JetBrains Research unites scientists working in challenging new disciplines

JetBrains Research is a private enterprise created to unite scientific projects that really make a difference and strive to improve a current state of science and technology. With the support of JetBrains, researchers and teams can focus on the actual work, instead of grant seeking or dealing with other management issues.

Recent publications

  • Igor Kuralenok, Artem Trofimov, Nikita Marshalkin, Boris Novikov
    ADBIS 2018: Advances in Databases and Information Systems,
  • arXiv,
  • Rustam Azimov, Semyon Grigorev

    The generalization of matrix-based Valiant's context-free language recognition algorithm for graph case is widely considered as a recipe for efficient context-free path querying; however, no progress has been made in this direction so far. We propose the first generalization of matrix-based Valiant's algorithm for context-free path querying. Our generalization does not deliver a truly sub-cubic worst-case complexity algorithm, whose existence still remains a hard open problem in the area. On the other hand, the utilization of matrix operations (such as matrix multiplication) in the process of context-free path query evaluation makes it possible to efficiently apply a wide class of optimizations and computing techniques, such as GPGPU, parallel processing, sparse matrix representation, distributed-memory computation, etc. Indeed, the evaluation on a set of conventional benchmarks shows, that our algorithm outperforms the existing ones.

    GRADES-NDA '18 Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA),