7 citations · 9 across the 5 of their papers we have counts for
5 papers
Compressing Structured Tensor Algebra
Mahdi Ghorbani, Emilien Bauer, Tobias Grosser +1
Tensor algebra is a crucial component for data-intensive workloads such as machine learning and scientific computing. As the complexity of data grows, scientists often encounter a…
Verifying Peephole Rewriting In SSA Compiler IRs
Siddharth Bhat, Alex Keizer, Chris Hughes +2
There is an increasing need for domain-specific reasoning in modern compilers. This has fueled the use of tailored intermediate representations (IRs) based on static single assignm…
mlirSynth: Automatic, Retargetable Program Raising in Multi-Level IR using Program Synthesis
Alexander Brauckmann, Elizabeth Polgreen, Tobias Grosser +1
MLIR is an emerging compiler infrastructure for modern hardware, but existing programs cannot take advantage of MLIR's high-performance compilation if they are described in lower-l…
Fortran performance optimisation and auto-parallelisation by leveraging MLIR-based domain specific abstractions in Flang
Nick Brown, Maurice Jamieson, Anton Lydike +2
MLIR has become popular since it was open sourced in 2019. A sub-project of LLVM, the flexibility provided by MLIR to represent Intermediate Representations (IR) as dialects at dif…
MOM: Matrix Operations in MLIR
Lorenzo Chelini, Henrik Barthels, Paolo Bientinesi +3
Modern research in code generators for dense linear algebra computations has shown the ability to produce optimized code with a performance which compares and often exceeds the one…