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An empirical study of the effect of source-level loop transformations on compiler stability

https://doi.org/10.1145/3276496
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What this work says

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

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International Journal of Parallel Programming
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Evaluating Iterative Compilation
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Automatic Transformations for Communication-Minimized Parallelization and Locality Optimization in the Polyhedral Model
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Effective Source-to-Source Outlining to Support Whole Program Empirical Optimization
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MediaBench II video: Expediting the next generation of video systems research
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Rose Compiler Support for Object-Oriented Frameworks
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SPEC CPU2000: measuring CPU performance in the New Millennium
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The Parallel Research Kernels
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Performance Metamorphic Testing: Motivation and Challenges
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Polyhedral Source-to-Source Compiler
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An Evaluation of Vectorizing Compilers
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ROSE: COMPILER SUPPORT FOR OBJECT-ORIENTED FRAMEWORKS
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A Fortran to C converter
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SPEC CPU2006 benchmark descriptions
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Iterative optimization in the polyhedral model
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Outer-loop vectorization
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CERE
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What points at this work

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

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Towards an Achievable Performance for the Loop Nests
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Abstractions for C++ code optimizations in parallel high-performance applications
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Automatic mapping of sequential programs to parallel computers with distributed memory.
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A Survey of Optimized Compiler Using Advanced Machine learning and Deep Learning Techniques
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Static Neural Compiler Optimization via Deep Reinforcement Learning
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ALT: Breaking the Wall between Data Layout and Loop Optimizations for Deep Learning Compilation
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Detection of Optimizations Missed by the Compiler
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Pure C++ Approach to Optimized Parallel Traversal of Regular Data Structures
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Refined Input, Degraded Output: The Counterintuitive World of Compiler Behavior
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Shoot Yourself in the Foot — Efficient Code Causes Inefficiency in Compiler Optimizations
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Synchronized Behavior Checking: A Method for Finding Missed Compiler Optimizations
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Seeking Evidence of Further Optimization: Detecting Missed Optimizations through Compiler’s Native Analyses
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Automation of the Application of Data Distribution with Overlapping in Distributed Memory
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Compiler Optimization Prediction with New Self-Improved Optimization Model
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Fast computation of cyclic convolutions and their applications in code-based asymmetric encryption schemes
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On the creation of parallelizing compilers for distributed memory computing systems
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Fast Solvers for Systems of Linear Equations with Block-Band Matrices
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