MLIR Lowering

MIND uses MLIR (Multi-Level Intermediate Representation) as its backend infrastructure, enabling powerful optimizations and multi-target code generation.

Lowering Pipeline

MIND IR
    ↓
mind dialect (high-level tensor ops)
    ↓
linalg dialect (loop-based tensor ops)
    ↓
scf dialect (structured control flow)
    ↓
arith + memref dialects
    ↓
llvm dialect
    ↓
LLVM IR → Machine Code

MIND Dialect

The custom MIND dialect represents high-level tensor operations:

// MIND dialect example
%result = mind.matmul %a, %b : tensor<2x3xf32>, tensor<3x4xf32> -> tensor<2x4xf32>
%activated = mind.relu %result : tensor<2x4xf32>
%reduced = mind.sum %activated {axis = 1} : tensor<2x4xf32> -> tensor<2xf32>

Optimization Passes

  • Operator Fusion: Combine sequential ops to reduce memory traffic
  • Layout Optimization: Select optimal memory layouts (row-major, column-major)
  • Tiling: Break large operations into cache-friendly tiles
  • Vectorization: Use SIMD instructions where available
  • Buffer Placement: Optimize memory allocation and reuse

GPU Lowering Path

For GPU targets, additional dialects are used:

mind dialect
    ↓
linalg on tensors
    ↓
linalg on buffers
    ↓
gpu dialect (kernel outline)
    ↓
nvvm dialect (NVIDIA) or spirv dialect (Vulkan/OpenCL)
    ↓
PTX / SPIR-V

Example Transformation

Before fusion:

%0 = mind.relu %input : tensor<1024xf32>
%1 = mind.mul %0, %scale : tensor<1024xf32>
%2 = mind.add %1, %bias : tensor<1024xf32>

After fusion (conceptual example — actual fused operations may vary):

// Hypothetical fused operation for illustration
%0 = mind.fused_relu_scale_bias %input, %scale, %bias : tensor<1024xf32>
// Single memory pass instead of three

Inspecting IR

Use compiler flags to inspect intermediate representations:

# Dump MIND dialect
mindc --emit=mind-dialect model.mind

# Dump linalg dialect
mindc --emit=linalg model.mind

# Dump LLVM IR
mindc --emit=llvm model.mind

# Dump assembly
mindc --emit=asm model.mind

Learn More

See the full MLIR lowering specification at mind-spec/mlir-lowering.md.