RL-Scope accepted MLSys 2022
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Open source RL-Scope
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Accepted at MLBench 2022
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portfolio
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publications
Protecting Data on Smartphones and Tablets from Memory Attacks
Patrick Colp, Jiawen Zhang, James Gleeson, Sahil Suneja, Eyal de Lara, Himanshu Raj, Stefan Saroiu, Alec Wolman
ASPLOS 2015 Acceptance rate: 17.3% (48/278)
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Crane: Fast and Migratable GPU Passthrough for OpenCL applications
James Gleeson, Daniel Kats, Charlie Mei, Eyal de Lara
SYSTOR 2017 Acceptance rate: 37.8% (17/45)
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Heterogeneous GPU reallocation
James Gleeson, Eyal de Lara
HotCloud 2017 Acceptance rate: 32.8% (19/58)
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RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads
James Gleeson, Srivatsan Krishnan, Moshe Gabel, Vijay Janapa Reddi, Eyal de Lara, Gennady Pekhimenko
MLSys 2021 Acceptance rate: 23.5% (52/221)
RL-Scope is open source!
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Lightning talk
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MoIL: Enabling Efficient Incremental Training on Edge Devices
Jiacheng Yang, James Gleeson, Mostafa Elhoushi, Gennady Pekhimenko
HAET 2021
Optimizing Data Collection in Deep Reinforcement Learning
James Gleeson, Daniel Snider, Yvonne Yang, Moshe Gabel, Eyal de Lara, Gennady Pekhimenko
MLBench 2022
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talks
Talk 1 on Relevant Topic in Your Field
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Tutorial 1 on Relevant Topic in Your Field
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Talk 2 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
Teaching experience 2
Workshop, University 1, Department, 2015