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Metric Selection for GPU Kernel Classification

https://doi.org/10.1145/3295690
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781119952954.ch1openalex-snapshot
Introduction to Statistical Pattern Recognition
inferredcites →https://doi.org/10.1007/11549468_24openalex-snapshot
An Approach to Performance Prediction for Parallel Applications
inferredcites →https://doi.org/10.1007/s11227-014-1338-zopenalex-snapshot
A statistical performance analyzer framework for OpenCL kernels on Nvidia GPUs
inferredcites →https://doi.org/10.1016/c2015-0-02431-5openalex-snapshot
Programming Massively Parallel Processors
inferredcites →https://doi.org/10.1016/j.future.2017.02.036openalex-snapshot
Locality based warp scheduling in GPGPUs
inferredcites →https://doi.org/10.1016/j.jpdc.2014.02.005openalex-snapshot
What is ahead for parallel computing
inferredcites →https://doi.org/10.1016/j.jpdc.2017.04.002openalex-snapshot
A quantitative roofline model for GPU kernel performance estimation using micro-benchmarks and hardware metric profiling
inferredcites →https://doi.org/10.1016/j.patcog.2016.11.003openalex-snapshot
A Survey on semi-supervised feature selection methods
inferredcites →https://doi.org/10.1016/j.procs.2016.07.111openalex-snapshot
A Survey on Feature Selection
inferredcites →https://doi.org/10.1109/34.574797openalex-snapshot
Feature selection: evaluation, application, and small sample performance
inferredcites →https://doi.org/10.1109/hpca.2014.6835937openalex-snapshot
Improving GPGPU resource utilization through alternative thread block scheduling
inferredcites →https://doi.org/10.1109/hpca.2015.7056063openalex-snapshot
GPGPU performance and power estimation using machine learning
inferredcites →https://doi.org/10.1109/iccke.2016.7802143openalex-snapshot
A dynamic special-purpose scheduler for concurrent kernels on GPU
inferredcites →https://doi.org/10.1109/iiswc.2009.5306797openalex-snapshot
Rodinia: A benchmark suite for heterogeneous computing
inferredcites →https://doi.org/10.1109/iiswc.2009.5306801openalex-snapshot
A characterization and analysis of PTX kernels
inferredcites →https://doi.org/10.1109/iiswc.2015.22openalex-snapshot
A Taxonomy of GPGPU Performance Scaling
inferredcites →https://doi.org/10.1109/isca.2016.29openalex-snapshot
Warped-Slicer: Efficient Intra-SM Slicing through Dynamic Resource Partitioning for GPU Multiprogramming
inferredcites →https://doi.org/10.1109/ispass.2009.4919648openalex-snapshot
Analyzing CUDA workloads using a detailed GPU simulator
inferredcites →https://doi.org/10.1109/ispass.2012.6189201openalex-snapshot
Stargazer: Automated regression-based GPU design space exploration
inferredcites →https://doi.org/10.1109/pdp.2015.51openalex-snapshot
A Practical Performance Model for Compute and Memory Bound GPU Kernels
inferredcites →https://doi.org/10.1109/tpds.2013.257openalex-snapshot
Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling
inferredcites →https://doi.org/10.1109/tpds.2016.2549523openalex-snapshot
Dissecting GPU Memory Hierarchy Through Microbenchmarking
inferredcites →https://doi.org/10.1109/tpds.2016.2586074openalex-snapshot
Understanding Co-Running Behaviors on Integrated CPU/GPU Architectures
inferredcites →https://doi.org/10.1109/tpds.2016.2630697openalex-snapshot
Real-Time GPU Resource Management with Loadable Kernel Modules
inferredcites →https://doi.org/10.1145/1229428.1229479openalex-snapshot
Methods of inference and learning for performance modeling of parallel applications
inferredcites →https://doi.org/10.1145/1356058openalex-snapshot
Proceedings of the 6th annual IEEE/ACM international symposium on Code generation and optimization
inferredcites →https://doi.org/10.1145/1498765.1498785openalex-snapshot
Roofline
inferredcites →https://doi.org/10.1145/2400682.2400716openalex-snapshot
A dynamic self-scheduling scheme for heterogeneous multiprocessor architectures
inferredcites →https://doi.org/10.1145/2597917.2597925openalex-snapshot
Symbiotic scheduling of concurrent GPU kernels for performance and energy optimizations
inferredcites →https://doi.org/10.1145/2632216openalex-snapshot
VGRIS: Virtualized GPU Resource Isolation and Scheduling in Cloud Gaming
inferredcites →https://doi.org/10.1145/2636342openalex-snapshot
A Survey of Methods for Analyzing and Improving GPU Energy Efficiency
inferredcites →https://doi.org/10.1145/2751205.2751213openalex-snapshot
Enabling and Exploiting Flexible Task Assignment on GPU through SM-Centric Program Transformations
inferredcites →https://doi.org/10.1145/2818950.2818979openalex-snapshot
Anatomy of GPU Memory System for Multi-Application Execution
inferredcites →https://doi.org/10.1145/2967938.2967940openalex-snapshot
Scheduling Techniques for GPU Architectures with Processing-In-Memory Capabilities
inferredcites →https://doi.org/10.1145/3007787.3001161openalex-snapshot
Warped-slicer
inferredcites →https://doi.org/10.2307/1268795openalex-snapshot
Applied Nonparametric Statistics
inferredcites →https://doi.org/10.2307/2528964openalex-snapshot
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s00607-023-01255-wopenalex-snapshot
Many-BSP: an analytical performance model for CUDA kernels
inferred← citeshttps://doi.org/10.1007/s11227-020-03209-xopenalex-snapshot
Efficient scheduling of streams on GPGPUs
inferred← citeshttps://doi.org/10.1016/j.jpdc.2019.05.015openalex-snapshot
Troodon: A machine-learning based load-balancing application scheduler for CPU–GPU system
inferred← citeshttps://doi.org/10.1109/csicc49403.2020.9050074openalex-snapshot
Machine Learning-based Interference Detection in GPGPU Concurrent Kernel Execution
inferred← citeshttps://doi.org/10.1109/iccke48569.2019.8964952openalex-snapshot
Predicting Execution Time of CUDA Kernels with Unified Memory Capability
inferred← citeshttps://doi.org/10.1109/icpads47876.2019.00058openalex-snapshot
Optimizing the Aggregated Throughput of GPUs in Public Clouds Based on Adaptive Kernel Reordering
inferred← citeshttps://doi.org/10.1109/pmbs49563.2019.00014openalex-snapshot
CUDA Flux: A Lightweight Instruction Profiler for CUDA Applications
inferred← citeshttps://doi.org/10.1109/tec.2026.3669438openalex-snapshot
Fine-Grained Optimal Allocation of Wind Farm Decoupled Models for CPU-GPU Parallel EMT Simulation
inferred← citeshttps://doi.org/10.1109/tpds.2019.2944602openalex-snapshot
cCUDA: Effective Co-Scheduling of Concurrent Kernels on GPUs
inferred← citeshttps://doi.org/10.1109/tpds.2021.3115630openalex-snapshot
A Survey of GPU Multitasking Methods Supported by Hardware Architecture
inferred← citeshttps://doi.org/10.1145/3638264.3638278openalex-snapshot
AIGPU: An Arithmetic-Intensity-Guided Single-GPU Scheduling Model
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