Robust LSM tuning research paper published

Mar 30, 2022 | Greater New England, IBM, News

Congratulations to Andy Hyunh, IBM PhD Fellowship intern and PhD candidate, Boston University; Harshal Chaudhari, PhD candidate, Boston University; Evimaria Terzi, Professor, Computer Science, Boston University; and Manos Athanassoulis, Assistant Professor, Computer Science, Boston University, on the acceptance of their paper,Endure: A Robust Tuning Paradigm for LSM Trees Under
Workload Uncertainty
” at VLDB2022.

Andy was awarded an IBM PhD Fellowship Award in 2020. Red Hat Research participated in the candidate reviews and made recommendations on joint project opportunities. Josh Berkus, Kubernetes Community Manager, Red Hat, served as Andy’s Red Hat mentor.

Those interested in the topic should follow the Robust Data Systems Tuning Project, which was awarded a 2021 Red Hat Collaboratory at Boston University Research Incubation Award.

Related Stories

PHYSICS 4th General Assembly held

PHYSICS 4th General Assembly held

Yiannis Georgiou, Ryax, discussing project outcomes The 4th PHYSICS project General Assembly meeting was held July 4-6, 2022, hosted by RYAX in Athens, Greece. During the meeting, partners analyzed the project’s growth and had the opportunity to participate in person...

DevConf.US 2022 recordings available

DevConf.US 2022 recordings available

Recordings from DevConf.US 2022, August 17-20, 2022 in Boston, MA are now available on the DevConf.US 2022 YouTube playlist. This year’s conference featured talks on topics integral to Red Hat Research projects, including hybrid cloud and cloud computing, edge...

Red Hat Collaboratory Announces 2022 Student Research Projects

Red Hat Collaboratory Announces 2022 Student Research Projects

On April 14, the Red Hat Collaboratory announced five newly funded Student Research Projects. As part of Boston University’s expanded partnership with Red Hat, the Student Research Projects aim to provide BU students with research and experiential learning...

Technical Report: Benchmarking tunnel and encryption methodologies in cloud environments

Technical Report: Benchmarking tunnel and encryption methodologies in cloud environments

In this report, we benchmark the performance of various tunneling technologies to provide directions on their use in multi-cloud deployments. Based on the various experiments conducted on three different testbeds, we present quantifiable data which can be leveraged by operators and providers tasked with design and development decisions of multi-cloud providers and orchestrators.”