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Energy, Power, and Performance Characterization of GPGPU Benchmark Programs
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1109/aspdac.2004.1337711openalex-snapshot
Compiler based exploration of DSP energy savings by SIMD operations
inferredcites →https://doi.org/10.1109/greencom-cpscom.2010.140openalex-snapshot
Understanding Power Measurement Implications in the Green500 List
inferredcites →https://doi.org/10.1109/icact.2015.7224902openalex-snapshot
Empirical characterization of power efficiency for large scale data processing
inferredcites →https://doi.org/10.1109/icacte.2010.5578942openalex-snapshot
Power analysis and optimizations for GPU architecture using a power simulator
inferredcites →https://doi.org/10.1109/icpp.2010.78openalex-snapshot
Designing Power-Aware Collective Communication Algorithms for InfiniBand Clusters
inferredcites →https://doi.org/10.1109/icpp.2013.98openalex-snapshot
Effects of Dynamic Voltage and Frequency Scaling on a K20 GPU
inferredcites →https://doi.org/10.1109/igcc.2011.6008582openalex-snapshot
Statistical GPU power analysis using tree-based methods
inferredcites →https://doi.org/10.1109/iiswc.2012.6402918openalex-snapshot
A quantitative study of irregular programs on GPUs
inferredcites →https://doi.org/10.1109/ipdps.2005.213openalex-snapshot
Exploring the Energy-Time Tradeoff in High-Performance Computing
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.2014.54openalex-snapshot
Algorithmic Time, Energy, and Power on Candidate HPC Compute Building Blocks
inferredcites →https://doi.org/10.1109/ipdpsw.2016.164openalex-snapshot
Energy, Power, and Performance Characterization of GPGPU Benchmark Programs
inferredcites →https://doi.org/10.1109/ispass.2005.1430559openalex-snapshot
Studying Thermal Management for Graphics-Processor Architectures
inferredcites →https://doi.org/10.1109/ispass.2013.6557150openalex-snapshot
How a single chip causes massive power bills GPUSimPow: A GPGPU power simulator
inferredcites →https://doi.org/10.1109/mitp.2008.8openalex-snapshot
Green Supercomputing Comes of Age
inferredcites →https://doi.org/10.1109/pccc.2013.6742789openalex-snapshot
Evaluating the performance and energy efficiency of n-body codes on multi-core CPUs and GPUs
inferredcites →https://doi.org/10.1109/saahpc.2012.17openalex-snapshot
Energy Analysis of Parallel Scientific Kernels on Multiple GPUs
inferredcites →https://doi.org/10.1145/1113841.1113844openalex-snapshot
Power-performance considerations of parallel computing on chip multiprocessors
inferredcites →https://doi.org/10.1145/1250734.1250759openalex-snapshot
Optimistic parallelism requires abstractions
inferredcites →https://doi.org/10.1145/1810479.1810510openalex-snapshot
Towards optimizing energy costs of algorithms for shared memory architectures
inferredcites →https://doi.org/10.1145/2576779.2576783openalex-snapshot
Measuring GPU Power with the K20 Built-in Sensor
inferredcites →https://doi.org/10.1145/2576779.2576790openalex-snapshot
Power Modeling for Heterogeneous Processors
inferredcites →https://doi.org/10.1145/2588768.2576783openalex-snapshot
Measuring GPU Power with the K20 Built-in Sensor
inferredcites →https://doi.org/10.1145/2588768.2576790openalex-snapshot
Power Modeling for Heterogeneous Processors
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-21867-5_1openalex-snapshot
Energy Efficient Frequency Scaling on GPUs in Heterogeneous HPC Systems
inferred← citeshttps://doi.org/10.1007/978-3-031-80084-9_4openalex-snapshot
A Comprehensive Analysis of Process Energy Consumption on Multi-socket Systems with GPUs
inferred← citeshttps://doi.org/10.1007/s11227-017-2144-1openalex-snapshot
A performance study of the time-varying cache behavior: a study on APEX, Mantevo, NAS, and PARSEC
inferred← citeshttps://doi.org/10.1007/s11227-022-04473-9openalex-snapshot
Investigating the effect of varying block size on power and energy consumption of GPU kernels
inferred← citeshttps://doi.org/10.1016/b978-0-12-803738-6.00019-7openalex-snapshot
Energy and power considerations of GPUs
inferred← citeshttps://doi.org/10.1016/j.sysarc.2020.101808openalex-snapshot
GPU Energy optimization based on task balance scheduling
inferred← citeshttps://doi.org/10.1109/access.2018.2861571openalex-snapshot
Analyzing Power and Energy Efficiency of Bitonic Mergesort Based on Performance Evaluation
inferred← citeshttps://doi.org/10.1109/access.2019.2915380openalex-snapshot
GPU Energy Consumption Optimization With a Global-Based Neural Network Method
inferred← citeshttps://doi.org/10.1109/e2sc.2016.012openalex-snapshot
Characterizing Power and Performance of GPU Memory Access
inferred← citeshttps://doi.org/10.1109/i-smac55078.2022.9987403openalex-snapshot
A Review on Statistical Power Modelling for a Graphics Processing Unit (GPU)
inferred← citeshttps://doi.org/10.1109/lca.2020.3023723openalex-snapshot
GPU-NEST: Characterizing Energy Efficiency of Multi-GPU Inference Servers
inferred← citeshttps://doi.org/10.1109/sc41404.2022.00070openalex-snapshot
Not All GPUs Are Created Equal: Characterizing Variability in Large-Scale, Accelerator-Rich Systems
inferred← citeshttps://doi.org/10.1109/sc41406.2024.00032openalex-snapshot
PAL: A Variability-Aware Policy for Scheduling ML Workloads in GPU Clusters
inferred← citeshttps://doi.org/10.1109/uic-atc.2017.8397629openalex-snapshot
The time-varying nature of cache utilization: A case study on the Mantevo and Apex benchmarks
inferred← citeshttps://doi.org/10.1109/wscad.2018.00034openalex-snapshot
Performance and Energy Efficiency Evaluation for HPC Applications in Heterogeneous Architectures
inferred← citeshttps://doi.org/10.1145/3152042.3152066openalex-snapshot
GPGPU Power Estimation with Core and Memory Frequency Scaling
inferred← citeshttps://doi.org/10.1145/3297663.3309667openalex-snapshot
Measuring the Energy Efficiency of Transactional Loads on GPGPU
inferred← citeshttps://doi.org/10.1145/3458817.3476188openalex-snapshot
Revealing power, energy and thermal dynamics of a 200PF pre-exascale supercomputer
inferred← citeshttps://doi.org/10.4018/978-1-5225-4760-0.ch003openalex-snapshot
Design and Optimizations of Lattice Boltzmann Methods for Massively Parallel GPU-Based Clusters
inferred← citeshttps://doi.org/10.5555/3018076.3018083openalex-snapshot
Characterizing power and performance of GPU memory access
inferred← citeshttps://doi.org/10.5753/wperformance.2017.3360openalex-snapshot
Analysis of GPU Power Consumption Using Internal Sensors
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