Workshop III: Big-Data-driven Applications Go HPC

November 5 - 9, 2018


BDCWS3 ImageTypical data analytics applications, which are usually based much more on a statistical or discrete (combinatorial, heuristic) apparatus than on numerical computations, will develop in a direction with much more HPC relevance than today. The computational challenges arising in this context go far beyond the “embarrassingly parallel” (i.e., a large number of relatively simple/cheap single analyses/runs to be done) and will require more HPC topics to be addressed in large-scale data analytics. We will discuss the question: What are the implications, needs, opportunities, and limitations?

This workshop will include a poster session; a request for posters will be sent to registered participants in advance of the workshop.

Organizing Committee

Joachim Buhmann (ETH Zürich)
Jennifer Chayes (Microsoft Research)
Vipin Kumar (University of Minnesota, Twin Cities)
Yann LeCun (New York University, Canadian Institute for Advanced Research)
Tandy Warnow (University of Illinois at Urbana-Champaign, Computer Sciences)