FasTensor is a parallel execution engine for user-defined functions on multidimensional arrays. The user-defined functions follow the stencil metaphor used for scientific computing and is effective for expressing a wide range of computations for data analyses, including common aggregation operations from database management systems and advanced machine learning pipelines. FasTensor execution engine exploits the structural-locality in the multidimensional arrays to automate data management operations such as file I/O, data partitioning, communication, parallel execution, and so on.

Continuous Integration

  • Topics: Data Management, Analytics
  • Skills: C++, github
  • Difficulty: Medium
  • Size: Large (350 hours)
  • Mentor: John Wu, Bin Dong, Suren Byna
  • Develop a test suite for the public API of FasTensor
  • Automate execution of the test suite
  • Document the continuous integration process
  • Develop performance testing suite