MLIR
Multi-Level IR Compiler Framework
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Getting Started
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Debugging
FAQ
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Developer Guide
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Code Documentation
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Bindings
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MLIR Python Bindings
Tools
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MLIR : Language Server Protocol
MLIR Reduce
Buffer Deallocation - Internals
Bufferization
Data Layout Modeling
Debug Actions
Diagnostic Infrastructure
Dialect Conversion
Dialects
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'acc' Dialect
'affine' Dialect
'amx' Dialect
'arith' Dialect
'arm_neon' Dialect
'arm_sve' Dialect
'async' Dialect
'bufferization' Dialect
'complex' Dialect
'emitc' Dialect
'gpu' Dialect
'linalg' Dialect
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Linalg OpDSL
'llvm' Dialect
'math' Dialect
'memref' Dialect
'nvvm' Dialect
'omp' Dialect
'pdl' Dialect
'pdl_interp' Dialect
'quant' Dialect
'rocdl' Dialect
'scf' Dialect
'shape' Dialect
'sparse_tensor' Dialect
'spv' Dialect
'std' Dialect
'tensor' Dialect
'vector' Dialect
'x86vector' Dialect
Builtin Dialect
Tensor Operator Set Architecture (TOSA) Dialect
Interfaces
LLVM IR Target
MLIR C API
MLIR Language Reference
Operation Canonicalization
Operation Definition Specification (ODS)
Pass Infrastructure
Passes
Pattern Rewriting : Generic DAG-to-DAG Rewriting
Quantization
Rationale
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Generic DAG Rewriter Infrastructure Rationale
Linalg Dialect Rationale: The Case For Compiler-Friendly Custom Operations
MLIR Rationale
MLIR: Incremental Application to Graph Algorithms in ML Frameworks
MLIR: The case for a simplified polyhedral form
Usage of 'const' in MLIR, for core IR types
Shape Inference
SPIR-V Dialect to LLVM Dialect conversion manual
Symbols and Symbol Tables
Table-driven Declarative Rewrite Rule (DRR)
Traits
Tutorials
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Creating a Dialect
Defining Dialect Attributes and Types
Quickstart tutorial to adding MLIR graph rewrite
Toy Tutorial
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Chapter 1: Toy Language and AST
Chapter 2: Emitting Basic MLIR
Chapter 3: High-level Language-Specific Analysis and Transformation
Chapter 4: Enabling Generic Transformation with Interfaces
Chapter 5: Partial Lowering to Lower-Level Dialects for Optimization
Chapter 6: Lowering to LLVM and CodeGeneration
Chapter 7: Adding a Composite Type to Toy
Understanding the IR Structure
Writing DataFlow Analyses in MLIR
MLIR
MLIR