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Iso-Energy-Efficiency: An Approach to Power-Constrained Parallel Computation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1006/jpdc.1993.1087openalex-snapshot
Scalable Problems and Memory-Bounded Speedup
inferredcites →https://doi.org/10.1007/978-3-540-39924-7_38openalex-snapshot
Improving the Performance of Collective Operations in MPICH
inferredcites →https://doi.org/10.1007/s10586-007-0012-0openalex-snapshot
Performance analysis of MPI collective operations
inferredcites →https://doi.org/10.1007/s10766-006-0028-8openalex-snapshot
Amdahl’s Law Revisited for Single Chip Systems
inferredcites →https://doi.org/10.1016/0026-2692(93)90111-qopenalex-snapshot
Computer architecture: a quantitative approach
inferredcites →https://doi.org/10.1109/88.242438openalex-snapshot
Isoefficiency: measuring the scalability of parallel algorithms and architectures
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.2006.1598114openalex-snapshot
Dynamic Power-Performance Adaptation of Parallel Computation on Chip Multiprocessors
inferredcites →https://doi.org/10.1109/ipdps.2005.214openalex-snapshot
Exploring the Energy-Time Tradeoff in MPI Programs on a Power-Scalable Cluster
inferredcites →https://doi.org/10.1109/ipdps.2005.251openalex-snapshot
Improvement of Power-Performance Efficiency for High-End Computing
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.2008.4536217openalex-snapshot
Towards energy efficient scaling of scientific codes
inferredcites →https://doi.org/10.1109/isca.2000.854380openalex-snapshot
Wattch: a framework for architectural-level power analysis and optimizations
inferredcites →https://doi.org/10.1109/mc.2003.1250885openalex-snapshot
Leakage current: Moore's law meets static power
inferredcites →https://doi.org/10.1109/mc.2005.380openalex-snapshot
High-performance, power-aware distributed computing for scientific applications
inferredcites →https://doi.org/10.1109/mc.2007.445openalex-snapshot
The Green500 List: Encouraging Sustainable Supercomputing
inferredcites →https://doi.org/10.1109/mc.2008.209openalex-snapshot
Amdahl's Law in the Multicore Era
inferredcites →https://doi.org/10.1109/micro.2005.7openalex-snapshot
A Dynamic Compilation Framework for Controlling Microprocessor Energy and Performance
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/scs.2003.1227076openalex-snapshot
Characterizing and improving energy-delay tradeoffs in heterogeneous communication systems
inferredcites →https://doi.org/10.1109/tpds.2009.76openalex-snapshot
PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications
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/10.1145/1122971.1123006openalex-snapshot
Minimizing execution time in MPI programs on an energy-constrained, power-scalable cluster
inferredcites →https://doi.org/10.1145/1188455.1188677openalex-snapshot
S12---The HPC Challenge (HPCC) benchmark suite
inferredcites →https://doi.org/10.1145/1465482.1465560openalex-snapshot
Validity of the single processor approach to achieving large scale computing capabilities
inferredcites →https://doi.org/10.1145/339647.339659openalex-snapshot
Energy-driven integrated hardware-software optimizations using SimplePower
inferredcites →https://doi.org/10.1145/342001.339659openalex-snapshot
Energy-driven integrated hardware-software optimizations using SimplePower
inferredcites →https://doi.org/10.1177/1094342006064482openalex-snapshot
The Tau Parallel Performance System
inferredcites →https://doi.org/10.1177/1094342009106193openalex-snapshot
Energy Profiling and Analysis of the HPC Challenge Benchmarks
inferredcites →https://doi.org/10.5860/choice.42-0990openalex-snapshot
Introduction to parallel computing
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Modeling and analyzing the energy consumption of fork‐join‐based task parallel programs
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Design of self‐adaptable data parallel applications on multicore clusters automatically optimized for performance and energy through load distribution
inferred← citeshttps://doi.org/10.1007/s00450-011-0190-0openalex-snapshot
Power-aware predictive models of hybrid (MPI/OpenMP) scientific applications on multicore systems
inferred← citeshttps://doi.org/10.1007/s00450-014-0269-5openalex-snapshot
Measuring energy consumption using EML (energy measurement library)
inferred← citeshttps://doi.org/10.1007/s11227-014-1236-4openalex-snapshot
Energy measurement, modeling, and prediction for processors with frequency scaling
inferred← citeshttps://doi.org/10.1007/s11390-022-2950-7openalex-snapshot
Adventures Beyond Amdahl’s Law: How Power-Performance Measurement and Modeling at Scale Drive Server and Supercomputer Design
inferred← citeshttps://doi.org/10.1016/j.future.2013.07.004openalex-snapshot
Energy trade-offs analysis using equal-energy maps
inferred← citeshttps://doi.org/10.1016/j.jpdc.2012.01.006openalex-snapshot
Understanding the future of energy-performance trade-off via DVFS in HPC environments
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A survey of power and energy efficient techniques for high performance numerical linear algebra operations
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Model-based optimization of the energy efficiency of multi-threaded applications
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Evaluating fault tolerance on asymmetric multicore systems‐on‐chip using iso‐metrics
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DVFS-Aware Energy-Efficient Implementation of DNNs on Heterogeneous Hybrid Parallel Computers
inferred← citeshttps://doi.org/10.1109/cluster.2011.37openalex-snapshot
An ISO-Energy-Efficient Approach to Scalable System Power-Performance Optimization
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EDR: An energy-aware runtime load distribution system for data-intensive applications in the cloud
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Energy consumption-based performance tuning of software and applications using Particle Swarm Optimization
inferred← citeshttps://doi.org/10.1109/csci51800.2020.00231openalex-snapshot
Energy-Efficient Heterogeneous Computing of Parallel Applications via Power Capping
inferred← citeshttps://doi.org/10.1109/greencom.2012.79openalex-snapshot
Towards an Energy Model for Modular Parallel Scientific Applications
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System energy analysis for shared memory multiprocessing applications
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Energy Efficient Parallel Matrix-Matrix Multiplication for DVFS-enabled Clusters
inferred← citeshttps://doi.org/10.1109/igcc.2015.7393699openalex-snapshot
Using the Greenup, Powerup, and Speedup metrics to evaluate software energy efficiency
inferred← citeshttps://doi.org/10.1109/ipdps.2013.73openalex-snapshot
A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures
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Investigating the Interplay between Energy Efficiency and Resilience in High Performance Computing
inferred← citeshttps://doi.org/10.1109/ipdpsw.2014.75openalex-snapshot
EEWA: Energy-Efficient Workload-Aware Task Scheduling in Multi-core Architectures
inferred← citeshttps://doi.org/10.1109/ipdpsw.2015.122openalex-snapshot
Iso-Power-Efficiency: An Approach to Scaling Application Codes with a Power Budget
inferred← citeshttps://doi.org/10.1109/mascots.2012.35openalex-snapshot
Energy-Aware Execution of Fork-Join-Based Task Parallelism
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Prometheus: Coherent Exploration of Hardware and Software Optimizations Using Aspen
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Energy-Proportional Computing: A New Definition
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Energy Measurement Library (EML) Usage and Overhead Analysis
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Energy Efficiency Modeling of Parallel Applications
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Bi-Objective Optimization of Data-Parallel Applications on Homogeneous Multicore Clusters for Performance and Energy
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Analytical modeling and simulation of the energy consumption of independent tasks
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Unified performance and power modeling of scientific workloads
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Scaling application properties to exascale
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Scalable Energy Efficiency with Resilience for High Performance Computing Systems
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Pareto Governors for Energy-Optimal Computing
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Automated Design Space Exploration with Aspen
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Energy and performance characteristics of different parallel implementations of scientific applications on multicore systems
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A survey on software methods to improve the energy efficiency of parallel computing
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Statistical and machine learning models for optimizing energy in parallel applications
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Power Consumption Trends in Supercomputers: A Study of NERSC's Cori and Perlmutter Machines
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Analytical modeling and simulation of the energy consumption of independent tasks
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Energy measurement and prediction for multi-threaded programs
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Energy Consumption Estimation in Parallel Applications: an Analysis in Real and Theoretical Models
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