Moderator
Event Type
Panel
Clouds and Distributed Computing
Data Analytics
Data management
Machine Learning
TimeWednesday, November 15th3:30pm -
5pm
Location201-203
DescriptionHigh-End Computing (HEC) encompasses both massive
computational and big data capability to solve
computational problems of significant importance that
are beyond the capability of small- to medium-scale
systems. Data science includes large-scale data
analytics and visualization across multiple scales of
data from a multitude of sources. Increasingly on-demand
and real-time data intensive computing, enabling
real-time analysis of simulations, data-intensive
experiments and streaming observations, is pushing the
boundaries of computing and resulting in a convergence
of traditional HEC and newer cloud computing
environments. This panel will explore challenges and
opportunities at the intersection of high-end computing
and data science.
• Which markets will drive the adoption of HEC for Data Science? What new applications could arise from this convergence? What game-changers will this enable?
• What impact will this have on conventional workflows, architectures and new memory paradigms (supercomputers versus shared cloud computing environments), software tools and workforce development?
• Which markets will drive the adoption of HEC for Data Science? What new applications could arise from this convergence? What game-changers will this enable?
• What impact will this have on conventional workflows, architectures and new memory paradigms (supercomputers versus shared cloud computing environments), software tools and workforce development?
Moderator
Panelists