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A survey of the research on power management techniques for high‐performance systems
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-36612-1_8openalex-snapshot
Energy-Driven Statistical Sampling: Detecting Software Hotspots
inferredcites →https://doi.org/10.1007/978-3-540-69338-3_13openalex-snapshot
Efficient Program Power Behavior Characterization
inferredcites →https://doi.org/10.1007/978-3-540-89856-6_13openalex-snapshot
pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems
inferredcites →https://doi.org/10.1007/978-3-642-03644-6_16openalex-snapshot
HPVZ: A High Performance Virtual Computing Environment for Super Computers
inferredcites →https://doi.org/10.1109/92.335013openalex-snapshot
A survey of power estimation techniques in VLSI circuits
inferredcites →https://doi.org/10.1109/conect.2004.1375189openalex-snapshot
What are the future trends in high-performance inter.connects for parallel computers? [Panel 1]
inferredcites →https://doi.org/10.1109/date.2003.1253746openalex-snapshot
Layer assignment techniques for low energy in multi-layered memory organisations
inferredcites →https://doi.org/10.1109/hpca.2002.995705openalex-snapshot
Using complete machine simulation for software power estimation: the SoftWatt approach
inferredcites →https://doi.org/10.1109/hpca.2008.4658631openalex-snapshot
Cluster-level feedback power control for performance optimization
inferredcites →https://doi.org/10.1109/icac.2005.17openalex-snapshot
Boosting Data Center Performance Through Non-Uniform Power Allocation
inferredcites →https://doi.org/10.1109/icdcs.2003.1203506openalex-snapshot
A case for grid computing on virtual machines
inferredcites →https://doi.org/10.1109/icpp.2007.29openalex-snapshot
CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters
inferredcites →https://doi.org/10.1109/isca.2008.37openalex-snapshot
Understanding and Designing New Server Architectures for Emerging Warehouse-Computing Environments
inferredcites →https://doi.org/10.1109/mc.2003.1250880openalex-snapshot
Energy management for commercial servers
inferredcites →https://doi.org/10.1109/mc.2005.173openalex-snapshot
The architecture of virtual machines
inferredcites →https://doi.org/10.1109/mc.2005.176openalex-snapshot
Virtual machine monitors: current technology and future trends
inferredcites →https://doi.org/10.1109/mcsa.1999.749272openalex-snapshot
PowerScope: a tool for profiling the energy usage of mobile applications
inferredcites →https://doi.org/10.1109/sc.2002.10058openalex-snapshot
Massive Arrays of Idle Disks For Storage Archives
inferredcites →https://doi.org/10.1109/sc.2005.39openalex-snapshot
Just In Time Dynamic Voltage Scaling: Exploiting Inter-Node Slack to Save Energy in MPI Programs
inferredcites →https://doi.org/10.1109/sc.2005.57openalex-snapshot
Performance-constrained Distributed DVS Scheduling for Scientific Applications on Power-aware Clusters
inferredcites →https://doi.org/10.1109/sc.2006.11openalex-snapshot
Adaptive, Transparent Frequency and Voltage Scaling of Communication Phases in MPI Programs
inferredcites →https://doi.org/10.1109/tc.2007.1003openalex-snapshot
Dynamic Voltage Scaling in Multitier Web Servers with End-to-End Delay Control
inferredcites →https://doi.org/10.1145/1006209.1006220openalex-snapshot
Energy conservation techniques for disk array-based servers
inferredcites →https://doi.org/10.1145/1013235.1013282openalex-snapshot
Dynamic voltage and frequency scaling based on workload decomposition
inferredcites →https://doi.org/10.1145/1064212.1064253openalex-snapshot
Managing server energy and operational costs in hosting centers
inferredcites →https://doi.org/10.1145/1065944.1065967openalex-snapshot
Using multiple energy gears in MPI programs on a power-scalable cluster
inferredcites →https://doi.org/10.1145/1065944.1065969openalex-snapshot
Energy conservation in heterogeneous server clusters
inferredcites →https://doi.org/10.1145/1108956.1108957openalex-snapshot
Power reduction techniques for microprocessor systems
inferredcites →https://doi.org/10.1145/1131322.1131328openalex-snapshot
Virtualization for high-performance computing
inferredcites →https://doi.org/10.1145/1140103.1140281openalex-snapshot
Exploiting redundancy to conserve energy in storage systems
inferredcites →https://doi.org/10.1145/1183401.1183421openalex-snapshot
A case for high performance computing with virtual machines
inferredcites →https://doi.org/10.1145/1250662.1250665openalex-snapshot
Power provisioning for a warehouse-sized computer
inferredcites →https://doi.org/10.1145/1272998.1273025openalex-snapshot
Container-based operating system virtualization
inferredcites →https://doi.org/10.1145/1283780.1283869openalex-snapshot
Phase-aware adaptive hardware selection for power-efficient scientific computations
inferredcites →https://doi.org/10.1145/1375527.1375555openalex-snapshot
Power-aware dynamic placement of HPC applications
inferredcites →https://doi.org/10.1145/1454115.1454153openalex-snapshot
Multi-mode energy management for multi-tier server clusters
inferredcites →https://doi.org/10.1145/502034.502045openalex-snapshot
Managing energy and server resources in hosting centers
inferredcites →https://doi.org/10.1145/505306.505330openalex-snapshot
Energy-delay efficiency of VLSI computations
inferredcites →https://doi.org/10.1145/782814.782829openalex-snapshot
Conserving disk energy in network servers
inferredcites →https://doi.org/10.1145/957717.957772openalex-snapshot
Making a Case for Efficient Supercomputing
inferredcites →https://doi.org/10.1145/980152.980157openalex-snapshot
Temperature-aware microarchitecture
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/9781118342015.ch3openalex-snapshot
Energy Efficiency in HPC Systems
inferred← citeshttps://doi.org/10.1002/spe.3139openalex-snapshot
DEPO: A dynamic energy‐performance optimizer tool for automatic power capping for energy efficient high‐performance computing
inferred← citeshttps://doi.org/10.1007/978-1-4939-2092-1_5openalex-snapshot
A Power-Aware Autonomic Approach for Performance Management of Scientific Applications in a Data Center Environment
inferred← citeshttps://doi.org/10.1007/978-3-030-35445-9_17openalex-snapshot
AMOSA with Analytical Tuning Parameters and Fuzzy Logic Controller for Heterogeneous Computing Scheduling Problem
inferred← citeshttps://doi.org/10.1007/978-3-319-09879-1_5openalex-snapshot
Opportunities and Challenges for Green HPC
inferred← citeshttps://doi.org/10.1007/978-3-319-22635-4_7openalex-snapshot
Modeling Power Consumption in Multicore CPUs with Multithreading and Frequency Scaling
inferred← citeshttps://doi.org/10.1007/978-3-319-47054-2_46openalex-snapshot
AMOSA with Analytical Tuning Parameters for Heterogeneous Computing Scheduling Problem
inferred← citeshttps://doi.org/10.1007/978-3-319-99966-1_9openalex-snapshot
Seven Pillars to Achieve Energy Efficiency in High-Performance Computing Data Centers
inferred← citeshttps://doi.org/10.1007/978-3-642-19328-6_1openalex-snapshot
Exascale Computing Technology Challenges
inferred← citeshttps://doi.org/10.1007/978-3-662-43779-7_6openalex-snapshot
Reducing Energy Costs for IBM Blue Gene/P via Power-Aware Job Scheduling
inferred← citeshttps://doi.org/10.1007/978-81-322-1759-6_100openalex-snapshot
Dynamic Sleep State Schedule for Idle Nodes in Clusters
inferred← citeshttps://doi.org/10.1007/978-981-16-3346-1_18openalex-snapshot
State-of-the-Art Power Management Techniques
inferred← citeshttps://doi.org/10.1007/s00450-011-0189-6openalex-snapshot
Energy-aware job scheduler for high-performance computing
inferred← citeshttps://doi.org/10.1007/s11227-012-0794-6openalex-snapshot
Energy management for a real-time shared disk cluster
inferred← citeshttps://doi.org/10.1007/s12053-015-9412-9openalex-snapshot
Energy management for the homogeneous server clusters offering web services
inferred← citeshttps://doi.org/10.1016/j.advengsoft.2012.11.011openalex-snapshot
An ACO-inspired algorithm for minimizing weighted flowtime in cloud-based parameter sweep experiments
inferred← citeshttps://doi.org/10.1016/j.advengsoft.2015.01.005openalex-snapshot
Balancing throughput and response time in online scientific Clouds via Ant Colony Optimization (SP2013/2013/00006)
inferred← citeshttps://doi.org/10.1016/j.future.2013.07.010openalex-snapshot
Exploiting performance counters to predict and improve energy performance of HPC systems
inferred← citeshttps://doi.org/10.1016/j.future.2025.107810openalex-snapshot
Prediction model of performance–energy trade-off for CFD codes on AMD-based cluster
inferred← citeshttps://doi.org/10.1016/j.rser.2015.07.061openalex-snapshot
Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: A review
inferred← citeshttps://doi.org/10.1016/j.suscom.2013.02.001openalex-snapshot
Dynamic power management for QoS-aware applications
inferred← citeshttps://doi.org/10.1016/j.suscom.2015.08.002openalex-snapshot
Energy efficient scheduling strategies in Federated Grids
inferred← citeshttps://doi.org/10.1051/epjconf/20147000081openalex-snapshot
Realization of dynamical electronic systems
inferred← citeshttps://doi.org/10.1109/adcom.2012.6563585openalex-snapshot
High performance systems: An agent based application power profiling
inferred← citeshttps://doi.org/10.1109/cloudcom.2012.6427509openalex-snapshot
Self-adaptive management of the sleep depths of idle nodes in large scale systems to balance between energy consumption and response times
inferred← citeshttps://doi.org/10.1109/confluence.2017.7943171openalex-snapshot
Preferred device early availability for faster user response
inferred← citeshttps://doi.org/10.1109/cvprw56347.2022.00310openalex-snapshot
MAPLE: Microprocessor A Priori for Latency Estimation
inferred← citeshttps://doi.org/10.1109/hipc.2010.5713196openalex-snapshot
Investigating the potential of application-centric aggressive power management for HPC workloads
inferred← citeshttps://doi.org/10.1109/icacci.2017.8126124openalex-snapshot
Self-adaptive power management framework for high performance computing
inferred← citeshttps://doi.org/10.1109/icghpc.2016.7508065openalex-snapshot
Adaptive Power Management for HPC applications
inferred← citeshttps://doi.org/10.1109/ipdpsw.2012.117openalex-snapshot
A Power Provision and Capping Architecture for Large Scale Systems
inferred← citeshttps://doi.org/10.1109/ipdpsw.2018.00111openalex-snapshot
Energy and Power Aware Job Scheduling and Resource Management: Global Survey — Initial Analysis
inferred← citeshttps://doi.org/10.1109/pdp.2015.73openalex-snapshot
DVFS Governor for HPC: Higher, Faster, Greener
inferred← citeshttps://doi.org/10.1109/sbac-pad.2012.32openalex-snapshot
Beyond CPU Frequency Scaling for a Fine-grained Energy Control of HPC Systems
inferred← citeshttps://doi.org/10.1109/sc.2016.55openalex-snapshot
A Data Driven Scheduling Approach for Power Management on HPC Systems
inferred← citeshttps://doi.org/10.1109/sustainit.2015.7101364openalex-snapshot
A user perspective on energy profiling tools in large scale computing environments
inferred← citeshttps://doi.org/10.1109/wetice.2014.48openalex-snapshot
Track Report of Collaborative and Autonomic Green Computing (CAGing 2014)
inferred← citeshttps://doi.org/10.1142/s0218126615501613openalex-snapshot
Software-Controlled Instruction Prefetch Buffering for Low-End Processors
inferred← citeshttps://doi.org/10.1142/s0218126617501730openalex-snapshot
Is Correlation Ranking Really Reliable for the Performance Counter Selection Conducted for Power Estimation?
inferred← citeshttps://doi.org/10.1145/3203217.3204464openalex-snapshot
A constrained extremum-seeking control for CPU thermal management
inferred← citeshttps://doi.org/10.1145/3694687openalex-snapshot
Modeling and Controlling Many-Core HPC Processors: An Alternative to PID and Moving Average Algorithms
inferred← citeshttps://doi.org/10.12694/scpe.v16i4.1132openalex-snapshot
Energy Efficiency of Parallel Multicore Programs
inferred← citeshttps://doi.org/10.1561/1000000055openalex-snapshot
On-Chip Dynamic Resource Management
inferred← citeshttps://doi.org/10.19153/cleiej.17.1.2openalex-snapshot
Dynamic Scheduling based on Particle Swarm Optimization for Cloud-based Scientific Experiments
inferred← citeshttps://doi.org/10.2298/csis150228063fopenalex-snapshot
Current prospects towards energy-efficient top HPC systems
inferred← citeshttps://doi.org/10.26102/2310-6018/2020.31.4.023openalex-snapshot
Resource allocation and task planning in a cloud environment based on the particle swarm and R-factor optimization algorithm
inferred← citeshttps://doi.org/10.32628/cseit1228115openalex-snapshot
A Review on Stock Prediction Using Machine Learning Algorithms
inferred← citeshttps://doi.org/10.3390/s22031280openalex-snapshot
Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking
inferred← citeshttps://doi.org/10.3990/1.9789036543590openalex-snapshot
Automated performance evaluation of service-oriented systems
inferred← citeshttps://doi.org/10.4018/978-1-4666-2518-1.ch016openalex-snapshot
Schedulers Based on Ant Colony Optimization for Parameter Sweep Experiments in Distributed Environments
inferred← citeshttps://doi.org/10.4108/icst.valuetools.2014.258214openalex-snapshot
Multi-Class Queuing Networks Models for Energy Optimization
inferred← citeshttps://doi.org/10.5821/dissertation-2117-96355openalex-snapshot
Per-task energy metering and accounting in the multicore era
inferred← citeshttps://doi.org/10.70675/ee690eb4z4676z4a3fz922cza886309a8b9fopenalex-snapshot
System Profiling and Green Capabilities for Large Scale and Distributed Infrastructures
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