Uni10 sprint 

Project site:
https://gitlab.com/uni10/uni10
Issue tracker:
https://gitlab.com/uni10/uni10/issues
Areas of interests:
Quantum physics, chemistry, statistics
Hosts:
Ying-jer Kao and Pochung Chen
Room:
202

Introduction 

Uni10 is a numerical library designed for tensor networks, which finds applications in quantum physics, chemistry, data analysis and machine learning. In this sprint, the participants will have the chance to work on different parts of Uni10 to understand and improve cross-platform build using CMake, GPU programming using CUDA, Python binding generation using pybind11, unit testing using gtests and writing API documentation using Doxygen. In addition, the participants can get familiar with git workflow and CI/CD. Furthermore, multi-node/multi-gpu programming paradigm will also be explored.

Objective 

  • Enhance the new architecture with unit tests and regression tests:
    • Make test cases for inserting numpy array to C++ array.
    • Make test cases for matrix transpose/multiplication in GPU.
  • Enable llvm-tidy on the CI.
  • Resolve other tickets.

Requirements 

Attendee equipment:
Laptop running Linux or MacOS (with wifi connectivity)
Software:
Git, Cmake, and Boost
Online service:
GitLab account
Other:
Unit-testing
Optional:
Linear algebra, matrix operation (at GPU), Hamitonian equation (physics)