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Trends in Server Energy Proportionality
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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-031-01722-3openalex-snapshot
The Datacenter as a Computer
inferredcites →https://doi.org/10.1109/mc.2007.443openalex-snapshot
The Case for Energy-Proportional Computing
inferredcites →https://doi.org/10.1109/mc.2009.84openalex-snapshot
Identifying Shades of Green: The SPECpower Benchmarks
inferredcites →https://doi.org/10.1145/1250662.1250665openalex-snapshot
Power provisioning for a warehouse-sized computer
inferredcites →https://doi.org/10.1145/1740390.1740399openalex-snapshot
Energy proportionality for storage
inferredcites →https://doi.org/10.1145/1815961.1816004openalex-snapshot
Energy proportional datacenter networks
inferredcites →https://doi.org/10.2200/s00193ed1v01y200905cac006openalex-snapshot
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-32813-9_16openalex-snapshot
Power Characterization of Memory Intensive Applications: Analysis and Implications
inferred← citeshttps://doi.org/10.1007/978-3-319-17248-4_14openalex-snapshot
On the Energy Proportionality of Distributed NoSQL Data Stores
inferred← citeshttps://doi.org/10.1007/978-3-642-36781-6_13openalex-snapshot
A Novel Approach to Energy Efficient Content Distribution with BitTorrent
inferred← citeshttps://doi.org/10.1007/s00450-011-0194-9openalex-snapshot
Flexible workload generation for HPC cluster efficiency benchmarking
inferred← citeshttps://doi.org/10.1007/s00450-014-0263-yopenalex-snapshot
Are our dense linear algebra libraries energy-friendly?
inferred← citeshttps://doi.org/10.1007/s11227-015-1600-zopenalex-snapshot
Adapting concurrency throttling and voltage–frequency scaling for dense eigensolvers
inferred← citeshttps://doi.org/10.1016/j.future.2019.10.021openalex-snapshot
The effect of server energy proportionality on data center power oversubscription
inferred← citeshttps://doi.org/10.1016/j.parco.2019.04.009openalex-snapshot
The time and energy efficiency of modern multicore systems
inferred← citeshttps://doi.org/10.1016/j.resconrec.2025.108310openalex-snapshot
The water use of data center workloads: A review and assessment of key determinants
inferred← citeshttps://doi.org/10.1109/access.2019.2939614openalex-snapshot
An Edge Computing Platform for Intelligent Operational Monitoring in Internet Data Centers
inferred← citeshttps://doi.org/10.1109/bdcloud.2014.99openalex-snapshot
Towards Generalizing "Big Little" for Energy Proportional HPC and Cloud Infrastructures
inferred← citeshttps://doi.org/10.1109/cahpc.2018.8645948openalex-snapshot
EASE: Energy Efficiency and Proportionality Aware Virtual Machine Scheduling
inferred← citeshttps://doi.org/10.1109/ccgrid.2014.119openalex-snapshot
Metrics, Models and Methodologies for Energy-Proportional Computing
inferred← citeshttps://doi.org/10.1109/ccgrid.2014.121openalex-snapshot
Enabling Efficient Power Provisioning for Enterprise Applications
inferred← citeshttps://doi.org/10.1109/cloud.2017.30openalex-snapshot
WASP: Workload Adaptive Energy-Latency Optimization in Server Farms Using Server Low-Power States
inferred← citeshttps://doi.org/10.1109/cloudcom.2015.75openalex-snapshot
A Dual Delay Timer Strategy for Optimizing Server Farm Energy
inferred← citeshttps://doi.org/10.1109/cluster.2016.44openalex-snapshot
On Energy Proportionality and Time-Energy Performance of Heterogeneous Clusters
inferred← citeshttps://doi.org/10.1109/hpca.2019.00038openalex-snapshot
Poly: Efficient Heterogeneous System and Application Management for Interactive Applications
inferred← citeshttps://doi.org/10.1109/iccd.2015.7357176openalex-snapshot
Power-agility metrics: Measuring dynamic characteristics of energy proportionality
inferred← citeshttps://doi.org/10.1109/iccd53106.2021.00059openalex-snapshot
HyperData: A Data Transfer Accelerator for Software Data Planes Based on Targeted Prefetching
inferred← citeshttps://doi.org/10.1109/icdcs.2017.285openalex-snapshot
Energy Proportional Servers: Where Are We in 2016?
inferred← citeshttps://doi.org/10.1109/icpp.2013.99openalex-snapshot
Revisiting Server Energy Proportionality
inferred← citeshttps://doi.org/10.1109/icppw.2015.30openalex-snapshot
HPC-Oriented Power Evaluation Method
inferred← citeshttps://doi.org/10.1109/iiswc.2015.18openalex-snapshot
A Retrospective Look Back on the Road Towards Energy Proportionality
inferred← citeshttps://doi.org/10.1109/isca.2016.49openalex-snapshot
Peak Efficiency Aware Scheduling for Highly Energy Proportional Servers
inferred← citeshttps://doi.org/10.1109/mc.2017.3001248openalex-snapshot
Energy-Proportional Computing: A New Definition
inferred← citeshttps://doi.org/10.1109/micro.2012.20openalex-snapshot
KnightShift: Scaling the Energy Proportionality Wall through Server-Level Heterogeneity
inferred← citeshttps://doi.org/10.1109/mm.2013.31openalex-snapshot
Scaling the Energy Proportionality Wall with KnightShift
inferred← citeshttps://doi.org/10.1109/pccc.2018.8710831openalex-snapshot
Choosing the Best Server for a Data Center: The Importance of Workload Weighting
inferred← citeshttps://doi.org/10.1109/rndm.2014.7014945openalex-snapshot
Reliability-aware virtual data center embedding
inferred← citeshttps://doi.org/10.1109/sbac-pad.2016.34openalex-snapshot
Energy Aware Dynamic Provisioning for Heterogeneous Data Centers
inferred← citeshttps://doi.org/10.1109/tsusc.2017.2701883openalex-snapshot
Metrics for Sustainable Data Centers
inferred← citeshttps://doi.org/10.1142/s0129626415410066openalex-snapshot
“Big, Medium, Little”: Reaching Energy Proportionality with Heterogeneous Computing Scheduler
inferred← citeshttps://doi.org/10.1145/2188286.2188309openalex-snapshot
Towards efficient supercomputing
inferred← citeshttps://doi.org/10.1145/2479871.2479878openalex-snapshot
Towards energy-proportional computing for enterprise-class server workloads
inferred← citeshttps://doi.org/10.1145/2491477.2491478openalex-snapshot
On bottleneck analysis in stochastic stream processing
inferred← citeshttps://doi.org/10.1145/2668930.2688049openalex-snapshot
Measuring Server Energy Proportionality
inferred← citeshttps://doi.org/10.1145/2834965.2834969openalex-snapshot
Towards Energy-Proportional State-Machine Replication
inferred← citeshttps://doi.org/10.1145/3007787.3001188openalex-snapshot
Peak efficiency aware scheduling for highly energy proportional servers
inferred← citeshttps://doi.org/10.1145/3046682openalex-snapshot
Pareto Governors for Energy-Optimal Computing
inferred← citeshttps://doi.org/10.1145/3229710.3229714openalex-snapshot
The Energy Efficiency of Modern Multicore Systems
inferred← citeshttps://doi.org/10.22215/etd/2017-12172openalex-snapshot
A User Relinquishment-based Resource Assignment Scheme to Maximize the Net Profit of Cloud Service Providers
inferred← citeshttps://doi.org/10.3390/en12040646openalex-snapshot
Energy Aware Virtual Machine Scheduling in Data Centers
inferred← citeshttps://doi.org/10.3390/en14144089openalex-snapshot
Power and Performance Evaluation of Memory-Intensive Applications
inferred← citeshttps://doi.org/10.3390/en16073187openalex-snapshot
Escope: An Energy Efficiency Simulator for Internet Data Centers
inferred← citeshttps://doi.org/10.48550/arxiv.1501.02724openalex-snapshot
Towards Energy-Proportional Computing Using Subsystem-Level Power Management
inferred← citeshttps://doi.org/10.48550/arxiv.2108.01776openalex-snapshot
How Can Datacenters Join the Smart Grid to Address the Climate Crisis? Using simulation to explore power and cost effects of direct participation in the energy market
inferred← citeshttps://doi.org/10.70675/668f3853z31f4z47aaz9b78z96245a4957e5openalex-snapshot
Scheduling and Dynamic Provisioning for Energy Proportional Heterogeneous Infrastructures
inferred← citeshttps://doi.org/10.70675/b1b9a342z53ccz4436za20cz5d850bf53c1dopenalex-snapshot
Supporting energy-awareness for cloud users
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