Systems For Big Data Applications: A Networking Perspective
Noa Zilberman, Cambridge University
Big data applications increasingly dominate every aspect of our lives.
Healthcare, finance and transportation are only a partial list of a
growing number of fields where big data is being used. These big data
applications, often running in the cloud, require significant computing resources and
drive the research of high-performance systems.
But how do these applications look like from a networking perspective? And
how does the network affect their performance? This talk presents a networking
perspective on big data applications. We study the effects of networking on the
performance of big data applications, and provide a breakdown of the basic latency
components within a high performance system. Based on our results, and using the
network profiles of different big data applications, we identify performance bottlenecks
and propose new system architectures for big data applications.
About the speaker
Noa Zilberman is a Leverhulme Early Career Fellow at the University of
Cambridge Computer Laboratory. Her research focuses on high performance
systems, combining both computer networks and computer architecture. Dr
Zilberman is the chief architect of the NetFPGA-SUME project, an open
source platform for rapid prototyping of high-performance networking
devices. She has over 15 years of industrial experience, in design,
management and architecture roles. Amongst others, she led the hardware
design of the world's first 100Gbps silicon switch, and the architecture
of the first device enabling scalable systems up to 100Tbps. Zilberman is the
PI on the CAND and PERF projects, and was a researcher on multiple EPSRC
and EU projects. She is a senior member of IEEE and a member of ACM,
Usenix and BCS.