mlir

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mlir is an intermediate representation language created in 2019 by Chris Lattner.

Source code:

git clone https://github.com/tensorflow/mlir

#401on PLDB

5Years Old

84Repos

"Multi-Level Intermediate Representation" Compiler Infrastructure

mlir website
mlir is developed on GitHub and has 1,678 stars
There are at least 84 mlir repos on GitHub
mlir first developed in https://github.com/tensorflow
file extensions for mlir include mlir
The Google BigQuery Public Dataset GitHub snapshot shows 27 users using mlir in 30 repos on GitHub
Read more about mlir on the web: 1. 2.

Example from the web:

// Syntactically similar to LLVM:
func @testFunction(%arg0: i32) {
  %x = call @thingToCall(%arg0) : (i32) -> i32
  br ^bb1
^bb1:
  %y = addi %x, %x : i32
  return %y : i32
}

Example from Compiler Explorer:

// Example code of an affine reduction.
// MLIR example code may not always work out of the box because the textual MLIR format is not stable.
// The example tries to be compatible with the latest MLIR version, which may not work on previous versions.

func @affine_parallel_with_reductions_i64(%arg0: memref<3x3xi64>, %arg1: memref<3x3xi64>) -> (i64, i64) {
  %0:2 = affine.parallel (%kx, %ky) = (0, 0) to (2, 2) reduce ("addi", "muli") -> (i64, i64) {
            %1 = affine.load %arg0[%kx, %ky] : memref<3x3xi64>
            %2 = affine.load %arg1[%kx, %ky] : memref<3x3xi64>
            %3 = arith.muli %1, %2 : i64
            %4 = arith.addi %1, %2 : i64
            affine.yield %3, %4 : i64, i64
          }
  return %0#0, %0#1 : i64, i64
}

Feature	Supported	Token	Example
Comments	✓		// A comment
Line Comments	✓	//	// A comment
Semantic Indentation	X

mlir - Intermediate representation language

Language features