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A multi-objective auto-tuning framework for parallel codes
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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/nme.2944openalex-snapshot
Convergence speed in multi‐objective metaheuristics: Efficiency criteria and empirical study
inferredcites →https://doi.org/10.1007/3-540-44719-9_9openalex-snapshot
A Micro-Genetic Algorithm for Multiobjective Optimization
inferredcites →https://doi.org/10.1007/978-3-642-28652-0_6openalex-snapshot
Analytical Bounds for Optimal Tile Size Selection
inferredcites →https://doi.org/10.1007/s10766-010-0161-2openalex-snapshot
Milepost GCC: Machine Learning Enabled Self-tuning Compiler
inferredcites →https://doi.org/10.1016/j.cor.2009.02.006openalex-snapshot
DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems
inferredcites →https://doi.org/10.1023/a:1008202821328openalex-snapshot
Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
inferredcites →https://doi.org/10.1023/a:1015729001611openalex-snapshot
Adaptive Optimizing Compilers for the 21st Century
inferredcites →https://doi.org/10.1088/1742-6596/16/1/071openalex-snapshot
OSKI: A library of automatically tuned sparse matrix kernels
inferredcites →https://doi.org/10.1093/comjnl/7.4.308openalex-snapshot
A Simplex Method for Function Minimization
inferredcites →https://doi.org/10.1109/4235.797969openalex-snapshot
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
inferredcites →https://doi.org/10.1109/cec.2005.1554717openalex-snapshot
GDE3: The third Evolution Step of Generalized Differential Evolution
inferredcites →https://doi.org/10.1109/cgo.2006.37openalex-snapshot
Using Machine Learning to Focus Iterative Optimization
inferredcites →https://doi.org/10.1109/cgo.2007.21openalex-snapshot
Iterative Optimization in the Polyhedral Model: Part I, One-Dimensional Time
inferredcites →https://doi.org/10.1109/cgo.2009.24openalex-snapshot
Scenario Based Optimization: A Framework for Statically Enabling Online Optimizations
inferredcites →https://doi.org/10.1109/icpads.2009.77openalex-snapshot
Adaptive Multi-versioning for OpenMP Parallelization via Machine Learning
inferredcites →https://doi.org/10.1109/ipdps.2009.5161054openalex-snapshot
A scalable auto-tuning framework for compiler optimization
inferredcites →https://doi.org/10.1109/ipdps.2010.5470421openalex-snapshot
An auto-tuning framework for parallel multicore stencil computations
inferredcites →https://doi.org/10.1109/ipdps.2010.5470459openalex-snapshot
DynTile: Parametric tiled loop generation for parallel execution on multicore processors
inferredcites →https://doi.org/10.1109/ipdps.2011.70openalex-snapshot
PATUS: A Code Generation and Autotuning Framework for Parallel Iterative Stencil Computations on Modern Microarchitectures
inferredcites →https://doi.org/10.1109/ipdps.2011.86openalex-snapshot
Online Adaptive Code Generation and Tuning
inferredcites →https://doi.org/10.1109/isorc.2010.15openalex-snapshot
Multi-objective Exploration of Compiler Optimizations for Real-Time Systems
inferredcites →https://doi.org/10.1109/jproc.2004.840306openalex-snapshot
SPIRAL: Code Generation for DSP Transforms
inferredcites →https://doi.org/10.1109/pact.2000.888348openalex-snapshot
Combined selection of tile sizes and unroll factors using iterative compilation
inferredcites →https://doi.org/10.1109/pact.2004.1342537openalex-snapshot
Code generation in the polyhedral model is easier than you think
inferredcites →https://doi.org/10.1109/sc.1998.10004openalex-snapshot
Automatically Tuned Linear Algebra Software
inferredcites →https://doi.org/10.1109/sc.2002.10062openalex-snapshot
Active Harmony: Towards Automated Performance Tuning
inferredcites →https://doi.org/10.1109/sc.2006.55openalex-snapshot
Sequoia: Programming the Memory Hierarchy
inferredcites →https://doi.org/10.1145/1250734.1250780openalex-snapshot
Parameterized tiled loops for free
inferredcites →https://doi.org/10.1145/1273442.1250780openalex-snapshot
Parameterized tiled loops for free
inferredcites →https://doi.org/10.1145/1379022.1375594openalex-snapshot
Iterative optimization in the polyhedral model
inferredcites →https://doi.org/10.1145/1542275.1542301openalex-snapshot
Parametric multi-level tiling of imperfectly nested loops
inferredcites →https://doi.org/10.1145/1772954.1772965openalex-snapshot
Automated just-in-time compiler tuning
inferredcites →https://doi.org/10.1145/1772954.1772983openalex-snapshot
Parameterized tiling revisited
inferredcites →https://doi.org/10.1145/301631.301661openalex-snapshot
A fast Fourier transform compiler
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Compiler multiversioning for automatic task granularity control
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Spectral turning bands for efficient Gaussian random fields generation on GPUs and accelerators
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Autotuning CUDA compiler parameters for heterogeneous applications using the OpenTuner framework
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Compiler Generated Progress Estimation for OpenMP Programs
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Tuning Parallel Applications
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Random Fields Generation on the GPU with the Spectral Turning Bands Method
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Multi-Objective Auto-Tuning with Insieme: Optimization and Trade-Off Analysis for Time, Energy and Resource Usage
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Multi Objective Optimization of HPC Kernels for Performance, Power, and Energy
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OpenMP : heterogenous execution and data movements : 11th International Workshop on OpenMP, IWOMP 2015, Aachen, Germany, October 1-2, 2015 : proceedings
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Application-Level Energy Awareness for OpenMP
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Adaptive Granularity Control in Task Parallel Programs Using Multiversioning
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On the potential of significance-driven execution for energy-aware HPC
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Multi-objective Parameter Auto-tuning for Tissue Image Segmentation Workflows
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Performance benchmarking and auto-tuning for scientific applications on virtual cluster
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Static Compiler Analyses for Application-specific Optimization of Task-Parallel Runtime Systems
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Prediction assisted runtime based energy tuning mechanism for HPC applications
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Autotuning Under Tight Budget Constraints: A Transparent Design of Experiments Approach
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Kill Two Birds with One Stone: Auto-tuning RocksDB for High Bandwidth and Low Latency
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An architecture for flexible auto-tuning: The Periscope Tuning Framework 2.0
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A Region-Aware Multi-Objective Auto-Tuner for Parallel Programs
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Online-Autotuning of Parallel SAH kD-Trees
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Taming the "Monster": Overcoming Program Optimization Challenges on SW26010 Through Precise Performance Modeling
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Blk-Tune: Blocking Parameter Auto-Tuning to Minimize Input-Output Traffic for Flash-Based Out-of-Core Stencil Computations
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Online-Autotuning in the Presence of Algorithmic Choice
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A Sampling Based Strategy to Automatic Performance Tuning of GPU Programs
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Automatic Selection of Tuning Plugins in PTF Using Machine Learning
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COMPOFF: A Compiler Cost model using Machine Learning to predict the Cost of OpenMP Offloading
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One OpenCL to rule them all?
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Parallel frame rendering: trading responsiveness for energy on a mobile GPU
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Modeling CPU Energy Consumption of HPC Applications on the IBM POWER7
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Characterizing Performance and Cache Impacts of Code Multi-versioning on Multicore Architectures
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Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp
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