possible papers

Glow: Graph Lowering Compiler Techniques for Neural Networks Nadav Rotem, Jordan Fix, Saleem Abdulrasool, Garret Catron, Summer Deng, Roman Dzhabarov, Nick Gibson, James Hegeman, Meghan Lele, Roman Levenstein, Jack Montgomery, Bert Maher, Satish Nadathur, Jakob Olesen, Jongsoo Park, Artem Rakhov, Misha Smelyanski chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/1805.00907

A Deep Learning Based Cost Model for Automatic Code Optimization. Riyadh Baghdadi, Massinissa Merouani, Mohamed-Hicham Leghettas, Kamel Abdous, Taha Arbaoui, Karima Benatchba, Saman Amarasinghe. Proceedings of the Fourth Conference on Machine Learning and Systems (MLSys).

https://dl.acm.org/doi/abs/10.1145/3213846.3213848?casa_token=cbgdY_Wgz9kAAAAA:IMKfnKAYKl3t9wXFen_yauFHY__vyUHcqSgjENz7RB2QEGeTC1L70FEC5vM9FnKBWdAiL6tw1uC4 Compiler fuzzing through deep learning

“Effective Superword Level Parallelism for Multimedia Extension Architectures” by Samuel Larsen and Saman Amarasinghe (2000)

Energy-Aware Tile Size Selection for Affine Programs on GPUs, M. Jayaweera, M. Kong, Y. Wang, D. Kaeli, Pre-print, Artifact