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.