Compilergym: Robust, performant compiler optimization environments for ai research
Interest in applying Artificial Intelligence (AI) techniques to compiler optimizations is
increasing rapidly, but compiler research has a high entry barrier. Unlike in other domains …
increasing rapidly, but compiler research has a high entry barrier. Unlike in other domains …
Automating reinforcement learning architecture design for code optimization
Reinforcement learning (RL) is emerging as a powerful technique for solving complex code
optimization tasks with an ample search space. While promising, existing solutions require a …
optimization tasks with an ample search space. While promising, existing solutions require a …
Automatic creation of high-bandwidth memory architectures from domain-specific languages: The case of computational fluid dynamics
S Soldavini, K Friebel, M Tibaldi, G Hempel… - ACM Transactions on …, 2023 - dl.acm.org
Numerical simulations can help solve complex problems. Most of these algorithms are
massively parallel and thus good candidates for FPGA acceleration thanks to spatial …
massively parallel and thus good candidates for FPGA acceleration thanks to spatial …
LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers
M Merouani, KA Boudaoud, IN Aouadj… - arXiv preprint arXiv …, 2024 - arxiv.org
While polyhedral compilers have shown success in implementing advanced code
transformations, they still have challenges in selecting the most profitable transformations …
transformations, they still have challenges in selecting the most profitable transformations …
Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities
To cope with the increasing complexity of digital systems programming, deep learning
techniques have recently been proposed to enhance software deployment by analysing …
techniques have recently been proposed to enhance software deployment by analysing …
Reinforcement learning strategies for compiler optimization in high level synthesis
H Shahzad, A Sanaullah, S Arora… - 2022 IEEE/ACM …, 2022 - ieeexplore.ieee.org
High Level Synthesis (HLS) offers a possible programmability solution for FPGAs by
automatically compiling CPU codes to custom hardware configurations, but currently …
automatically compiling CPU codes to custom hardware configurations, but currently …
Supercompiler Code Optimization with Zero-Shot Reinforcement Learning
Effective code optimization in compilers plays a central role in computer and software
engineering. While compilers can be made to automatically search the optimization space …
engineering. While compilers can be made to automatically search the optimization space …
Towards intelligent compiler optimization
The future of computation is massively parallel and heterogeneous with specialized
accelerator devices and instruction sets in both edge-and cluster-computing. However …
accelerator devices and instruction sets in both edge-and cluster-computing. However …
LoopTune: Optimizing Tensor Computations with Reinforcement Learning
Advanced compiler technology is crucial for enabling machine learning applications to run
on novel hardware, but traditional compilers fail to deliver performance, popular auto-tuners …
on novel hardware, but traditional compilers fail to deliver performance, popular auto-tuners …
The Next 700 ML-Enabled Compiler Optimizations
There is a growing interest in enhancing compiler optimizations with ML models, yet
interactions between compilers and ML frameworks remain challenging. Some optimizations …
interactions between compilers and ML frameworks remain challenging. Some optimizations …