Portrait of Amar Phanishayee

Amar Phanishayee

Researcher

About

Hi! I am a Researcher at Microsoft Research in Redmond.

The goal of my research is to enable the creation of high-performance and efficient systems for large-scale data-intensive computing. To this end, my work follows two broad approaches:

1. Radically rethinking cluster architecture

  • Energy-efficient clusters for data intensive computing – FAWN
  • Freespace optics for datacenter networks – ProjecToR

2. Build robust clustered systems and protocols

  • First to analyse and solve TCP throughput collapse and latency insensitivity for clustered systems – TCP Incast
  • Distributed KV systems – FAWN-KV, Flex-KV (and the underlying Ouroborous protocol)
  • Reliable and scalable multicast – Ricochet, Plato
  • Compositional reasoning for systematically testing distributed systems [Ongoing work]
  • Efficient distributed deep learning [Ongoing work]

I have also occasionally looked at addressing issues in geo-distributed systems:

  • High-perf multi-hop wireless transfers using opportunistic caching – Ditto
  • Scalable one-hop overlay routing – NuRON
  • Systems/abstractions for connected devices – Bolt (storage) and Beam(programming framework and runtime)

As a graduate student at Carnegie Mellon University I worked with Dave Andersen and some stellar collaborators on FAWN, Incast, and Ditto.

Publications

2017

2016

2015

2014

2013

2012

2011

2009

2008

2007

2006

Other

Research Awards

  • 2012 CMU’s Allen Newell Award for Research Excellence for our work on “Energy-efficient Data Intensive Computing”
  • Best Paper Award, SOSP 2009 for FAWN