Data-Intensive Supercomputing laboratory

Research directions

  • Processing of superlarge graphs
    • development of problem-oriented large graph processing language
    • development of graph algorithms, scalable to a superlarge number of cores
    • Big-data technology
  • Research in the field of optimization (solution algorithms) of problems (Data-Intensive class) with high requirements for the memory sub-system and a communication network
    • Intel Xeon Phi accelerators
    • Angara and Infiniband interconnects, scaling to a large number of computing nodes
    • the use of of prospective parallel programming models
  • Research on the development of prospective architectures
    • simulation of exaFLOPS supercomputers
    • development of multithreaded processor
    • development of memory sub-systems that are effective in solving problems with intensive irregular access
  • HPCjudge contest conduct system