further reduction

Signed-off-by: Anatoly Myachev <[email protected]>

Author: anmyachev

python/test/unit/intel/test_regressions.py

@@ -61,12 +61,11 @@ def test_kernel_from_09_tutorial(device, tmp_path: pathlib.Path):
 #blocked = #ttg.blocked<{sizePerThread = [4, 4], threadsPerWarp = [1, 32], warpsPerCTA = [4, 1], order = [1, 0]}>
 #blocked1 = #ttg.blocked<{sizePerThread = [8, 1], threadsPerWarp = [8, 4], warpsPerCTA = [1, 4], order = [0, 1]}>
 #blocked2 = #ttg.blocked<{sizePerThread = [1, 8], threadsPerWarp = [4, 8], warpsPerCTA = [4, 1], order = [1, 0]}>
-#blocked3 = #ttg.blocked<{sizePerThread = [1, 8], threadsPerWarp = [2, 16], warpsPerCTA = [4, 1], order = [1, 0]}>
 #shared = #ttg.swizzled_shared<{vec = 1, perPhase = 1, maxPhase = 1, order = [1, 0]}>
 #shared1 = #ttg.swizzled_shared<{vec = 1, perPhase = 1, maxPhase = 1, order = [0, 1]}>
 #smem = #ttg.shared_memory
 module attributes {"ttg.num-ctas" = 1 : i32, "ttg.num-warps" = 4 : i32, ttg.target = "xpu", "ttg.threads-per-warp" = 32 : i32, ttig.min_sg_size = 8 : i32, ttig.support_bf16_conversion, ttig.support_dpas, ttig.target_arch = "spir64"} {
-  tt.func public @matmul_kernel(%arg0: !tt.ptr<f32> {tt.divisibility = 16 : i32}, %arg1: !tt.ptr<f32> {tt.divisibility = 16 : i32}, %arg2: !tt.ptr<f32> {tt.divisibility = 16 : i32}, %arg3: i32 {tt.divisibility = 16 : i32}, %arg4: i32 {tt.divisibility = 16 : i32}, %arg5: i32 {tt.divisibility = 16 : i32}, %arg6: i32 {tt.divisibility = 16 : i32}, %arg7: i32 {tt.divisibility = 16 : i32}, %arg8: i32 {tt.divisibility = 16 : i32} ) attributes {noinline = false} {
+  tt.func public @matmul_kernel(%arg0: !tt.ptr<f32> {tt.divisibility = 16 : i32}, %arg3: i32 {tt.divisibility = 16 : i32}, %arg5: i32 {tt.divisibility = 16 : i32}) attributes {noinline = false} {
     %cst = arith.constant dense<0.000000e+00> : tensor<128x128xf32, #blocked>
     %c63_i32 = arith.constant 63 : i32
     %c127_i32 = arith.constant 127 : i32
@@ -79,82 +78,54 @@ def test_kernel_from_09_tutorial(device, tmp_path: pathlib.Path):
     %c128_i32 = arith.constant 128 : i32
     %cst_2 = arith.constant dense<0> : tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
     %cst_3 = arith.constant dense<0> : tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>>
-    %cst_4 = arith.constant dense<64> : tensor<128x64xi32, #blocked2>
-    %cst_5 = arith.constant dense<64> : tensor<64x128xi32, #blocked1>
     %0 = tt.get_program_id x : i32
     %1 = arith.addi %arg3, %c127_i32 : i32
     %2 = arith.divsi %1, %c128_i32 : i32
-    %3 = arith.addi %arg4, %c127_i32 : i32
-    %4 = arith.divsi %3, %c128_i32 : i32
-    %5 = arith.muli %4, %c8_i32 : i32
+    %5 = arith.muli %2, %c8_i32 : i32
     %6 = arith.divsi %0, %5 : i32
     %7 = arith.muli %6, %c8_i32 : i32
     %8 = arith.subi %2, %7 : i32
     %9 = arith.minsi %8, %c8_i32 : i32
-    %10 = arith.remsi %0, %9 : i32
-    %11 = arith.addi %7, %10 : i32
     %12 = arith.remsi %0, %5 : i32
     %13 = arith.divsi %12, %9 : i32
-    %14 = arith.muli %11, %c128_i32 : i32
     %15 = arith.muli %13, %c128_i32 : i32
-    %16 = tt.make_range {end = 128 : i32, start = 0 : i32} : tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
     %18 = tt.make_range {end = 128 : i32, start = 0 : i32} : tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>>
-    %20 = tt.splat %14 : i32 -> tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
-    %22 = arith.addi %20, %16 : tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
+    %20 = tt.splat %c128_i32 : i32 -> tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
     %24 = tt.splat %15 : i32 -> tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>>
     %26 = arith.addi %24, %18 : tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>>
     %28 = tt.splat %arg3 : i32 -> tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
-    %29 = arith.cmpi slt, %22, %28 : tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
-    %30 = arith.select %29, %22, %cst_2 {tt.contiguity = dense<128> : tensor<1xi32>, tt.divisibility = dense<128> : tensor<1xi32>} : tensor<128xi1, #ttg.slice<{dim = 1, parent = #blocked2}>>, tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
-    %31 = tt.splat %arg4 : i32 -> tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>>
+    %29 = arith.cmpi slt, %20, %28 : tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>>
+    %31 = tt.splat %arg3 : i32 -> tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>>
     %32 = arith.cmpi slt, %26, %31 : tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>>
     %33 = arith.select %32, %26, %cst_3 {tt.contiguity = dense<128> : tensor<1xi32>, tt.divisibility = dense<128> : tensor<1xi32>} : tensor<128xi1, #ttg.slice<{dim = 0, parent = #blocked1}>>, tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>>
-    %34 = tt.expand_dims %30 {axis = 1 : i32} : tensor<128xi32, #ttg.slice<{dim = 1, parent = #blocked2}>> -> tensor<128x1xi32, #blocked2>
-    %35 = tt.splat %arg6 : i32 -> tensor<128x1xi32, #blocked2>
-    %36 = arith.muli %34, %35 : tensor<128x1xi32, #blocked2>
     %37 = tt.make_range {end = 64 : i32, start = 0 : i32} : tensor<64xi32, #ttg.slice<{dim = 0, parent = #blocked2}>>
     %38 = tt.expand_dims %37 {axis = 0 : i32} : tensor<64xi32, #ttg.slice<{dim = 0, parent = #blocked2}>> -> tensor<1x64xi32, #blocked2>
-    %39 = tt.broadcast %36 : tensor<128x1xi32, #blocked2> -> tensor<128x64xi32, #blocked2>
-    %40 = tt.broadcast %38 : tensor<1x64xi32, #blocked2> -> tensor<128x64xi32, #blocked2>
-    %41 = arith.addi %39, %40 : tensor<128x64xi32, #blocked2>
     %42 = tt.splat %arg0 : !tt.ptr<f32> -> tensor<128x64x!tt.ptr<f32>, #blocked2>
-    %43 = tt.addptr %42, %41 : tensor<128x64x!tt.ptr<f32>, #blocked2>, tensor<128x64xi32, #blocked2>
     %44 = tt.make_range {end = 64 : i32, start = 0 : i32} : tensor<64xi32, #ttg.slice<{dim = 1, parent = #blocked1}>>
     %45 = tt.expand_dims %44 {axis = 1 : i32} : tensor<64xi32, #ttg.slice<{dim = 1, parent = #blocked1}>> -> tensor<64x1xi32, #blocked1>
     %46 = tt.expand_dims %33 {axis = 0 : i32} : tensor<128xi32, #ttg.slice<{dim = 0, parent = #blocked1}>> -> tensor<1x128xi32, #blocked1>
-    %47 = tt.splat %arg7 : i32 -> tensor<1x128xi32, #blocked1>
-    %48 = arith.muli %46, %47 : tensor<1x128xi32, #blocked1>
-    %49 = tt.broadcast %45 : tensor<64x1xi32, #blocked1> -> tensor<64x128xi32, #blocked1>
-    %50 = tt.broadcast %48 : tensor<1x128xi32, #blocked1> -> tensor<64x128xi32, #blocked1>
-    %51 = arith.addi %49, %50 : tensor<64x128xi32, #blocked1>
-    %52 = tt.splat %arg1 : !tt.ptr<f32> -> tensor<64x128x!tt.ptr<f32>, #blocked1>
-    %53 = tt.addptr %52, %51 : tensor<64x128x!tt.ptr<f32>, #blocked1>, tensor<64x128xi32, #blocked1>
-    %54 = arith.addi %arg5, %c63_i32 : i32
-    %55 = arith.divsi %54, %c64_i32 : i32
-    %56 = arith.remsi %arg5, %c64_i32 : i32
-    %57 = arith.cmpi eq, %56, %c0_i32 : i32
-    %58 = arith.cmpi sgt, %arg5, %c64_i32 : i32
-    %59 = arith.andi %57, %58 : i1
+    %50 = tt.broadcast %46 : tensor<1x128xi32, #blocked1> -> tensor<64x128xi32, #blocked1>
+    %52 = tt.splat %arg0 : !tt.ptr<f32> -> tensor<64x128x!tt.ptr<f32>, #blocked1>
+    %53 = tt.addptr %52, %50 : tensor<64x128x!tt.ptr<f32>, #blocked1>, tensor<64x128xi32, #blocked1>
 
     %80 = arith.muli %c0_i32, %c64_i32 : i32
     %81 = arith.subi %arg5, %80 : i32
     %82 = tt.splat %81 : i32 -> tensor<1x64xi32, #blocked2>
     %83 = arith.cmpi slt, %38, %82 : tensor<1x64xi32, #blocked2>
     %84 = tt.broadcast %83 : tensor<1x64xi1, #blocked2> -> tensor<128x64xi1, #blocked2>
-    %85 = tt.load %43, %84, %cst_1 : tensor<128x64x!tt.ptr<f32>, #blocked2>
+    %85 = tt.load %42, %84, %cst_1 : tensor<128x64x!tt.ptr<f32>, #blocked2>
     %86 = tt.splat %81 : i32 -> tensor<64x1xi32, #blocked1>
     %87 = arith.cmpi slt, %45, %86 : tensor<64x1xi32, #blocked1>
     %88 = tt.broadcast %87 : tensor<64x1xi1, #blocked1> -> tensor<64x128xi1, #blocked1>
     %89 = tt.load %53, %88, %cst_0 : tensor<64x128x!tt.ptr<f32>, #blocked1>
     %91 = ttg.local_alloc %85 : (tensor<128x64xf32, #blocked2>) -> !ttg.memdesc<128x64xf32, #shared, #smem>
     %92 = ttg.local_load %91 : !ttg.memdesc<128x64xf32, #shared, #smem> -> tensor<128x64xf32, #ttg.dot_op<{opIdx = 0, parent = #blocked}>>
     %94 = ttg.local_alloc %89 : (tensor<64x128xf32, #blocked1>) -> !ttg.memdesc<64x128xf32, #shared1, #smem>
-    %95 = ttg.local_load %94 : !ttg.memdesc<64x128xf32, #shared1, #smem> -> tensor<64x128xf32, #ttg.dot_op<{opIdx = 1, parent = #blocked}>>
-    %96 = tt.dot %92, %95, %cst, inputPrecision = tf32 : tensor<128x64xf32, #ttg.dot_op<{opIdx = 0, parent = #blocked}>> * tensor<64x128xf32, #ttg.dot_op<{opIdx = 1, parent = #blocked}>> -> tensor<128x128xf32, #blocked>
-    %97 = tt.addptr %43, %cst_4 : tensor<128x64x!tt.ptr<f32>, #blocked2>, tensor<128x64xi32, #blocked2>
-    %98 = tt.addptr %53, %cst_5 : tensor<64x128x!tt.ptr<f32>, #blocked1>, tensor<64x128xi32, #blocked1>
+    %cst_test = arith.constant dense<1.11111116> : tensor<128x64xf32, #ttg.dot_op<{opIdx = 0, parent = #blocked}>>
+    %cst_test2 = arith.constant dense<1.11111116> : tensor<64x128xf32, #ttg.dot_op<{opIdx = 1, parent = #blocked}>>
+    %96 = tt.dot %92, %cst_test2, %cst, inputPrecision = tf32 : tensor<128x64xf32, #ttg.dot_op<{opIdx = 0, parent = #blocked}>> * tensor<64x128xf32, #ttg.dot_op<{opIdx = 1, parent = #blocked}>> -> tensor<128x128xf32, #blocked>
 
-    %78 = ttg.convert_layout %96 : tensor<128x128xf32, #blocked> -> tensor<128x128xf32, #blocked3>
+    %78 = ttg.convert_layout %96 : tensor<128x128xf32, #blocked> -> tensor<128x128xf32, #blocked2>
     tt.return
   }
 }