SIGHPC Big Data was formed in July 2015 to share best practices in High Performance Computing (HPC) Big Data solutions. In particular the chapter objectives include:

  • Providing a means of communication and collaboration among individuals having an interest in the convergence between HPC and Big Data, in order to exchange ideas and best practices
  • Promoting the parallelization of state-of-the-art big data analytics frameworks to use HPC platforms efficiently and the adaptation of common software stacks
  • Promoting the development of new tools for data intensive supercomputing
  • Promoting the use of HPC and Big Data technologies in commercial analytics

To encourage worldwide membership, SIGHPC Big Data is established as a virtual chapter.  Members attend the annual meeting at SC and join talks and learning activities via the internet.

 


To learn more about SIGHPC and ACM, just follow the links.