Understanding Acceleration Opportunities at Hyperscale

Abstract

Modern web services run across hundreds of thousands of servers in a data center, i.e., at hyperscale. With the end of Moore's Law and Dennard scaling, successive server generations running these web services exhibit diminishing performance returns, resulting in architects adopting hardware customization. An important question arises: Which web service software operations are worth building custom hardware for? To answer this question, we comprehensively analyze important Facebook production services and identify key acceleration opportunities. We then develop an open-source analytical model, Accelerometer, to help make well-informed hardware decisions for the acceleration opportunities we identify.

Publication
To appear in IEEE Micro Issue: Top Picks in Computer Architecture from Conferences in 2020. (Acceptance: Top 12 computer architecture papers in 2020)
Akshitha Sriraman
Akshitha Sriraman
Assistant Professor

I am an Assistant Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University. My research bridges computer architecture and software systems, with a focus on making hyperscale data center systems more efficient (via solutions that span the systems stack). The central theme of my work is to (1) design software that is aware of new hardware constraints and (2) architect hardware that efficiently supports new hyperscale software requirements.