Gray Systems Lab

June 11, 2024 | Rana Alotaibi, Hanxian Huang, Tarique Siddiqui, Carlo Curino, Jesús Camacho Rodríguez, and Yuanyuan Tian

SIBYL is a machine learning model that makes highly accurate predictions of database queries, enabling tuning for more efficiency. Applying traditional database optimizations to these predicted queries helps maintain high performance as demands change.

June 10, 2024 | Jesús Camacho Rodríguez, Ashvin Agrawal, Anja Gruenheid, Ashit Gosalia, Cristian Petculescu, Josep Aguilar-Saborit, Avrilia Floratou, Carlo Curino, and Raghu Ramakrishnan

LST-Bench is a new open-source benchmark designed to evaluate table formats in cloud environments. It extends existing benchmarks to better reflect real-world usage & performance of data lakes and easily integrates with commonly used analytical engines.

May 13, 2024 | Anna Pavlenko, Karla Saur, Yiwen Zhu, Brian Kroth, Joyce Cahoon, and Jesús Camacho Rodríguez

Autoscaling can optimize cloud resource usage and costs by adjusting to demand. VASIM shows that simplifying testing and refinement of autoscaling algorithms can enable rapid development and evaluation of more efficient & cost-effective autoscaling strategies.

February 21, 2024

In this issue: CaaSPER: vertical autoscaling algorithm dynamically maintains optimal CPU utilization; Improved scene landmark detection for camera localization runs faster, uses less storage; ESUS simplifies usability questionnaires for technical products and services.

September 13, 2023

In this issue: Efficient polyglot analytics on semantic data aids query performance; generative retrieval for conversational question answering improves dialogue-based interfaces; a new tool uses ML to address capacity degradation in lithium-ion batteries.

May 27, 2020

We are announcing Hummingbird, a library for accelerating inference (scoring/prediction) in traditional machine learning models. Internally, Hummingbird compiles traditional ML pipelines into tensor computations to take advantage of the optimizations that are being implemented for neural network systems.

January 7, 2020

    We take an ‘applied research’ approach. Our scientists collaborate with our engineering and product teams to solve hard technical problems. Coupled with a direct line to data, resources, engineers, and the voice of the customer, GSL retains the…