Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Mancuso, Renato"'
Autor:
Sengupta, Kathakoli, Shagguan, Zhongkai, Bharadwaj, Sandesh, Arora, Sanjay, Ohn-Bar, Eshed, Mancuso, Renato
Embodied vision-based real-world systems, such as mobile robots, require a careful balance between energy consumption, compute latency, and safety constraints to optimize operation across dynamic tasks and contexts. As local computation tends to be r
Externí odkaz:
http://arxiv.org/abs/2409.11403
This study presents "anchor critics", a novel strategy for enhancing the robustness of reinforcement learning (RL) agents in crossing the sim-to-real gap. While RL agents can be successfully trained in simulation, they often encounter difficulties su
Externí odkaz:
http://arxiv.org/abs/2301.06987
Autor:
Raza, Ali, Unger, Thomas, Boyd, Matthew, Munson, Eric, Sohal, Parul, Drepper, Ulrich, Jones, Richard, de Oliveira, Daniel Bristot, Woodman, Larry, Mancuso, Renato, Appavoo, Jonathan, Krieger, Orran
Publikováno v:
Proceedings of the Eighteenth European Conference on Computer Systems (EuroSys 23), May 2023, Pages 590 - 605
This paper presents Unikernel Linux (UKL), a path toward integrating unikernel optimization techniques in Linux, a general purpose operating system. UKL adds a configuration option to Linux allowing for a single, optimized process to link with the ke
Externí odkaz:
http://arxiv.org/abs/2206.00789
Publikováno v:
RTNS 2022: Proceedings of the 30th International Conference on Real-Time Networks and Systems June 2022 Pages 184-195
Benchmarking is crucial for testing and validating any system, even more so in real-time systems. Typical real-time applications adhere to well-understood abstractions: they exhibit a periodic behavior, operate on a well-defined working set, and stri
Externí odkaz:
http://arxiv.org/abs/2203.11423
Autor:
Roozkhosh, Shahin, Hoornaert, Denis, Mun, Ju Hyoung, Papon, Tarikul Islam, Sanaullah, Ahmed, Drepper, Ulrich, Mancuso, Renato, Athanassoulis, Manos
Analytical database systems are typically designed to use a column-first data layout to access only the desired fields. On the other hand, storing data row-first works great for accessing, inserting, or updating entire rows. Transforming rows to colu
Externí odkaz:
http://arxiv.org/abs/2109.14349
Actors and critics in actor-critic reinforcement learning algorithms are functionally separate, yet they often use the same network architectures. This case study explores the performance impact of network sizes when considering actor and critic arch
Externí odkaz:
http://arxiv.org/abs/2102.11893
Publikováno v:
ACM Transactions on Cyber-Physical Systems, Volume 5, Issue 4, October 2021
We focus on the problem of reliably training Reinforcement Learning (RL) models (agents) for stable low-level control in embedded systems and test our methods on a high-performance, custom-built quadrotor platform. A common but often under-studied pr
Externí odkaz:
http://arxiv.org/abs/2012.06656
A critical problem with the practical utility of controllers trained with deep Reinforcement Learning (RL) is the notable lack of smoothness in the actions learned by the RL policies. This trend often presents itself in the form of control signal osc
Externí odkaz:
http://arxiv.org/abs/2012.06644
Clouds inherit CPU scheduling policies of operating systems. These policies enforce fairness while leveraging best-effort mechanisms to enhance responsiveness of all schedulable entities, irrespective of their service level objectives (SLOs). This le
Externí odkaz:
http://arxiv.org/abs/2009.09104
The vast majority of high-performance embedded systems implement multi-level CPU cache hierarchies. But the exact behavior of these CPU caches has historically been opaque to system designers. Absent expensive hardware debuggers, an understanding of
Externí odkaz:
http://arxiv.org/abs/2007.12271