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Dynamic Colocation Policies with Reinforcement Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/047166880xopenalex-snapshot
Feedback Control of Computing Systems
inferredcites →https://doi.org/10.1007/978-3-642-24455-1_33openalex-snapshot
Value-Difference Based Exploration: Adaptive Control between Epsilon-Greedy and Softmax
inferredcites →https://doi.org/10.1007/s10723-014-9314-7openalex-snapshot
A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments
inferredcites →https://doi.org/10.1109/cec.2011.5949796openalex-snapshot
Reinforcement learning with adaptive Kanerva coding for Xpilot game AI
inferredcites →https://doi.org/10.1109/hpca.2015.7056037openalex-snapshot
Octopus-Man: QoS-driven task management for heterogeneous multicores in warehouse-scale computers
inferredcites →https://doi.org/10.1109/hpca.2017.13openalex-snapshot
Hipster: Hybrid Task Manager for Latency-Critical Cloud Workloads
inferredcites →https://doi.org/10.1109/hpca.2018.00059openalex-snapshot
Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective
inferredcites →https://doi.org/10.1109/hpca.2019.00032openalex-snapshot
μDPM: Dynamic Power Management for the Microsecond Era
inferredcites →https://doi.org/10.1109/icicta.2012.115openalex-snapshot
Energy Aware Resource Scheduling Algorithm for Data Center Using Reinforcement Learning
inferredcites →https://doi.org/10.1109/iiswc.2016.7581261openalex-snapshot
Tailbench: a benchmark suite and evaluation methodology for latency-critical applications
inferredcites →https://doi.org/10.1109/isca.2008.21openalex-snapshot
Self-Optimizing Memory Controllers: A Reinforcement Learning Approach
inferredcites →https://doi.org/10.1109/mc.2007.443openalex-snapshot
The Case for Energy-Proportional Computing
inferredcites →https://doi.org/10.1109/mic.2007.21openalex-snapshot
Reinforcement Learning in Autonomic Computing: A Manifesto and Case Studies
inferredcites →https://doi.org/10.1109/micro.1996openalex-snapshot
Proceedings of the 29th Annual IEEE/ACM International Symposium on Microarchitecture. MICRO 29
inferredcites →https://doi.org/10.1109/micro.2006.31openalex-snapshot
Managing Distributed, Shared L2 Caches through OS-Level Page Allocation
inferredcites →https://doi.org/10.1109/micro.2014.53openalex-snapshot
SMiTe: Precise QoS Prediction on Real-System SMT Processors to Improve Utilization in Warehouse Scale Computers
inferredcites →https://doi.org/10.1109/tsmcc.2011.2106494openalex-snapshot
Experience Replay for Real-Time Reinforcement Learning Control
inferredcites →https://doi.org/10.1145/1380584.1380585openalex-snapshot
A survey of autonomic computing—degrees, models, and applications
inferredcites →https://doi.org/10.1145/2678373.2665718openalex-snapshot
Towards energy proportionality for large-scale latency-critical workloads
inferredcites →https://doi.org/10.1145/3005745.3005750openalex-snapshot
Resource Management with Deep Reinforcement Learning
inferredcites →https://doi.org/10.5555/1870926.1871068openalex-snapshot
Enhanced Q-learning algorithm for dynamic power management with performance constraint
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-87010-2_28openalex-snapshot
An Analytical Bound for Choosing Trivial Strategies in Co-scheduling
inferred← citeshttps://doi.org/10.1007/978-3-030-88224-2_7openalex-snapshot
A HPC Co-scheduler with Reinforcement Learning
inferred← citeshttps://doi.org/10.1007/978-981-95-0497-8_43openalex-snapshot
Quantum Circuit Transpilation: A Comprehensive Overview
inferred← citeshttps://doi.org/10.1007/s00500-023-09281-8openalex-snapshot
Dynamic link utilization empowered by reinforcement learning for adaptive storage allocation in MANET
inferred← citeshttps://doi.org/10.1016/j.dcan.2024.08.002openalex-snapshot
Collaborative learning-based inter-dependent task dispatching and co-location in an integrated edge computing system
inferred← citeshttps://doi.org/10.1016/j.jnca.2023.103632openalex-snapshot
EdgeDrones: Co-scheduling of drones for multi-location aerial computing missions
inferred← citeshttps://doi.org/10.1016/j.jocs.2026.102915openalex-snapshot
Competitive analysis of HPC co-scheduling strategies optimizing for makespan, fairness and efficiency
inferred← citeshttps://doi.org/10.1016/j.sysarc.2023.102923openalex-snapshot
Resource-aware multi-task offloading and dependency-aware scheduling for integrated edge-enabled IoV
inferred← citeshttps://doi.org/10.1109/cluster59578.2024.00025openalex-snapshot
RL-Cache: An Efficient Reinforcement Learning Based Cache Partitioning Approach for Multi-Tenant CDN Services
inferred← citeshttps://doi.org/10.1109/edge50951.2020.00021openalex-snapshot
Edge Federation: A Dependency-Aware Multi-Task Dispatching and Co-location in Federated Edge Container-Instances
inferred← citeshttps://doi.org/10.1109/icccbda51879.2021.9442553openalex-snapshot
Dynamic Resources Allocation among Collocated Applications via Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/tvt.2021.3127011openalex-snapshot
AirEdge: A Dependency-Aware Multi-Task Orchestration in Federated Aerial Computing
inferred← citeshttps://doi.org/10.3390/computers10100122openalex-snapshot
Analytical and Numerical Evaluation of Co-Scheduling Strategies and Their Application
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