Kyle C. Hale
Kyle C. Hale
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REU Site: Collaborative Research: BigDataX: From theory to practice in Big Data computing at eXtreme scales
NSF Award OAC-2150500; $362,878 (Collaborative Total: $400K); July 2022 through June 2025. This project is in collaboration with Ioan Raicu at IIT as well as Kyle Chard at the University of Chicago.
Kyle C. Hale
,
Ioan Raicu
,
Kyle Chard
Last updated on Feb 21, 2024
Multi-kernel Modeling paper accepted to appear in TPDS!
Our work on modeling speed-up in multi-kernel environments has been accepated to appear in TPDS! Congratulations to Brian and Conghao on the hard work, and in particular to Brian for the journal paper push.
Brian Tauro
,
Conghao Liu
,
Kyle C. Hale
Last updated on Mar 4, 2023
REU Site: Collaborative Research: BigDataX: From theory to practice in Big Data computing at eXtreme scales
NSF Award CCF-1757964; $333,106 (Collaborative Total: $368K); February 2018 through January 2021. This project is in collaboration with Ioan Raicu at IIT as well as Kyle Chard and Aaron Elmore at the University of Chicago.
Kyle C. Hale
,
Ioan Raicu
,
Kyle Chard
,
Aaron Elmore
Last updated on Feb 21, 2024
CSR: Small: Collaborative Research: Flexible Resource Management and Coordination Schemes for Lightweight, Rapidly Deployable OS/Rs
CNS Award CNS-1718252; $249,771 (Collaborative total: $499,735); August 2017 through July 2020. This project is a collaborative effort with Jack Lange at the University of Pittsburgh. Current cloud systems leverage either heavy-weight virtualization (running applications inside full-fledged virtual machines (VMs) with their own operating systems) or containers (light-weight software environments that share a single underlying operating system).
Kyle C. Hale
,
Jack Lange
Last updated on Mar 4, 2023
CS 595-03: OS and Runtime Design for Supercomputing
Past Iterations: Fall ‘16
Kyle C. Hale
Last updated on Mar 4, 2023
ConCORD: Easily Exploiting Memory Content Redundancy through the Content-Aware Service Command
We argue that memory content-tracking across the nodes of a parallel machine should be factored into a distinct platform service on top …
Lei Xia
,
Kyle C. Hale
,
Peter Dinda
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