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Design of an Energy Aware Petaflops Class High Performance Cluster Based on Power Architecture
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/10968987_3openalex-snapshot
SLURM: Simple Linux Utility for Resource Management
inferredcites →https://doi.org/10.1007/978-1-4939-2092-1_4openalex-snapshot
Techniques to Achieve Energy Proportionality in Data Centers: A Survey
inferredcites →https://doi.org/10.1007/978-3-319-23219-5_37openalex-snapshot
Power Capping in High Performance Computing Systems
inferredcites →https://doi.org/10.1007/978-3-319-41321-1_10openalex-snapshot
Predictive Modeling for Job Power Consumption in HPC Systems
inferredcites →https://doi.org/10.1007/978-3-319-43659-3_9openalex-snapshot
Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer
inferredcites →https://doi.org/10.1007/s00450-010-0129-xopenalex-snapshot
Utilization driven power-aware parallel job scheduling
inferredcites →https://doi.org/10.1007/s10586-007-0045-4openalex-snapshot
Power capping: a prelude to power shifting
inferredcites →https://doi.org/10.1016/j.cpc.2010.05.002openalex-snapshot
Solving lattice QCD systems of equations using mixed precision solvers on GPUs
inferredcites →https://doi.org/10.1109/e2sc.2014.13openalex-snapshot
HDEEM: High Definition Energy Efficiency Monitoring
inferredcites →https://doi.org/10.1109/hpcsim.2016.7568400openalex-snapshot
User-space APIs for dynamic power management in many-core ARMv8 computing nodes
inferredcites →https://doi.org/10.1109/hpcsim.2016.7568419openalex-snapshot
Evaluation of synchronization protocols for fine-grain HPC sensor data time-stamping and collection
inferredcites →https://doi.org/10.1109/igcc.2015.7393692openalex-snapshot
ARDUPOWER: A low-cost wattmeter to improve energy efficiency of HPC applications
inferredcites →https://doi.org/10.1109/igcc.2015.7393710openalex-snapshot
Power measurements for compute nodes: Improving sampling rates, granularity and accuracy
inferredcites →https://doi.org/10.1109/mc.2016.308openalex-snapshot
Standardizing Power Monitoring and Control at Exascale
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.2016.37openalex-snapshot
The Mont-Blanc Prototype: An Alternative Approach for HPC Systems
inferredcites →https://doi.org/10.1145/2063384.2063478openalex-snapshot
Scaling lattice QCD beyond 100 GPUs
inferredcites →https://doi.org/10.1145/2807591.2807643openalex-snapshot
Dynamic power sharing for higher job throughput
inferredcites →https://doi.org/10.14529/jsfi160104openalex-snapshot
Server Level Liquid Cooling: Do Higher System Temperatures Improve Energy Efficiency?
inferredcites →https://doi.org/10.48550/arxiv.1011.0199openalex-snapshot
BQCD - Berlin quantum chromodynamics program
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-02465-9_26openalex-snapshot
Early Experience on Running OpenStaPLE on DAVIDE
inferred← citeshttps://doi.org/10.1007/978-3-030-02465-9_28openalex-snapshot
Improving Performance and Energy Efficiency on OpenPower Systems Using Scalable Hardware-Software Co-design
inferred← citeshttps://doi.org/10.1007/978-3-030-43222-5_15openalex-snapshot
Energy-Efficiency Tuning of a Lattice Boltzmann Simulation Using MERIC
inferred← citeshttps://doi.org/10.1007/978-3-030-78713-4_11openalex-snapshot
Proctor: A Semi-Supervised Performance Anomaly Diagnosis Framework for Production HPC Systems
inferred← citeshttps://doi.org/10.1007/s10586-020-03219-7openalex-snapshot
DiG: enabling out-of-band scalable high-resolution monitoring for data-center analytics, automation and control (extended)
inferred← citeshttps://doi.org/10.1016/j.engappai.2019.07.008openalex-snapshot
A semisupervised autoencoder-based approach for anomaly detection in high performance computing systems
inferred← citeshttps://doi.org/10.1016/j.jpdc.2019.04.021openalex-snapshot
Analyzing the performance/power tradeoff of the rCUDA middleware for future exascale systems
inferred← citeshttps://doi.org/10.1016/j.procs.2025.04.358openalex-snapshot
Highlights on Utilizing Machine Learning for High Performance Computing Systems
inferred← citeshttps://doi.org/10.1016/j.rser.2023.114019openalex-snapshot
A review on the decarbonization of high-performance computing centers
inferred← citeshttps://doi.org/10.1109/aicas.2019.8771527openalex-snapshot
Online Anomaly Detection in HPC Systems
inferred← citeshttps://doi.org/10.1109/hipineb.2018.00014openalex-snapshot
Improving the Efficiency of Future Exascale Systems with rCUDA
inferred← citeshttps://doi.org/10.1109/jiot.2020.2986702openalex-snapshot
pAElla: Edge AI-Based Real-Time Malware Detection in Data Centers
inferred← citeshttps://doi.org/10.1109/jiot.2021.3125885openalex-snapshot
ExaMon-X: A Predictive Maintenance Framework for Automatic Monitoring in Industrial IoT Systems
inferred← citeshttps://doi.org/10.1145/3203217.3205863openalex-snapshot
The D.A.V.I.D.E. big-data-powered fine-grain power and performance monitoring support
inferred← citeshttps://doi.org/10.1145/3295816.3295819openalex-snapshot
Evaluation of NTP/PTP fine-grain synchronization performance in HPC clusters
inferred← citeshttps://doi.org/10.1145/3339186.3339215openalex-snapshot
Paving the Way Toward Energy-Aware and Automated Datacentre
inferred← citeshttps://doi.org/10.1145/3718350.3718359openalex-snapshot
Improving the Efficiency of a Deep Reinforcement Learning-Based Power Management System for HPC Clusters Using Curriculum Learning
inferred← citeshttps://doi.org/10.1177/1094342018814593openalex-snapshot
Pricing schemes for energy-efficient HPC systems: Design and exploration
inferred← citeshttps://doi.org/10.1186/s13677-023-00546-zopenalex-snapshot
Investigating performance metrics for container-based HPC environments using x86 and OpenPOWER systems
inferred← citeshttps://doi.org/10.1609/aaai.v33i01.33019428openalex-snapshot
Anomaly Detection Using Autoencoders in High Performance Computing Systems
inferred← citeshttps://doi.org/10.3233/978-1-61499-843-3-723openalex-snapshot
Multi-Node Advanced Performance and Power Analysis with Paraver
inferred← citeshttps://doi.org/10.3390/jlpea8020013openalex-snapshot
Performance and Power Analysis of HPC Workloads on Heterogeneous Multi-Node Clusters
inferred← citeshttps://doi.org/10.4108/eai.13-7-2018.163972openalex-snapshot
Big Computing: Where are we heading?
inferred← citeshttps://doi.org/10.4203/ccp.112.33openalex-snapshot
Fine-grained application tuning on OpenPOWER HPC systems
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