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An Adaptive Core-Specific Runtime for Energy Efficiency
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-24595-9_17openalex-snapshot
Evaluating the Energy Consumption of OpenMP Applications on Haswell Processors
inferredcites →https://doi.org/10.1007/s00450-011-0190-0openalex-snapshot
Power-aware predictive models of hybrid (MPI/OpenMP) scientific applications on multicore systems
inferredcites →https://doi.org/10.1007/s11432-016-5588-7openalex-snapshot
The Sunway TaihuLight supercomputer: system and applications
inferredcites →https://doi.org/10.1016/j.jpdc.2010.02.005openalex-snapshot
Dynamic slack allocation algorithms for energy minimization on parallel machines
inferredcites →https://doi.org/10.1109/ccgrid.2009.88openalex-snapshot
Energy-Efficient Cluster Computing via Accurate Workload Characterization
inferredcites →https://doi.org/10.1109/cgc.2012.62openalex-snapshot
Green Queue: Customized Large-Scale Clock Frequency Scaling
inferredcites →https://doi.org/10.1109/cluster.2013.6702684openalex-snapshot
Optimizing power allocation to CPU and memory subsystems in overprovisioned HPC systems
inferredcites →https://doi.org/10.1109/clustr.2006.311839openalex-snapshot
Emprical study on Reducing Energy of Parallel Programs using Slack Reclamation by DVFS in a Power-scalable High Performance Cluster
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/icpp.2015.72openalex-snapshot
Using Per-Loop CPU Clock Modulation for Energy Efficiency in OpenMP Applications
inferredcites →https://doi.org/10.1109/ipdps.2005.346openalex-snapshot
Power and Energy Profiling of Scientific Applications on Distributed Systems
inferredcites →https://doi.org/10.1109/ipdps.2008.4536223openalex-snapshot
Power efficiency in high performance computing
inferredcites →https://doi.org/10.1109/ipdpsw.2012.116openalex-snapshot
Beyond DVFS: A First Look at Performance under a Hardware-Enforced Power Bound
inferredcites →https://doi.org/10.1109/ipdpsw.2015.144openalex-snapshot
Using Dynamic Duty Cycle Modulation to Improve Energy Efficiency in High Performance Computing
inferredcites →https://doi.org/10.1109/ipdpsw.2015.70openalex-snapshot
An Energy Efficiency Feature Survey of the Intel Haswell Processor
inferredcites →https://doi.org/10.1109/sc.2005.3openalex-snapshot
A Power-Aware Run-Time System for High-Performance Computing
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.2014.71openalex-snapshot
Maximizing Throughput of Overprovisioned HPC Data Centers Under a Strict Power Budget
inferredcites →https://doi.org/10.1145/1013235.1013282openalex-snapshot
Dynamic voltage and frequency scaling based on workload decomposition
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/10.1145/2212908.2212927openalex-snapshot
Studying the impact of application-level optimizations on the power consumption of multi-core architectures
inferredcites →https://doi.org/10.1145/2464996.2465009openalex-snapshot
Exploring hardware overprovisioning in power-constrained, high performance computing
inferredcites →https://doi.org/10.1145/2536430.2536437openalex-snapshot
OpenMP and MPI application energy measurement variation
inferredcites →https://doi.org/10.1145/2768405.2768408openalex-snapshot
Application Runtime Variability and Power Optimization for Exascale Computers
inferredcites →https://doi.org/10.1145/2807591.2807658openalex-snapshot
A case for application-oblivious energy-efficient MPI runtime
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-43222-5_16openalex-snapshot
Evaluating the Advantage of Reactive MPI-aware Power Control Policies
inferred← citeshttps://doi.org/10.1109/argencon49523.2020.9505498openalex-snapshot
Towards Management of Energy Consumption in HPC Systems with Fault Tolerance
inferred← citeshttps://doi.org/10.1109/cluster49012.2020.00068openalex-snapshot
Toward an End-to-End Auto-tuning Framework in HPC PowerStack
inferred← citeshttps://doi.org/10.1109/cluster59578.2024.00026openalex-snapshot
FCUFS: Core-Level Frequency Tuning for Energy Optimization on Intel Processors
inferred← citeshttps://doi.org/10.1109/hpcc/smartcity/dss.2018.00159openalex-snapshot
Improve Energy Efficiency by Processor Overclocking and Memory Frequency Scaling
inferred← citeshttps://doi.org/10.1109/igsc48788.2019.8957174openalex-snapshot
Fine-Grained Energy Efficiency Using Per-Core DVFS with an Adaptive Runtime System
inferred← citeshttps://doi.org/10.1109/igsc55832.2022.9969367openalex-snapshot
Optimizing Energy Efficiency of Node.js Applications with CPU DVFS Awareness
inferred← citeshttps://doi.org/10.1109/ipdps47924.2020.00087openalex-snapshot
What does Power Consumption Behavior of HPC Jobs Reveal? : Demystifying, Quantifying, and Predicting Power Consumption Characteristics
inferred← citeshttps://doi.org/10.1109/ipdps53621.2022.00126openalex-snapshot
PowerSpector: Towards Energy Efficiency with Calling-Context-Aware Profiling
inferred← citeshttps://doi.org/10.1109/ipdps65963.2026.00082openalex-snapshot
Toward Energy-Efficient HPC: Insights from Power Profiling a Cloud-Resolving Earth System Model
inferred← citeshttps://doi.org/10.1109/ispass61541.2024.00018openalex-snapshot
RTune: Towards Automated and Coordinated Optimization of Computing and Computational Objectives of Parallel Iterative Applications
inferred← citeshttps://doi.org/10.1109/pmbs54543.2021.00011openalex-snapshot
Understanding power variation and its implications on performance optimization on the Cori supercomputer
inferred← citeshttps://doi.org/10.1109/scw63240.2024.00189openalex-snapshot
Understanding VASP Power Profiles on NVIDIA A100 GPUs
inferred← citeshttps://doi.org/10.1109/tc.2020.2995269openalex-snapshot
COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI Applications
inferred← citeshttps://doi.org/10.1109/tpds.2020.3000418openalex-snapshot
Countdown Slack: A Run-Time Library to Reduce Energy Footprint in Large-Scale MPI Applications
inferred← citeshttps://doi.org/10.1109/tpds.2020.3045983openalex-snapshot
Fine-grained Powercap Allocation for Power-constrained Systems based on Multi-objective Machine Learning
inferred← citeshttps://doi.org/10.1109/ucc56403.2022.00031openalex-snapshot
Performance, Energy and Parallelism: Using Near Data Processing in Utility and Cloud Computing
inferred← citeshttps://doi.org/10.1145/3149412.3149418openalex-snapshot
Improving Energy Efficiency in Memory-constrained Applications Using Core-specific Power Control
inferred← citeshttps://doi.org/10.1145/3624062.3624275openalex-snapshot
ReAPER: Region Aware Power and Energy Regulator
inferred← citeshttps://doi.org/10.1145/3710848.3710875openalex-snapshot
EVeREST: An Effective and Versatile Runtime Energy Saving Tool for GPUs
inferred← citeshttps://doi.org/10.1145/3712285.3759879openalex-snapshot
Minimizing Power Waste in Heterogenous Computing via Adaptive Uncore Scaling
inferred← citeshttps://doi.org/10.1145/3721145.3725759openalex-snapshot
EVeREST-C: An Effective and Versatile Runtime Energy Saving Tool for CPUs
inferred← citeshttps://doi.org/10.1145/3818685openalex-snapshot
Power Scheduling for Maximizing Throughput and Fairness in Co-running Applications
inferred← citeshttps://doi.org/10.1177/1094342018774405openalex-snapshot
Effect of frequency scaling granularity on energy-saving strategies
inferred← citeshttps://doi.org/10.23919/isc.2024.10528943openalex-snapshot
Power Consumption Trends in Supercomputers: A Study of NERSC's Cori and Perlmutter Machines
inferred← citeshttps://doi.org/10.26599/tst.2018.9020104openalex-snapshot
A holistic energy-efficient approach for a processor-memory system
inferred← citeshttps://doi.org/10.48550/arxiv.2110.00617openalex-snapshot
Cuttlefish: Library for Achieving Energy Efficiency in Multicore Parallel Programs
inferred← citeshttps://doi.org/10.5281/zenodo.21595313openalex-snapshot
A Survey of Dynamic Power Saving Strategies in Real Systems
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