Scisprint 2024 November in Hsinchu

Date

  • Date: 2nd November, Saturday, 2024
  • Time: 10:00 -- 17:00 (7 hours)

Agenda

  • 10:00-10:30 Arrival and Seating (Confirmation of registration information)
  • 10:30-11:00 Project Introduction
  • 11:00-12:00 Coding Session 1
  • 12:00-13:30 Lunch Break & Group Discussion 1
  • 13:30-14:20 Coding Session 2
  • 14:20-14:30 Group Discussion 2
  • 14:30-15:20 Coding Session 3
  • 15:20-15:30 Group Discussion 3
  • 15:30-16:30 Final Sprint
  • 16:30-17:00 Project Summary & Closing

About the scisprint

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.

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.

Project List

modmesh

  • Related Subjects: Python, C++, PDE
  • Project Link: Github
  • Project Contact: Yung-Yu Chen (discord: @yyc#7718), Chun-Hsu (@Chun-Hsu#6296)

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

  • Project Link: GitHub
  • Project Contact: Dboy (discord: @dboyliao#1295)

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

  • Project Link: GitHub
  • Project Contact: Chester (discord: @chester), Steve Chen (discord: @Steve Chen), Wuxian (discord: @5x9527)

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

  • Project Link: GitHub
  • Project Contact: Jonathan Chen (discord: @é™ģį•Ŋį”°), PeterWolf (discord: @PeterWolf#1422), Discord

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.

AItlas

  • Project Link: GitHub
  • Project Contact: PeterWolf (discord: @PeterWolf#1422), Discord

A knowledge graph should formally represent relations between/among entities and provide insights for semantic computation in natural language understanding (NLU). The representation is usually like a net 2D or atlas in 3D and higher dimensions. In recent years, this is usually called RAG. We believe a knowledge graph (thus KG) can do more for AI, thus named our project AI+Atlas = AItlas.

Sign Up

Please register at kktix.