Deploying a Steered Query Optimizer in Production at Microsoft

no code implementations • 24 Oct 2022 • Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari Karlen Lie, Marc Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal

Modern analytical workloads are highly heterogeneous and massively complex, making generic query optimizers untenable for many customers and scenarios.

Enhancing Strong PUF Security with Non-monotonic Response Quantization

no code implementations • 7 Jun 2022 • Kleber Stangherlin, Zhuanhao Wu, Hiren Patel, Manoj Sachdev

In this paper, we introduce the concept of non-monotonic response quantization for strong PUFs.

Quantization

Phoebe: A Learning-based Checkpoint Optimizer

no code implementations • 5 Oct 2021 • Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal

To address these issues, we propose Phoebe, an efficient learning-based checkpoint optimizer.

Optimal Resource Allocation for Serverless Queries

no code implementations • 19 Jul 2021 • Anish Pimpley, Shuo Li, Anubha Srivastava, Vishal Rohra, Yi Zhu, Soundararajan Srinivasan, Alekh Jindal, Hiren Patel, Shi Qiao, Rathijit Sen

We introduce a system for optimal resource allocation that can predict performance with aggressive trade-offs, for both new and past observed queries.

Data Augmentation

Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML

no code implementations • 30 Aug 2019 • Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Gowdal, Matteo Interlandi, Alekh Jindal, Kostantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu

Consequently, rigorous data management has emerged as a key requirement in enterprise settings.

Management