243 citations · 397 across the 10 of their papers we have counts for
12 papers
Relaxed activation analysis of dataflow networks - A clock calculus for machine learning and real-time scheduling
William Gaudelier, Albert Cohen, Dumitru Potop Butucaru
Previous work has shown that the simple dataflow primitives of the Lustre language allow the natural, semantically unambiguous, and compact representation of machine learning (ML)…
RL4ReAl: Reinforcement Learning for Register Allocation
S. VenkataKeerthy, Siddharth Jain, Anilava Kundu +3
We aim to automate decades of research and experience in register allocation, leveraging machine learning. We tackle this problem by embedding a multi-agent reinforcement learning…
Composable and Modular Code Generation in MLIR: A Structured and Retargetable Approach to Tensor Compiler Construction
Nicolas Vasilache, Oleksandr Zinenko, Aart J. C. Bik +9
Despite significant investment in software infrastructure, machine learning systems, runtimes and compilers do not compose properly. We propose a new design aiming at providing unp…
Secure Optimization Through Opaque Observations
Son Tuan Vu, Albert Cohen, Karine Heydemann +2
Secure applications implement software protections against side-channel and physical attacks. Such protections are meaningful at machine code or micro-architectural level, but they…
MLIR: A Compiler Infrastructure for the End of Moore's Law
Chris Lattner, Mehdi Amini, Uday Bondhugula +7
This work presents MLIR, a novel approach to building reusable and extensible compiler infrastructure. MLIR aims to address software fragmentation, improve compilation for heteroge…
On the Representation of Partially Specified Implementations and its Application to the Optimization of Linear Algebra Kernels on GPU
Ulysse Beaugnon, Basile Clément, Nicolas Tollenaere +1
Traditional optimizing compilers rely on rewrite rules to iteratively apply program transformations. This iterative approach hides optimization opportunities behind intermediate tr…