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Scheduling Processor Voltage and Frequency in Server and Cluster 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_3openalex-snapshot
A Hardware Architecture for Dynamic Performance and Energy Adaptation
inferredcites →https://doi.org/10.1109/isca.2004.1310764openalex-snapshot
Single-ISA heterogeneous multi-core architectures for multithreaded workload performance
inferredcites →https://doi.org/10.1109/mc.2003.1250880openalex-snapshot
Energy management for commercial servers
inferredcites →https://doi.org/10.1109/micro.2003.1253185openalex-snapshot
Single-ISA heterogeneous multi-core architectures: the potential for processor power reduction
inferredcites →https://doi.org/10.1109/wwc.2004.1437388openalex-snapshot
Characterizing the impact of different memory-intensity levels
inferredcites →https://doi.org/10.1145/1028176.1006707openalex-snapshot
Single-ISA Heterogeneous Multi-Core Architectures for Multithreaded Workload Performance
inferredcites →https://doi.org/10.1145/1062261.1062295openalex-snapshot
Scheduling for heterogeneous processors in server systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Embracing the Memory and I/O Walls for Energy‐Efficient Scientific Computing
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Power Issues in Servers and Data Centers
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Predictive Power Management for Multi-core Processors
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Providing platform heterogeneity-awareness for data center power management
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VPM tokens: virtual machine-aware power budgeting in datacenters
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Adaptive energy-efficient scheduling for real-time tasks on DVS-enabled heterogeneous clusters
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Energy saving strategies for parallel applications with point-to-point communication phases
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Runtime Energy Adaptation with Low-Impact Instrumented Code in a Power-Scalable Cluster System
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Dynamic power scheduling for VM-based multi-core systems
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Toward Power-Aware Computing with Dynamic Voltage Scaling for Heterogeneous Platforms
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Enhanced Weighted Round Robin (EWRR) with DVFS Technology in Cloud Energy-Aware
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Grouping-Based Dynamic Power Management for Multi-threaded Programs in Chip-Multiprocessors
inferred← citeshttps://doi.org/10.1109/hpcc-css-icess.2015.214openalex-snapshot
GPU-Memory Coordinated Energy Saving Approach Based on Extreme Learning Machine
inferred← citeshttps://doi.org/10.1109/icac.2007.16openalex-snapshot
Exploiting Platform Heterogeneity for Power Efficient Data Centers
inferred← citeshttps://doi.org/10.1109/iiswc.2006.302728openalex-snapshot
Application-Aware Power Management
inferred← citeshttps://doi.org/10.1109/ipdps.2006.1639601openalex-snapshot
Power-performance efficiency of asymmetric multiprocessors for multi-threaded scientific applications
inferred← citeshttps://doi.org/10.1109/ipdps.2006.1639602openalex-snapshot
Compiler and runtime support for predictive control of power and cooling
inferred← citeshttps://doi.org/10.1109/ipdps.2007.370535openalex-snapshot
A High Performance Cluster System Design by Adaptie Power Control
inferred← citeshttps://doi.org/10.1109/ipdps.2007.370539openalex-snapshot
Scaling and Packing on a Chip Multiprocessor
inferred← citeshttps://doi.org/10.1109/ipdps.2008.4536221openalex-snapshot
Power management of distributed web savers by controlling server power state and traffic prediction for QoS
inferred← citeshttps://doi.org/10.1109/itsim.2010.5561559openalex-snapshot
Power optimization in multi-processor systems
inferred← citeshttps://doi.org/10.1109/mascots.2014.55openalex-snapshot
How Processor Speedups Can Slow Down I/O Performance
inferred← citeshttps://doi.org/10.1109/micro.2006.30openalex-snapshot
Live, Runtime Phase Monitoring and Prediction on Real Systems with Application to Dynamic Power Management
inferred← citeshttps://doi.org/10.1109/parcomptech.2015.7084517openalex-snapshot
DVFS based heterogeneous scheduling for power optimisation and load balancing in HPC clustersaper
inferred← citeshttps://doi.org/10.1109/tc.2011.47openalex-snapshot
Complete System Power Estimation Using Processor Performance Events
inferred← citeshttps://doi.org/10.1109/tc.2012.283openalex-snapshot
A Cool Scheduler for Multi-Core Systems Exploiting Program Phases
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Analyzing the Energy-Time Trade-Off in High-Performance Computing Applications
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Architecturally Homogeneous Power-Performance Heterogeneous Multicore Systems
inferred← citeshttps://doi.org/10.1109/ucc48980.2020.00040openalex-snapshot
Exploring the Potential of using Power as a First Class Parameter for Resource Allocation in Apache Mesos Managed Clouds
inferred← citeshttps://doi.org/10.1145/1062261.1062295openalex-snapshot
Scheduling for heterogeneous processors in server systems
inferred← citeshttps://doi.org/10.1145/1283780.1283826openalex-snapshot
Thermal-aware task scheduling at the system software level
inferred← citeshttps://doi.org/10.1145/1958746.1958819openalex-snapshot
On-line analysis of hardware performance events for workload characterization and processor frequency scaling decisions
inferred← citeshttps://doi.org/10.1145/2524211.2524220openalex-snapshot
Impact of DVFS on n-tier application performance
inferred← citeshttps://doi.org/10.1145/2567658openalex-snapshot
Dynamic Power and Thermal Management of NoC-Based Heterogeneous MPSoCs
inferred← citeshttps://doi.org/10.1147/rd.516.0733openalex-snapshot
System power management support in the IBM POWER6 microprocessor
inferred← citeshttps://doi.org/10.31274/etd-180810-3569openalex-snapshot
Automatic Energy Saving Schemes for Parallel Applications
inferred← citeshttps://doi.org/10.4018/978-1-5225-4044-1.ch002openalex-snapshot
Energy Optimization in Cryptographic Protocols for the Cloud
inferred← citeshttps://doi.org/10.5445/ir/1000015825openalex-snapshot
Task Activity Vectors: A Novel Metric for Temperature-Aware and Energy-Efficient Scheduling
inferred← citeshttps://doi.org/10.5555/1898699.1898828openalex-snapshot
Compiler and runtime support for predictive control of power and cooling
inferred← citeshttps://doi.org/10.5555/1898699.1898829openalex-snapshot
Power-performance efficiency of asymmetric multiprocessors for multi-threaded scientific applications
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