230 citations · 260 across the 6 of their papers we have counts for
6 papers
T-LLM Compiler: Trusted LLM-based Code Optimization and Verification Framework
Zahra Fazel, Sunanda Gamage, Shayan Shirahmad Gale Bagi +5
Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, and it has since emerged as on…
Protean Compiler: An Agile Framework to Drive Fine-grain Phase Ordering
Amir H. Ashouri, Shayan Shirahmad Gale Bagi, Kavin Satheeskumar +6
The phase ordering problem has been a long-standing challenge since the late 1970s, yet it remains an open problem due to having a vast optimization space and an unbounded nature,…
ACPO: AI-Enabled Compiler Framework
Amir H. Ashouri, Muhammad Asif Manzoor, Duc Minh Vu +7
The key to performance optimization of a program is to decide correctly when a certain transformation should be applied by a compiler. This is an ideal opportunity to apply machine…
MLGOPerf: An ML Guided Inliner to Optimize Performance
Amir H. Ashouri, Mostafa Elhoushi, Yuzhe Hua +4
For the past 25 years, we have witnessed an extensive application of Machine Learning to the Compiler space; the selection and the phase-ordering problem. However, limited works ha…
Fast On-the-fly Retraining-free Sparsification of Convolutional Neural Networks
Amir H. Ashouri, Tarek S. Abdelrahman, Alwyn Dos Remedios
Modern Convolutional Neural Networks (CNNs) are complex, encompassing millions of parameters. Their deployment exerts computational, storage and energy demands, particularly on emb…
A Survey on Compiler Autotuning using Machine Learning
Amir H. Ashouri, William Killian, John Cavazos +2
Since the mid-1990s, researchers have been trying to use machine-learning based approaches to solve a number of different compiler optimization problems. These techniques primarily…