MLIR: Scaling compiler infrastructure for domain specific computation

C Lattner, M Amini, U Bondhugula… - 2021 IEEE/ACM …, 2021‏ - ieeexplore.ieee.org
This work presents MLIR, a novel approach to building reusable and extensible compiler
infrastructure. MLIR addresses software fragmentation, compilation for heterogeneous …

MLIR: A compiler infrastructure for the end of Moore's law

C Lattner, M Amini, U Bondhugula, A Cohen… - arxiv preprint arxiv …, 2020‏ - arxiv.org
This work presents MLIR, a novel approach to building reusable and extensible compiler
infrastructure. MLIR aims to address software fragmentation, improve compilation for …

Tensor comprehensions: Framework-agnostic high-performance machine learning abstractions

N Vasilache, O Zinenko, T Theodoridis, P Goyal… - arxiv preprint arxiv …, 2018‏ - arxiv.org
Deep learning models with convolutional and recurrent networks are now ubiquitous and
analyze massive amounts of audio, image, video, text and graph data, with applications in …

Tiramisu: A polyhedral compiler for expressing fast and portable code

R Baghdadi, J Ray, MB Romdhane… - 2019 IEEE/ACM …, 2019‏ - ieeexplore.ieee.org
This paper introduces Tiramisu, a polyhedral framework designed to generate high
performance code for multiple platforms including multicores, GPUs, and distributed …

A Comprehensive Survey of Benchmarks for Improvement of Software's Non-Functional Properties

A Blot, J Petke - ACM Computing Surveys, 2025‏ - dl.acm.org
Despite recent increase in research on improvement of non-functional properties of
software, such as energy usage or program size, there is a lack of standard benchmarks for …

Polly—performing polyhedral optimizations on a low-level intermediate representation

T Grosser, A Groesslinger, C Lengauer - Parallel Processing Letters, 2012‏ - World Scientific
The polyhedral model for loop parallelization has proved to be an effective tool for advanced
optimization and automatic parallelization of programs in higher-level languages. Yet, to …

A practical automatic polyhedral parallelizer and locality optimizer

U Bondhugula, A Hartono, J Ramanujam… - Proceedings of the 29th …, 2008‏ - dl.acm.org
We present the design and implementation of an automatic polyhedral source-to-source
transformation framework that can optimize regular programs (sequences of possibly …

Polymage: Automatic optimization for image processing pipelines

RT Mullapudi, V Vasista, U Bondhugula - ACM SIGARCH Computer …, 2015‏ - dl.acm.org
This paper presents the design and implementation of PolyMage, a domain-specific
language and compiler for image processing pipelines. An image processing pipeline can …

Polygeist: Raising C to polyhedral MLIR

WS Moses, L Chelini, R Zhao… - 2021 30th International …, 2021‏ - ieeexplore.ieee.org
We present Polygeist, a new compilation flow that connects the MLIR compiler infrastructure
to cutting edge polyhedral optimization tools. It consists of a C and C++ frontend capable of …

Automatic transformations for communication-minimized parallelization and locality optimization in the polyhedral model

U Bondhugula, M Baskaran, S Krishnamoorthy… - … CC 2008, Held as Part of …, 2008‏ - Springer
The polyhedral model provides powerful abstractions to optimize loop nests with regular
accesses. Affine transformations in this model capture a complex sequence of execution …