40 citations · 118 across the 8 of their papers we have counts for
13 papers
Towards Building Autonomous Data Services on Azure
Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon +35
Modern cloud has turned data services into easily accessible commodities. With just a few clicks, users are now able to access a catalog of data processing systems for a wide range…
The Tensor Data Platform: Towards an AI-centric Database System
Apurva Gandhi, Yuki Asada, Victor Fu +6
Database engines have historically absorbed many of the innovations in data processing, adding features to process graph data, XML, object oriented, and text among many others. In…
KEA: Tuning an Exabyte-Scale Data Infrastructure
Yiwen Zhu, Subru Krishnan, Konstantinos Karanasos +12
Microsoft's internal big-data infrastructure is one of the largest in the world -- with over 300k machines running billions of tasks from over 0.6M daily jobs. Operating this infra…
A Tensor Compiler for Unified Machine Learning Prediction Serving
Supun Nakandala, Karla Saur, Gyeong-In Yu +4
Machine Learning (ML) adoption in the enterprise requires simpler and more efficient software infrastructure---the bespoke solutions typical in large web companies are simply unten…
Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation
Olga Poppe, Tayo Amuneke, Dalitso Banda +23
Microsoft Azure is dedicated to guarantee high quality of service to its customers, in particular, during periods of high customer activity, while controlling cost. We employ a Dat…
MLOS: An Infrastructure for Automated Software Performance Engineering
Carlo Curino, Neha Godwal, Brian Kroth +9
Developing modern systems software is a complex task that combines business logic programming and Software Performance Engineering (SPE). The later is an experimental and labor-int…