[Mlir-commits] [mlir] [mlir][sparse][gpu] add GPU BSR SDDMM check test (PR #71491)

llvmlistbot at llvm.org llvmlistbot at llvm.org
Mon Nov 6 22:26:00 PST 2023


llvmbot wrote:


<!--LLVM PR SUMMARY COMMENT-->

@llvm/pr-subscribers-mlir

Author: Aart Bik (aartbik)

<details>
<summary>Changes</summary>

also minor edits in other GPU check tests

---
Full diff: https://github.com/llvm/llvm-project/pull/71491.diff


6 Files Affected:

- (modified) mlir/test/Dialect/SparseTensor/GPU/gpu_matmul.mlir (+9-9) 
- (modified) mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib_2to4.mlir (+6-6) 
- (modified) mlir/test/Dialect/SparseTensor/GPU/gpu_matvec.mlir (+6-6) 
- (modified) mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir (+5-5) 
- (added) mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir (+108) 
- (modified) mlir/test/Dialect/SparseTensor/GPU/gpu_spgemm_lib.mlir (+3-3) 


``````````diff
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul.mlir
index 84265398d60cd87..8dc6afa320af7d5 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul.mlir
@@ -10,15 +10,15 @@
 //
 // CHECK-LABEL: gpu.module @sparse_kernels
 // CHECK-LABEL: gpu.func @kernel0(
-// CHECK-SAME:        %[[VAL_0:.*0]]: index,
-// CHECK-SAME:        %[[VAL_1:.*1]]: index,
-// CHECK-SAME:        %[[VAL_2:.*2]]: memref<?xindex>,
-// CHECK-SAME:        %[[VAL_3:.*3]]: memref<?xindex>,
-// CHECK-SAME:        %[[VAL_4:.*4]]: memref<?xf64>,
-// CHECK-SAME:        %[[VAL_5:.*5]]: memref<?x?xf64>,
-// CHECK-SAME:        %[[VAL_6:.*6]]: memref<?x?xf64>) kernel {
-// CHECK:         %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK:         %[[VAL_8:.*]] = arith.constant 0 : index
+// CHECK-SAME:    %[[VAL_0:.*0]]: index,
+// CHECK-SAME:    %[[VAL_1:.*1]]: index,
+// CHECK-SAME:    %[[VAL_2:.*2]]: memref<?xindex>,
+// CHECK-SAME:    %[[VAL_3:.*3]]: memref<?xindex>,
+// CHECK-SAME:    %[[VAL_4:.*4]]: memref<?xf64>,
+// CHECK-SAME:    %[[VAL_5:.*5]]: memref<?x?xf64>,
+// CHECK-SAME:    %[[VAL_6:.*6]]: memref<?x?xf64>) kernel {
+// CHECK-DAG:     %[[VAL_7:.*]] = arith.constant 1 : index
+// CHECK-DAG:     %[[VAL_8:.*]] = arith.constant 0 : index
 // CHECK:         %[[VAL_9:.*]] = gpu.block_id  x
 // CHECK:         %[[VAL_10:.*]] = gpu.block_dim  x
 // CHECK:         %[[VAL_11:.*]] = gpu.thread_id  x
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib_2to4.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib_2to4.mlir
index 0769e217782c6c2..9973050d40799d4 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib_2to4.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib_2to4.mlir
@@ -2,11 +2,11 @@
 // RUN:             --sparsification="enable-gpu-libgen" | FileCheck %s
 
 // CHECK-LABEL:   func.func @matmul(
-// CHECK-SAME:                      %[[VAL_0:.*0]]: tensor<?x?xf16>,
-// CHECK-SAME:                      %[[VAL_1:.*1]]: tensor<?x?xf16>,
-// CHECK-SAME:                      %[[VAL_2:.*2]]: tensor<?x?xf16>) -> tensor<?x?xf16> {
-// CHECK:           %[[VAL_3:.*]] = arith.constant 0 : index
-// CHECK:           %[[VAL_4:.*]] = arith.constant 1 : index
+// CHECK-SAME:      %[[VAL_0:.*0]]: tensor<?x?xf16>,
+// CHECK-SAME:      %[[VAL_1:.*1]]: tensor<?x?xf16>,
+// CHECK-SAME:      %[[VAL_2:.*2]]: tensor<?x?xf16>) -> tensor<?x?xf16> {
+// CHECK-DAG:       %[[VAL_3:.*]] = arith.constant 0 : index
+// CHECK-DAG:       %[[VAL_4:.*]] = arith.constant 1 : index
 // CHECK:           %[[VAL_5:.*]] = bufferization.to_memref %[[VAL_0]] : memref<?x?xf16>
 // CHECK:           %[[VAL_6:.*]] = gpu.wait async
 // CHECK:           %[[VAL_7:.*]] = memref.dim %[[VAL_5]], %[[VAL_3]] : memref<?x?xf16>
@@ -66,4 +66,4 @@ module {
     } -> tensor<?x?xf16>
     return %0 : tensor<?x?xf16>
   }
-}
\ No newline at end of file
+}
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec.mlir
index b56f3a90aa27c34..ab267062e41693a 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec.mlir
@@ -10,12 +10,12 @@
 //
 // CHECK-LABEL: gpu.module @sparse_kernels
 // CHECK:       gpu.func @kernel0(
-// CHECK-SAME:          %[[VAL_0:.*0]]: index,
-// CHECK-SAME:          %[[VAL_1:.*1]]: memref<?xf64>,
-// CHECK-SAME:          %[[VAL_2:.*2]]: memref<?xindex>,
-// CHECK-SAME:          %[[VAL_3:.*3]]: memref<?xindex>,
-// CHECK-SAME:          %[[VAL_4:.*4]]: memref<?xf64>,
-// CHECK-SAME:          %[[VAL_5:.*5]]: memref<?xf64>) kernel {
+// CHECK-SAME:    %[[VAL_0:.*0]]: index,
+// CHECK-SAME:    %[[VAL_1:.*1]]: memref<?xf64>,
+// CHECK-SAME:    %[[VAL_2:.*2]]: memref<?xindex>,
+// CHECK-SAME:    %[[VAL_3:.*3]]: memref<?xindex>,
+// CHECK-SAME:    %[[VAL_4:.*4]]: memref<?xf64>,
+// CHECK-SAME:    %[[VAL_5:.*5]]: memref<?xf64>) kernel {
 // CHECK:         %[[VAL_6:.*]] = arith.constant 1 : index
 // CHECK:         %[[VAL_7:.*]] = gpu.block_id  x
 // CHECK:         %[[VAL_8:.*]] = gpu.block_dim  x
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir
index 4d925abe47fdcaf..221bda47291ebf9 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir
@@ -22,11 +22,11 @@
 #CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
 
 // CHECK-LABEL:   func.func @sparse_sampled_dd(
-// CHECK-SAME:                                 %[[VAL_0:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>,
-// CHECK-SAME:                                 %[[VAL_1:.*]]: tensor<8x8xf64>,
-// CHECK-SAME:                                 %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> {
-// CHECK:           %[[VAL_3:.*]] = arith.constant 8 : index
-// CHECK:           %[[VAL_4:.*]] = arith.constant 0 : index
+// CHECK-SAME:      %[[VAL_0:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME:      %[[VAL_1:.*]]: tensor<8x8xf64>,
+// CHECK-SAME:      %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-DAG:       %[[VAL_3:.*]] = arith.constant 8 : index
+// CHECK-DAG:       %[[VAL_4:.*]] = arith.constant 0 : index
 // CHECK:           %[[VAL_5:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
 // CHECK:           %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_1]] : memref<8x8xf64>
 // CHECK:           %[[VAL_7:.*]] = gpu.wait async
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir
new file mode 100644
index 000000000000000..6afb626625cfe2d
--- /dev/null
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir
@@ -0,0 +1,108 @@
+// RUN: mlir-opt %s --sparsification="enable-gpu-libgen" | FileCheck %s
+
+#BSR = #sparse_tensor.encoding<{
+  map = (i, j) -> (
+    i floordiv 2 : dense,
+    j floordiv 2 : compressed,
+    i mod 2 : dense,
+    j mod 2 : dense)
+}>
+
+#trait_SDDMM = {
+  indexing_maps = [
+    affine_map<(i,j,k) -> (i,k)>,  // A
+    affine_map<(i,j,k) -> (k,j)>,  // B
+    affine_map<(i,j,k) -> (i,j)>   // S (in/out)
+  ],
+  iterator_types = ["parallel", "parallel", "reduction"],
+  doc = "S(i,j) += spy[S(i,j)] x SUM_k A(i,k) B(k,j)"
+}
+
+// CHECK-LABEL:   func.func @SDDMM_block(
+// CHECK-SAME:      %[[VAL_0:.*]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME:      %[[VAL_1:.*]]: tensor<?x?xf32>,
+// CHECK-SAME:      %[[VAL_2:.*]]: tensor<?x?xf32>) -> tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-DAG:       %[[VAL_3:.*]] = arith.constant 0 : index
+// CHECK-DAG:       %[[VAL_4:.*]] = arith.constant 1 : index
+// CHECK-DAG:       %[[VAL_5:.*]] = arith.constant 2 : index
+// CHECK-DAG:       %[[VAL_6:.*]] = arith.constant 4 : index
+// CHECK:           %[[VAL_7:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK:           %[[VAL_8:.*]] = tensor.dim %[[VAL_1]], %[[VAL_3]] : tensor<?x?xf32>
+// CHECK:           %[[VAL_9:.*]] = tensor.dim %[[VAL_1]], %[[VAL_4]] : tensor<?x?xf32>
+// CHECK:           %[[VAL_10:.*]] = tensor.dim %[[VAL_2]], %[[VAL_4]] : tensor<?x?xf32>
+// CHECK:           %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<?x?xf32>
+// CHECK:           %[[VAL_12:.*]] = gpu.wait async
+// CHECK:           %[[VAL_13:.*]] = memref.dim %[[VAL_11]], %[[VAL_3]] : memref<?x?xf32>
+// CHECK:           %[[VAL_14:.*]] = memref.dim %[[VAL_11]], %[[VAL_4]] : memref<?x?xf32>
+// CHECK:           %[[VAL_15:.*]], %[[VAL_16:.*]] = gpu.alloc async {{\[}}%[[VAL_12]]] (%[[VAL_13]], %[[VAL_14]]) : memref<?x?xf32>
+// CHECK:           %[[VAL_17:.*]] = gpu.memcpy async {{\[}}%[[VAL_16]]] %[[VAL_15]], %[[VAL_11]] : memref<?x?xf32>, memref<?x?xf32>
+// CHECK:           %[[VAL_18:.*]] = bufferization.to_memref %[[VAL_2]] : memref<?x?xf32>
+// CHECK:           %[[VAL_19:.*]] = gpu.wait async
+// CHECK:           %[[VAL_20:.*]] = memref.dim %[[VAL_18]], %[[VAL_3]] : memref<?x?xf32>
+// CHECK:           %[[VAL_21:.*]] = memref.dim %[[VAL_18]], %[[VAL_4]] : memref<?x?xf32>
+// CHECK:           %[[VAL_22:.*]], %[[VAL_23:.*]] = gpu.alloc async {{\[}}%[[VAL_19]]] (%[[VAL_20]], %[[VAL_21]]) : memref<?x?xf32>
+// CHECK:           %[[VAL_24:.*]] = gpu.memcpy async {{\[}}%[[VAL_23]]] %[[VAL_22]], %[[VAL_18]] : memref<?x?xf32>, memref<?x?xf32>
+// CHECK:           %[[VAL_25:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index}
+// CHECK:           %[[VAL_26:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index}
+// CHECK:           %[[VAL_27:.*]] = sparse_tensor.values %[[VAL_0]]
+// CHECK:           %[[VAL_28:.*]] = gpu.wait async
+// CHECK:           %[[VAL_29:.*]] = memref.dim %[[VAL_25]], %[[VAL_3]] : memref<?xindex>
+// CHECK:           %[[VAL_30:.*]], %[[VAL_31:.*]] = gpu.alloc async {{\[}}%[[VAL_28]]] (%[[VAL_29]]) : memref<?xindex>
+// CHECK:           %[[VAL_32:.*]] = gpu.memcpy async {{\[}}%[[VAL_31]]] %[[VAL_30]], %[[VAL_25]] : memref<?xindex>, memref<?xindex>
+// CHECK:           %[[VAL_33:.*]] = gpu.wait async
+// CHECK:           %[[VAL_34:.*]] = memref.dim %[[VAL_26]], %[[VAL_3]] : memref<?xindex>
+// CHECK:           %[[VAL_35:.*]], %[[VAL_36:.*]] = gpu.alloc async {{\[}}%[[VAL_33]]] (%[[VAL_34]]) : memref<?xindex>
+// CHECK:           %[[VAL_37:.*]] = gpu.memcpy async {{\[}}%[[VAL_36]]] %[[VAL_35]], %[[VAL_26]] : memref<?xindex>, memref<?xindex>
+// CHECK:           %[[VAL_38:.*]] = gpu.wait async
+// CHECK:           %[[VAL_39:.*]] = memref.dim %[[VAL_27]], %[[VAL_3]] : memref<?xf32>
+// CHECK:           %[[VAL_40:.*]], %[[VAL_41:.*]] = gpu.alloc async {{\[}}%[[VAL_38]]] (%[[VAL_39]]) : memref<?xf32>
+// CHECK:           %[[VAL_42:.*]] = gpu.memcpy async {{\[}}%[[VAL_41]]] %[[VAL_40]], %[[VAL_27]] : memref<?xf32>, memref<?xf32>
+// CHECK:           gpu.wait {{\[}}%[[VAL_17]], %[[VAL_24]], %[[VAL_32]], %[[VAL_37]], %[[VAL_42]]]
+// CHECK:           %[[VAL_43:.*]] = gpu.wait async
+// CHECK:           %[[VAL_44:.*]], %[[VAL_45:.*]] = gpu.create_dn_tensor async {{\[}}%[[VAL_43]]] %[[VAL_15]], %[[VAL_8]], %[[VAL_9]] : index, index into memref<?x?xf32>
+// CHECK:           %[[VAL_46:.*]], %[[VAL_47:.*]] = gpu.create_dn_tensor async {{\[}}%[[VAL_45]]] %[[VAL_22]], %[[VAL_9]], %[[VAL_10]] : index, index into memref<?x?xf32>
+// CHECK:           %[[VAL_48:.*]] = arith.divui %[[VAL_8]], %[[VAL_5]] : index
+// CHECK:           %[[VAL_49:.*]] = arith.divui %[[VAL_10]], %[[VAL_5]] : index
+// CHECK:           %[[VAL_50:.*]] = arith.divui %[[VAL_7]], %[[VAL_6]] : index
+// CHECK:           %[[VAL_51:.*]], %[[VAL_52:.*]] = gpu.create_bsr async {{\[}}%[[VAL_47]]] %[[VAL_48]], %[[VAL_49]], %[[VAL_50]], %[[VAL_5]], %[[VAL_5]], %[[VAL_30]], %[[VAL_35]], %[[VAL_40]] : memref<?xindex>, memref<?xindex>, memref<?xf32>
+// CHECK:           %[[VAL_53:.*]], %[[VAL_54:.*]] = gpu.sddmm_buffer_size async {{\[}}%[[VAL_52]]] %[[VAL_44]], %[[VAL_46]], %[[VAL_51]] into f32
+// CHECK:           %[[VAL_55:.*]], %[[VAL_56:.*]] = gpu.alloc async {{\[}}%[[VAL_54]]] (%[[VAL_53]]) : memref<?xi8>
+// CHECK:           %[[VAL_57:.*]] = gpu.sddmm async {{\[}}%[[VAL_56]]] %[[VAL_44]], %[[VAL_46]], %[[VAL_51]], %[[VAL_55]] : memref<?xi8> into f32
+// CHECK:           %[[VAL_58:.*]] = gpu.destroy_dn_tensor async {{\[}}%[[VAL_57]]] %[[VAL_44]]
+// CHECK:           %[[VAL_59:.*]] = gpu.destroy_dn_tensor async {{\[}}%[[VAL_58]]] %[[VAL_46]]
+// CHECK:           %[[VAL_60:.*]] = gpu.destroy_sp_mat async {{\[}}%[[VAL_59]]] %[[VAL_51]]
+// CHECK:           %[[VAL_61:.*]] = gpu.dealloc async {{\[}}%[[VAL_60]]] %[[VAL_55]] : memref<?xi8>
+// CHECK:           %[[VAL_62:.*]] = gpu.dealloc async {{\[}}%[[VAL_61]]] %[[VAL_15]] : memref<?x?xf32>
+// CHECK:           %[[VAL_63:.*]] = gpu.dealloc async {{\[}}%[[VAL_62]]] %[[VAL_22]] : memref<?x?xf32>
+// CHECK:           %[[VAL_64:.*]] = gpu.dealloc async {{\[}}%[[VAL_63]]] %[[VAL_30]] : memref<?xindex>
+// CHECK:           %[[VAL_65:.*]] = gpu.dealloc async {{\[}}%[[VAL_64]]] %[[VAL_35]] : memref<?xindex>
+// CHECK:           %[[VAL_66:.*]] = gpu.memcpy async {{\[}}%[[VAL_65]]] %[[VAL_27]], %[[VAL_40]] : memref<?xf32>, memref<?xf32>
+// CHECK:           %[[VAL_67:.*]] = gpu.dealloc async {{\[}}%[[VAL_66]]] %[[VAL_40]] : memref<?xf32>
+// CHECK:           gpu.wait {{\[}}%[[VAL_67]]]
+// CHECK:           %[[VAL_68:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK:           return %[[VAL_68]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK:         }
+func.func @SDDMM_block(%args: tensor<?x?xf32, #BSR>,
+                       %arga: tensor<?x?xf32>,
+                       %argb: tensor<?x?xf32>) -> tensor<?x?xf32, #BSR> {
+  %result = linalg.generic #trait_SDDMM
+      ins(%arga, %argb: tensor<?x?xf32>, tensor<?x?xf32>)
+      outs(%args: tensor<?x?xf32, #BSR>) {
+        ^bb(%a: f32, %b: f32, %s: f32):
+           %f0 = arith.constant 0.0 : f32
+           %u = sparse_tensor.unary %s : f32 to f32
+             present={
+                ^bb0(%p: f32):
+                  %mul = arith.mulf %a, %b : f32
+                  sparse_tensor.yield %mul : f32
+             }
+             absent={}
+           %r = sparse_tensor.reduce %s, %u, %f0 : f32 {
+              ^bb0(%p: f32, %q: f32):
+                %add = arith.addf %p, %q : f32
+                sparse_tensor.yield %add : f32
+            }
+           linalg.yield %r : f32
+      } -> tensor<?x?xf32, #BSR>
+  return %result : tensor<?x?xf32, #BSR>
+}
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_spgemm_lib.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_spgemm_lib.mlir
index a5d4ee2b55f546e..027c9fda5da90eb 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_spgemm_lib.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_spgemm_lib.mlir
@@ -6,9 +6,9 @@
 // CHECK-LABEL: func.func @matmulCSR(
 // CHECK-SAME:      %[[VAL_0:.*0]]: tensor<8x8xf32, #{{.*}}>,
 // CHECK-SAME:      %[[VAL_1:.*1]]: tensor<8x8xf32, #{{.*}}>) -> tensor<8x8xf32, #{{.*}}> {
-// CHECK:           %[[VAL_2:.*]] = arith.constant 8 : index
-// CHECK:           %[[VAL_3:.*]] = arith.constant 0 : index
-// CHECK:           %[[VAL_4:.*]] = arith.constant 9 : index
+// CHECK-DAG:       %[[VAL_2:.*]] = arith.constant 8 : index
+// CHECK-DAG:       %[[VAL_3:.*]] = arith.constant 0 : index
+// CHECK-DAG:       %[[VAL_4:.*]] = arith.constant 9 : index
 // CHECK:           %[[VAL_6:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<8x8xf32, #{{.*}}>
 // CHECK:           %[[VAL_7:.*]] = sparse_tensor.number_of_entries %[[VAL_1]] : tensor<8x8xf32, #{{.*}}>
 // CHECK:           %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf32, #{{.*}}>

``````````

</details>


https://github.com/llvm/llvm-project/pull/71491


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