Generic Tensors

This is an out-of-tree MLIR frontend for a simple text based language for tensors. It is just a demonstration and not particularly useful. It does very little error checking.

Docker

Running Ubuntu

$ mkdir /Users/<user-name>/gen_ten
$ docker run \
--name ubuntu \
-e HOST_IP=$(ifconfig en0 | awk '/ *inet /{print $2}') \
-v /Users/<user-name>/gen_ten:/gen_ten \
-t -i \
ubuntu /bin/bash

Updating apt-get

$ apt-get update

Installing Tools

$ apt-get install -y build-essential git cmake clang llvm

Getting and Building MLIR

Checkout hash is last tested, newer ones may work too.

$ cd /gen_ten
$ git clone https://github.com/llvm/llvm-project.git
$ cd llvm-project
$ git checkout ff758372bd51840b4f566968fb0929d19557dd9b
$ mkdir build
$ cd build
$ cmake -G "Unix Makefiles" ../llvm \
  -DLLVM_ENABLE_PROJECTS="clang;mlir;libcxx;libcxxabi" \
  -DLLVM_BUILD_EXAMPLES=ON \
  -DLLVM_TARGETS_TO_BUILD="X86;AArch64" \
  -DCMAKE_BUILD_TYPE=Release \
  -DLLVM_ENABLE_ASSERTIONS=ON \
  -DLLVM_ENABLE_RTTI=ON \
  -DCMAKE_C_COMPILER=/usr/bin/clang \
  -DCMAKE_CXX_COMPILER=/usr/bin/clang++
$ cmake --build . -j8
$ cmake --build . --target check-mlir
$ export LLVM_PROJ_BUILD=$PWD

Building generic-tensors

This setup assumes that you have built LLVM and MLIR in $LLVM_PROJ_BUILD. To build and launch the tests, run

$ mkdir build && cd build
$ cmake -G "Unix Makefiles" .. -DMLIR_DIR=$LLVM_PROJ_BUILD/lib/cmake/mlir -DLLVM_EXTERNAL_LIT=$LLVM_PROJ_BUILD/bin/llvm-lit
$ cmake --build . -j8

To build the documentation from the TableGen description of the dialect operations, run

$ cmake --build . --target mlir-doc

Using generic-tensors

Usage
    generic-tensors -dump-tokens <input_file>
    generic-tensors -dump-parsed <input_file>
    generic-tensors -dump-mlir [-clean-up] <input_file>
    generic-tensors -help

Use -dump-tokens to generate a list of tokens scanned from the input file. Use -dump-parsed to pretty print the parsed input file. Use -dump-mlir to get a dump of the MLIR.

Example

There is an example file in the examples folder.

%func Gemm( a: Float32[2*3], b: Float32[3*2], c: Float32[2*2] )
      -> ( y: Float32[2*2] )
{
  
  ( transposeA ) = transpose( a ) [ "perms" : [ 1, 0 ] ]
  ( transposeB ) = transpose( b ) [ "perms" : [ 1, 0 ] ]
  ( matMulTransposeATransposeB ) = matmul( transposeA, transposeB )
  ( matMulMatMulTransposeATransposeBAlpha ) = matmul( matMulTransposeATransposeB, alpha )
  ( matMulCBeta ) = matmul( c, beta )
  ( result ) = add( matMulMatMulTransposeATransposeBAlpha, matMulCBeta )
  ( y ) = identity( result )
  
  %var transposeA: Float32[3*2]
  %var transposeB: Float32[2*3]
  %var alpha: Float32[1] = [
    1
  ]
  %var beta: Float32[1] = [
    1
  ]
  %var matMulTransposeATransposeB: Float32[2*2]
  %var matMulMatMulTransposeATransposeBAlpha: Float32[2*2]
  %var matMulCBeta: Float32[2*2]
  %var result: Float32[2*2]
}

$ ./bin/generic-tensors -help
$ ./bin/generic-tensors -dump-tokens ../examples/Gemm.gen_ten.txt 
$ ./bin/generic-tensors -dump-parsed ../examples/Gemm.gen_ten.txt 
$ ./bin/generic-tensors -dump-mlir ../examples/Gemm.gen_ten.txt 
$ ./bin/generic-tensors -dump-mlir -clean-up ../examples/Gemm.gen_ten.txt