243 citations · 369 across the 6 of their papers we have counts for
8 papers
The MLIR Transform Dialect. Your compiler is more powerful than you think
Martin Paul Lücke, Oleksandr Zinenko, William S. Moses +2
To take full advantage of a specific hardware target, performance engineers need to gain control on compilers in order to leverage their domain knowledge about the program and hard…
Strided Difference Bound Matrices
Arjun Pitchanathan, Albert Cohen, Oleksandr Zinenko +1
A wide range of symbolic analysis and optimization problems can be formalized using polyhedra. Sub-classes of polyhedra, also known as sub-polyhedral domains, are sought for their…
Transform Dialect Tutorial
Oleksandr Zinenko
Transform Dialect in MLIR provides operations that can be used to control transformation of the Intermediate Representation (IR) using a different portion of the IR. It refers to t…
High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs
William S. Moses, Ivan R. Ivanov, Jens Domke +3
While parallelism remains the main source of performance, architectural implementations and programming models change with each new hardware generation, often leading to costly app…
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…
Domain-Specific Multi-Level IR Rewriting for GPU
Tobias Gysi, Christoph Müller, Oleksandr Zinenko +6
Traditional compilers operate on a single generic intermediate representation (IR). These IRs are usually low-level and close to machine instructions. As a result, optimizations re…