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Add f16 linalg-conv2d and linalg-matmul examples #487

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09cf24f
update vocab.
R-Tars Mar 3, 2025
820ca77
update vocab.
R-Tars Mar 3, 2025
8dcc39d
update vocab.
R-Tars Mar 3, 2025
25b4357
Merge branch 'buddy-compiler:main' into DS
R-Tars Mar 16, 2025
4b21bc1
Fix bug in llama example
R-Tars Mar 31, 2025
449c2f2
add f16 linalg-conv2d and linalg-matmul example
R-Tars Apr 7, 2025
339496d
add f16 linalg-conv2d and linalg-matmul example
R-Tars Apr 7, 2025
9f6d3f6
Merge branch 'buddy-compiler:main' into DS
R-Tars Apr 7, 2025
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95 changes: 95 additions & 0 deletions examples/MLIRLinalg/linalg-conv2d-f16.mlir
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Original file line number Diff line number Diff line change
@@ -0,0 +1,95 @@
// RUN: buddy-opt %s \
// RUN: -convert-linalg-to-loops -lower-affine -convert-scf-to-cf \
// RUN: -convert-vector-to-llvm -finalize-memref-to-llvm -convert-arith-to-llvm \
// RUN: -convert-func-to-llvm -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_runner_utils_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext \
// RUN: | FileCheck %s

#map0 = affine_map<(d0, d1) -> (d0 + d1 - 1)>
module {
func.func private @printMemrefF32(memref<*xf32>)

func.func @alloc_2d_filled_f16(%arg0: index, %arg1: index, %arg2: f16) -> memref<?x?xf16> {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%0 = memref.alloc(%arg0, %arg1) : memref<?x?xf16>
scf.for %arg3 = %c0 to %arg0 step %c1 {
scf.for %arg4 = %c0 to %arg1 step %c1 {
memref.store %arg2, %0[%arg3, %arg4] : memref<?x?xf16>
}
}
return %0 : memref<?x?xf16>
}

func.func @conv_2d(%arg0: memref<?x?xf16>, %arg1: memref<?x?xf16>, %arg2: memref<?x?xf16>) {
linalg.conv_2d ins (%arg0, %arg1: memref<?x?xf16>, memref<?x?xf16>)
outs (%arg2: memref<?x?xf16>)
return
}

func.func @main() {
%c2 = arith.constant 2 : index
%c3 = arith.constant 3 : index

// Image and Output value.
%cst = arith.constant 1.000000e+00 : f16
%cst_0 = arith.constant 0.000000e+00 : f16
%cst_2048 = arith.constant 2048.000000e+00 : f16
%cst_2049 = arith.constant 2049.000000e+00 : f16

%current_filter = arith.constant 3 : index
%current_output = arith.constant 8 : index
%current_image = affine.apply #map0(%current_output, %current_filter)

// Filter.
%filter = call @alloc_2d_filled_f16(%current_filter, %current_filter, %cst) : (index, index, f16) -> memref<?x?xf16>
// Image.
%image1 = call @alloc_2d_filled_f16(%current_image, %current_image, %cst_2048) : (index, index, f16) -> memref<?x?xf16>

%image2 = call @alloc_2d_filled_f16(%current_image, %current_image, %cst_2049) : (index, index, f16) -> memref<?x?xf16>
// Output.
%output1 = call @alloc_2d_filled_f16(%current_output, %current_output, %cst_0) : (index, index, f16) -> memref<?x?xf16>

%output2 = call @alloc_2d_filled_f16(%current_output, %current_output, %cst_0) : (index, index, f16) -> memref<?x?xf16>

call @conv_2d(%image1, %filter, %output1) : (memref<?x?xf16>, memref<?x?xf16>, memref<?x?xf16>) -> ()

call @conv_2d(%image2, %filter, %output2) : (memref<?x?xf16>, memref<?x?xf16>, memref<?x?xf16>) -> ()

// Convert f16 output to f32 for printing.
%output_f32_1 = memref.alloc(%current_output, %current_output) : memref<?x?xf32>
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
scf.for %i = %c0 to %current_output step %c1 {
scf.for %j = %c0 to %current_output step %c1 {
%val_f16 = memref.load %output1[%i, %j] : memref<?x?xf16>
%val_f32 = arith.extf %val_f16 : f16 to f32
memref.store %val_f32, %output_f32_1[%i, %j] : memref<?x?xf32>
}
}
%print_output1 = memref.cast %output_f32_1 : memref<?x?xf32> to memref<*xf32>
call @printMemrefF32(%print_output1) : (memref<*xf32>) -> ()

%output_f32_2 = memref.alloc(%current_output, %current_output) : memref<?x?xf32>
scf.for %i = %c0 to %current_output step %c1 {
scf.for %j = %c0 to %current_output step %c1 {
%val_f16 = memref.load %output2[%i, %j] : memref<?x?xf16>
%val_f32 = arith.extf %val_f16 : f16 to f32
memref.store %val_f32, %output_f32_2[%i, %j] : memref<?x?xf32>
}
}
%print_output2 = memref.cast %output_f32_2 : memref<?x?xf32> to memref<*xf32>
call @printMemrefF32(%print_output2) : (memref<*xf32>) -> ()

memref.dealloc %image1 : memref<?x?xf16>
memref.dealloc %image2 : memref<?x?xf16>
memref.dealloc %filter : memref<?x?xf16>
memref.dealloc %output1 : memref<?x?xf16>
memref.dealloc %output2 : memref<?x?xf16>
memref.dealloc %output_f32_1 : memref<?x?xf32>
memref.dealloc %output_f32_2 : memref<?x?xf32>
return
}
}
91 changes: 91 additions & 0 deletions examples/MLIRLinalg/linalg-matmul-f16.mlir
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Original file line number Diff line number Diff line change
@@ -0,0 +1,91 @@
// RUN: buddy-opt %s \
// RUN: -convert-linalg-to-loops -lower-affine -convert-scf-to-cf \
// RUN: -convert-vector-to-llvm -finalize-memref-to-llvm -convert-arith-to-llvm \
// RUN: -convert-func-to-llvm -reconcile-unrealized-casts \
// RUN: | mlir-cpu-runner -e main -entry-point-result=void \
// RUN: -shared-libs=%mlir_runner_utils_dir/libmlir_runner_utils%shlibext \
// RUN: -shared-libs=%mlir_runner_utils_dir/libmlir_c_runner_utils%shlibext \
// RUN: | FileCheck %s

module {
func.func private @printMemrefF32(memref<*xf32>)

func.func @alloc_2d_filled_f16(%arg0: index, %arg1: index, %arg2: f16) -> memref<?x?xf16> {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%0 = memref.alloc(%arg0, %arg1) : memref<?x?xf16>
scf.for %arg3 = %c0 to %arg0 step %c1 {
scf.for %arg4 = %c0 to %arg1 step %c1 {
memref.store %arg2, %0[%arg3, %arg4] : memref<?x?xf16>
}
}
return %0 : memref<?x?xf16>
}

func.func @matmul(%a : memref<?x?xf16>, %b : memref<?x?xf16>, %c : memref<?x?xf16>) {
linalg.matmul
ins(%a, %b: memref<?x?xf16>, memref<?x?xf16>)
outs(%c: memref<?x?xf16>)
return
}

func.func @main() {
// Set up dims.
%cM = arith.constant 2 : index
%cN = arith.constant 2 : index
%cK = arith.constant 2 : index

// Set Init Value.
%cf2048 = arith.constant 2048.000000e+00 : f16
%cf2049 = arith.constant 2049.000000e+00 : f16
%cf0 = arith.constant 0.000000e+00 : f16
%cf2 = arith.constant 2.000000e+00 : f16

// Allocate and initialize matrices
%A1 = call @alloc_2d_filled_f16(%cM, %cK, %cf2048) : (index, index, f16) -> memref<?x?xf16>
%A2 = call @alloc_2d_filled_f16(%cM, %cK, %cf2049) : (index, index, f16) -> memref<?x?xf16>
%B = call @alloc_2d_filled_f16(%cK, %cN, %cf2) : (index, index, f16) -> memref<?x?xf16>
%C1 = call @alloc_2d_filled_f16(%cM, %cN, %cf0) : (index, index, f16) -> memref<?x?xf16>
%C2 = call @alloc_2d_filled_f16(%cM, %cN, %cf0) : (index, index, f16) -> memref<?x?xf16>

call @matmul(%A1, %B, %C1) : (memref<?x?xf16>, memref<?x?xf16>, memref<?x?xf16>) -> ()
call @matmul(%A2, %B, %C2) : (memref<?x?xf16>, memref<?x?xf16>, memref<?x?xf16>) -> ()

// Convert f16 output to f32 for printing
%C1_f32 = memref.alloc(%cM, %cN) : memref<?x?xf32>
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
scf.for %i = %c0 to %cM step %c1 {
scf.for %j = %c0 to %cN step %c1 {
%val_f16 = memref.load %C1[%i, %j] : memref<?x?xf16>
%val_f32 = arith.extf %val_f16 : f16 to f32
memref.store %val_f32, %C1_f32[%i, %j] : memref<?x?xf32>
}
}

%C2_f32 = memref.alloc(%cM, %cN) : memref<?x?xf32>
scf.for %i = %c0 to %cM step %c1 {
scf.for %j = %c0 to %cN step %c1 {
%val_f16 = memref.load %C2[%i, %j] : memref<?x?xf16>
%val_f32 = arith.extf %val_f16 : f16 to f32
memref.store %val_f32, %C2_f32[%i, %j] : memref<?x?xf32>
}
}

// Print output.
%print_C1 = memref.cast %C1_f32 : memref<?x?xf32> to memref<*xf32>
%print_C2 = memref.cast %C2_f32 : memref<?x?xf32> to memref<*xf32>
call @printMemrefF32(%print_C1) : (memref<*xf32>) -> ()
call @printMemrefF32(%print_C2) : (memref<*xf32>) -> ()

// Deallocations
memref.dealloc %A1 : memref<?x?xf16>
memref.dealloc %A2 : memref<?x?xf16>
memref.dealloc %B : memref<?x?xf16>
memref.dealloc %C1 : memref<?x?xf16>
memref.dealloc %C2 : memref<?x?xf16>
memref.dealloc %C1_f32 : memref<?x?xf32>
memref.dealloc %C2_f32 : memref<?x?xf32>
return
}
}
16 changes: 15 additions & 1 deletion examples/MLIRLinalg/makefile
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Original file line number Diff line number Diff line change
Expand Up @@ -39,6 +39,13 @@ linalg-conv2d-run:
-convert-func-to-llvm -reconcile-unrealized-casts | \
${MLIR_CPU_RUNNER} ${OPT_FLAG} -e main -entry-point-result=void -shared-libs=${MLIR_RUNNER_UTILS} -shared-libs=${MLIR_C_RUNNER_UTILS}

linalg-conv2d-f16-run:
@${MLIR_OPT} linalg-conv2d-f16.mlir ${MLIR_OPT_OPTIONS} \
-convert-linalg-to-loops -lower-affine -convert-scf-to-cf \
-convert-vector-to-llvm -finalize-memref-to-llvm -convert-arith-to-llvm \
-convert-func-to-llvm -reconcile-unrealized-casts | \
${MLIR_CPU_RUNNER} ${OPT_FLAG} -e main -entry-point-result=void -shared-libs=${MLIR_RUNNER_UTILS} -shared-libs=${MLIR_C_RUNNER_UTILS}

linalg-conv2d-tiling-lower:
@${MLIR_OPT} ./linalg-conv2d.mlir \
-test-transform-dialect-interpreter \
Expand Down Expand Up @@ -73,7 +80,7 @@ linalg-conv2d_nhwc_fhwc-optimize-run:
-convert-func-to-llvm -reconcile-unrealized-casts | \
${MLIR_CPU_RUNNER} ${OPT_FLAG} -e main -entry-point-result=void -shared-libs=${MLIR_RUNNER_UTILS} -shared-libs=${MLIR_C_RUNNER_UTILS}


linalg-conv2d_nhwc_fhwc-tile-optimize-lower:
@${BUDDY_OPT} linalg-conv2d_nhwc_fhwc.mlir \
-conv-nhwc-fhwc-tile-optimize="vec-size=16 tiling-height=2 tiling-width=3" \
Expand Down Expand Up @@ -142,6 +149,13 @@ linalg-matmul-run:
-convert-func-to-llvm -reconcile-unrealized-casts | \
${MLIR_CPU_RUNNER} ${OPT_FLAG} -e main -entry-point-result=void -shared-libs=${MLIR_RUNNER_UTILS} -shared-libs=${MLIR_C_RUNNER_UTILS}

linalg-matmul-f16-run:
@${MLIR_OPT} linalg-matmul-f16.mlir ${MLIR_OPT_OPTIONS} \
-convert-linalg-to-loops -lower-affine -convert-scf-to-cf \
-convert-vector-to-llvm -finalize-memref-to-llvm -convert-arith-to-llvm \
-convert-func-to-llvm -reconcile-unrealized-casts | \
${MLIR_CPU_RUNNER} ${OPT_FLAG} -e main -entry-point-result=void -shared-libs=${MLIR_RUNNER_UTILS} -shared-libs=${MLIR_C_RUNNER_UTILS}

linalg-matmul-optimize-lower:
@${BUDDY_OPT} linalg-matmul.mlir ${MLIR_OPT_OPTIONS} \
--matmul-optimize="vec-size=16 kernel-m=2 kernel-n=4" \
Expand Down
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