fix(dnn/cuda): fix cublas matmul on sm60

GitOrigin-RevId: 3fc0c30a23f1dfe35d6629595b2cb1a8c2f379c5

dnn/src/cuda/conv_bias/matmul_8x8x32.cpp

@@ -21,7 +21,7 @@ bool ConvBiasForwardImpl::AlgoMatmul8x8x32::is_available(
         const SizeArgs& args) const {
     if (args.z_layout->ndim > 0)
         return false;
-    if (cuda::current_device_prop().major < 6)
+    if (!is_compute_capability_required(6, 1))
         return false;
 
     auto dst_layout = *args.dst_layout;

dnn/src/cuda/matrix_mul/cublas.cpp

@@ -42,7 +42,7 @@ bool MatrixMulForwardImpl::AlgoCuBlas::is_available(
          */
         return args.layout_a.stride[0] % 4 == 0 &&
                args.layout_b.stride[0] % 4 == 0 &&
-               current_device_prop().major > 5;
+               is_compute_capability_required(6, 1);
     }
     return false;
 }

dnn/test/cuda/benchmark.cpp

@@ -24,7 +24,7 @@ namespace test {
 
 TEST_F(CUDA, BENCHMARK_CONVOLUTION_8X8X32)
 {
-    if (cuda::current_device_prop().major < 6) {
+    if (!cuda::is_compute_capability_required(6, 1)) {
         printf("Skip CUDA.BENCHMARK_CONVOLUTION_8X8X32 test as current device"
                "doesn't support\n");
         return;

dnn/test/cuda/conv_bias.cpp

@@ -325,7 +325,7 @@ TEST_F(CUDA, CONV_BIAS_FORWARD_CHANWISE_SMALL) {
 }
 
 TEST_F(CUDA, CONV_BIAS_FORWARD_CHANWISE_8x8x32) {
-    require_compute_capability(6, 0);
+    require_compute_capability(6, 1);
     Checker<ConvBiasForward> checker(handle_cuda());
     checker.set_before_exec_callback(conv_bias::ConvBiasAlgoChecker<ConvBias>(
             ConvBiasForward::algo_name<ConvBias::DirectParam>(
@@ -472,7 +472,7 @@ TEST_F(CUDA, CONV_BIAS_FORWARD_MATMUL) {
 }
 
 TEST_F(CUDA, CONV_BIAS_FORWARD_MATMUL_8x8x32) {
-    require_compute_capability(6, 0);
+    require_compute_capability(6, 1);
     Checker<ConvBiasForward> checker(handle_cuda());
     checker.set_before_exec_callback(conv_bias::ConvBiasAlgoChecker<ConvBias>(
             ConvBiasForward::algo_name<ConvBiasForward::MatmulParam>(
@@ -517,7 +517,7 @@ TEST_F(CUDA, CONV_BIAS_FORWARD_MATMUL_8x8x32) {
 }
 
 TEST_F(CUDA, CONV_BIAS_FORWARD_MATMUL_NCHW4) {
-    require_compute_capability(6, 0);
+    require_compute_capability(6, 1);
     Checker<ConvBiasForward> checker(handle_cuda());
     checker.set_before_exec_callback(conv_bias::ConvBiasAlgoChecker<ConvBias>(
             ConvBiasForward::algo_name<ConvBiasForward::MatmulParam>(

dnn/test/cuda/convolution.cpp

@@ -30,7 +30,7 @@ namespace test {
 
 TEST_F(CUDA, CONVOLUTION_8X8X32)
 {
-    if (cuda::current_device_prop().major < 6) {
+    if (!cuda::is_compute_capability_required(6, 1)) {
         printf("Skip CUDA.CONVOLUTION_8X8X32 test as current device"
                "doesn't support\n");
         return;
@@ -112,7 +112,7 @@ TEST_F(CUDA, CONVOLUTION_FORWARD)
 }
 
 TEST_F(CUDA, CONV_FORWARD_MATMUL_NCHW4) {
-    if (cuda::current_device_prop().major < 6)
+    if (!cuda::is_compute_capability_required(6, 1))
         return;
     using namespace convolution;
     Checker<Convolution> checker(handle_cuda());

dnn/test/cuda/convolution3d.cpp

@@ -24,7 +24,7 @@ namespace test {
 
 #if 0
 TEST_F(CUDA, CONVOLUTION3D_8X8X32) {
-    if (cuda::current_device_prop().major < 6) {
+    if (!cuda::is_compute_capability_required(6, 1)) {
         printf("Skip CUDA.CONVOLUTION_8X8X32 test as current device"
                "doesn't support\n");
         return;

dnn/test/cuda/group_conv.cpp

@@ -23,7 +23,7 @@ namespace test {
 
 TEST_F(CUDA, GROUP_CONV_FORWARD)
 {
-    bool is_int_available = (cuda::current_device_prop().major >= 6);
+    bool is_int_available = cuda::is_compute_capability_required(6, 1);
     auto run = [&](size_t N, size_t IC, size_t IH, size_t IW,
             size_t FH, size_t FW,
             size_t OC, size_t /* OH */, size_t /* OW */,

dnn/test/cuda/group_conv3d.cpp

@@ -21,7 +21,7 @@ namespace megdnn {
 namespace test {
 
 TEST_F(CUDA, GROUP_CONVOLUTION3D_FORWARD) {
-    bool is_int_available = (cuda::current_device_prop().major >= 6);
+    bool is_int_available = cuda::is_compute_capability_required(6, 1);
     static_cast<void>(is_int_available);
     auto run = [&](size_t N, size_t IC, size_t ID, size_t IH, size_t IW,
                    size_t FD, size_t FH, size_t FW, size_t OC, size_t PD,

dnn/test/cuda/matrix_mul.cpp

@@ -193,8 +193,15 @@ TEST_F(CUDA, MATRIX_MUL)
     Checker<MatrixMul> checker(handle_cuda());
     using Param = MatrixMul::Param;
     size_t m = 12, n = 16, k = 20;
-    for (DType dtype: std::array<DType, 3>{
-            {dtype::Float32(), dtype::Float16(), dtype::Int32()}}) {
+
+    bool is_int_available = cuda::is_compute_capability_required(6, 1);
+    std::vector<DType> dtype_array;
+    dtype_array.push_back(dtype::Float32());
+    dtype_array.push_back(dtype::Float16());
+    if (is_int_available)
+        dtype_array.push_back(dtype::Int32());
+
+    for (DType dtype : dtype_array) {
         for (unsigned mask = 0; mask < 4; ++mask) {
             Param param;
             param.transposeA = mask & 1;