. P518, 3rd General Building, National Tsing Hua University).