removed most of the extraneous code, testing with different dimensions

example/43_elementwise_permute_2d/elementwise_permute_4D_fp16_2d.cpp

@@ -48,7 +48,7 @@ int main()
     bool do_verification = true;
     bool time_kernel     = true;
 
-    const int N = 16;
+    const int N = 120;
     const int H = 32;
     const int W = 64;
 
@@ -72,7 +72,6 @@ int main()
     std::array<void*, 1> output      = {b_device_buf.GetDeviceBuffer()};
 
     std::array<ck::index_t, 4> ab_lengths{N, H, W, C};
-    // std::copy(nhwc.begin(), nhwc.end(), ab_lengths.begin());
 
     std::array<ck::index_t, 4> a_strides = {C * H * W, W, 1, H * W};
     std::array<ck::index_t, 4> b_strides = {H * W * C, W * C, C, 1};

include/ck/tensor_operation/gpu/device/device_elementwise_2d.hpp

@@ -69,7 +69,11 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
     using OutDataTypePointerTuple = decltype(GenerateOutDataTypePointerTuple());
 
     template <typename Desc_MN>
-    static auto PadDescriptor_MN_2d(Desc_MN desc_mn, index_t gridSize, index_t blockSize, index_t num_threads_m, index_t num_threads_n)
+    static auto PadDescriptor_MN_2d(Desc_MN desc_mn,
+                                    index_t gridSize,
+                                    index_t blockSize,
+                                    index_t num_threads_m,
+                                    index_t num_threads_n)
     {
         std::ignore               = blockSize;
         std::ignore               = gridSize;
@@ -172,8 +176,8 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
               elementwise_op_(elementwise_op),
               blockSize_(256),
               gridSize_(120), // FIXME - Calculate the grid size by number of CU in the future
-	      num_threads_m_((gridSize_*blockSize_)/8),
-	      num_threads_n_(8)
+              num_threads_m_((gridSize_ * blockSize_) / 16),
+              num_threads_n_(16)
         {
             static_assert(NumDim_m > 0, "");
             static_assert(NumDim_n > 0, "");
@@ -194,15 +198,23 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
 
             in_grid_2d_desc_tuple_ = generate_tuple(
                 [&](auto I) {
-                    return MakeDescriptor_MN(
-                        lengths, inStridesArray[I.value], gridSize_, blockSize_, num_threads_m_, num_threads_n_);
+                    return MakeDescriptor_MN(lengths,
+                                             inStridesArray[I.value],
+                                             gridSize_,
+                                             blockSize_,
+                                             num_threads_m_,
+                                             num_threads_n_);
                 },
                 Number<NumInput>{});
 
             out_grid_2d_desc_tuple_ = generate_tuple(
                 [&](auto I) {
-                    return MakeDescriptor_MN(
-                        lengths, outStridesArray[I.value], gridSize_, blockSize_, num_threads_m_, num_threads_n_);
+                    return MakeDescriptor_MN(lengths,
+                                             outStridesArray[I.value],
+                                             gridSize_,
+                                             blockSize_,
+                                             num_threads_m_,
+                                             num_threads_n_);
                 },
                 Number<NumOutput>{});
         }
@@ -284,10 +296,8 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
             return false;
         };
 
-
         bool valid = true;
         static_for<0, NumInput, 1>{}([&](auto I) {
-            std::cout << "running: " << I << std::endl;
             if(!IsScalarPerVectorValid(pArg->lengths_,
                                        pArg->inStridesArray_[I.value],
                                        InScalarPerVectorSeq::At(I),
@@ -296,7 +306,6 @@ struct DeviceElementwise : public DeviceElementwiseBase<InDataTypeTuple,
         });
 
         static_for<0, NumOutput, 1>{}([&](auto I) {
-            std::cout << "running 2: " << I << std::endl;
             if(!IsScalarPerVectorValid(pArg->lengths_,
                                        pArg->outStridesArray_[I.value],
                                        OutScalarPerVectorSeq::At(I),