[PDF][PDF] Bayesian learning for hardware and software configuration co-optimization

Y Ding, A Pervaiz, S Krishnan… - University of Chicago …, 2020 - newtraell.cs.uchicago.edu
Both hardware and software systems are increasingly configurable, which poses a
challenge to finding the highest performance configuration due to the tremendous search …

Intelligent Resource Scheduling for Co-located Latency-critical Services: A {Multi-Model} Collaborative Learning Approach

L Liu, X Dou, Y Chen - 21st USENIX Conference on File and Storage …, 2023 - usenix.org
Latency-critical services have been widely deployed in cloud environments. For cost-
efficiency, multiple services are usually co-located on a server. Thus, run-time resource …

Scope: Safe exploration for dynamic computer systems optimization

H Kim, A Pervaiz, H Hoffmann, M Carbin… - arXiv preprint arXiv …, 2022 - arxiv.org
Modern computer systems need to execute under strict safety constraints (eg, a power limit),
but doing so often conflicts with their ability to deliver high performance (ie minimal latency) …

[PDF][PDF] KMLIB: Towards machine learning for operating systems

IU Akgun, AS Aydin, E Zadok - Proceedings of the On-Device …, 2020 - fsl.cs.stonybrook.edu
Despite the ever-changing software and hardware profiles of modern computing systems,
many operating systems (OS) components adhere to designs developed decades ago …

Artificial Intelligence in the Low-Level Realm--A Survey

VM Safarzadeh, HG Loghmani - arXiv preprint arXiv:2111.00881, 2021 - arxiv.org
Resource-aware machine learning has been a trending topic in recent years, focusing on
making ML computational aspects more exploitable by the edge devices in the Internet of …

MUSTACHE: Multi-Step-Ahead Predictions for Cache Eviction

G Tolomei, L Takanen, F Pinelli - arXiv preprint arXiv:2211.02177, 2022 - arxiv.org
In this work, we propose MUSTACHE, a new page cache replacement algorithm whose
logic is learned from observed memory access requests rather than fixed like existing …

[PDF][PDF] Building Verified Neural Networks for Computer Systems with Ouroboros

T Wei, Z Jia, C Liu, C Tan - Sixth Conference on Machine Learning and …, 2023 - cs.cmu.edu
Neural networks are powerful tools. Applying them in computer systems—operating
systems, databases, and networked systems—attracts much attention. However, neural …

Improving emerging systems' efficiency with hardware accelerators

H Fingler - 2023 - repositories.lib.utexas.edu
The constant growth of datacenters and cloud computing comes with an increase of power
consumption. With the end of Dennard scaling and Moore's law, computing no longer grows …

Safe Exploration for Dynamic Computer Systems Optimization

H Kim - 2022 - dspace.mit.edu
Modern computer systems need to execute under strict safety constraints (eg, power limit),
but doing so often conflicts with their ability to deliver high performance (ie, minimal latency) …

[PDF][PDF] SmartOS: Automating Allocation of Operating System Resources to User Preferences via Reinforcement Learning

S Goodarzy - 2022 - eric-keller.github.io
As modern humans, we deal with computer operating systems (OSs) in our daily lives when
we are at work, home, school, or even watching a TV show with our family at night …