diff --git a/modules/dynamicuda/src/cuda/matrix_operations.cu b/modules/dynamicuda/src/cuda/matrix_operations.cu
index c9b12de104..35bca63200 100644
--- a/modules/dynamicuda/src/cuda/matrix_operations.cu
+++ b/modules/dynamicuda/src/cuda/matrix_operations.cu
@@ -44,6 +44,7 @@
 #include "opencv2/gpu/device/transform.hpp"
 #include "opencv2/gpu/device/functional.hpp"
 #include "opencv2/gpu/device/type_traits.hpp"
+#include "opencv2/gpu/device/vec_traits.hpp"
 
 namespace cv { namespace gpu { namespace device
 {
@@ -105,87 +106,59 @@ namespace cv { namespace gpu { namespace device
     ////////////////////////////////// SetTo //////////////////////////////////
     ///////////////////////////////////////////////////////////////////////////
 
-    __constant__ uchar scalar_8u[4];
-    __constant__ schar scalar_8s[4];
-    __constant__ ushort scalar_16u[4];
-    __constant__ short scalar_16s[4];
-    __constant__ int scalar_32s[4];
-    __constant__ float scalar_32f[4];
-    __constant__ double scalar_64f[4];
-
-    template <typename T> __device__ __forceinline__ T readScalar(int i);
-    template <> __device__ __forceinline__ uchar readScalar<uchar>(int i) {return scalar_8u[i];}
-    template <> __device__ __forceinline__ schar readScalar<schar>(int i) {return scalar_8s[i];}
-    template <> __device__ __forceinline__ ushort readScalar<ushort>(int i) {return scalar_16u[i];}
-    template <> __device__ __forceinline__ short readScalar<short>(int i) {return scalar_16s[i];}
-    template <> __device__ __forceinline__ int readScalar<int>(int i) {return scalar_32s[i];}
-    template <> __device__ __forceinline__ float readScalar<float>(int i) {return scalar_32f[i];}
-    template <> __device__ __forceinline__ double readScalar<double>(int i) {return scalar_64f[i];}
-
-    void writeScalar(const uchar* vals)
-    {
-        cudaSafeCall( cudaMemcpyToSymbol(scalar_8u, vals, sizeof(uchar) * 4) );
-    }
-    void writeScalar(const schar* vals)
-    {
-        cudaSafeCall( cudaMemcpyToSymbol(scalar_8s, vals, sizeof(schar) * 4) );
-    }
-    void writeScalar(const ushort* vals)
-    {
-        cudaSafeCall( cudaMemcpyToSymbol(scalar_16u, vals, sizeof(ushort) * 4) );
-    }
-    void writeScalar(const short* vals)
-    {
-        cudaSafeCall( cudaMemcpyToSymbol(scalar_16s, vals, sizeof(short) * 4) );
-    }
-    void writeScalar(const int* vals)
-    {
-        cudaSafeCall( cudaMemcpyToSymbol(scalar_32s, vals, sizeof(int) * 4) );
-    }
-    void writeScalar(const float* vals)
-    {
-        cudaSafeCall( cudaMemcpyToSymbol(scalar_32f, vals, sizeof(float) * 4) );
-    }
-    void writeScalar(const double* vals)
-    {
-        cudaSafeCall( cudaMemcpyToSymbol(scalar_64f, vals, sizeof(double) * 4) );
-    }
-
     template<typename T>
-    __global__ void set_to_without_mask(T* mat, int cols, int rows, size_t step, int channels)
+    __global__ void set_to_without_mask(PtrStepSz<T> mat, typename TypeVec<T, 4>::vec_type val, int channels)
     {
-        size_t x = blockIdx.x * blockDim.x + threadIdx.x;
-        size_t y = blockIdx.y * blockDim.y + threadIdx.y;
+        const int y = blockIdx.x * blockDim.y + threadIdx.y;
 
-        if ((x < cols * channels ) && (y < rows))
+        if (y < mat.rows)
         {
-            size_t idx = y * ( step >> shift_and_sizeof<T>::shift ) + x;
-            mat[idx] = readScalar<T>(x % channels);
+            const T vals[] = {
+                val.x, val.y, val.z, val.w
+            };
+
+            T* row = mat.ptr(y);
+
+            for (int x = threadIdx.x; x < mat.cols * channels; x += 32)
+            {
+                row[x] = vals[x % channels];
+            }
         }
     }
 
     template<typename T>
-    __global__ void set_to_with_mask(T* mat, const uchar* mask, int cols, int rows, size_t step, int channels, size_t step_mask)
+    __global__ void set_to_with_mask(PtrStepSz<T> mat, const PtrStepb mask, typename TypeVec<T, 4>::vec_type val, int channels)
     {
-        size_t x = blockIdx.x * blockDim.x + threadIdx.x;
-        size_t y = blockIdx.y * blockDim.y + threadIdx.y;
+        const int y = blockIdx.x * blockDim.y + threadIdx.y;
 
-        if ((x < cols * channels ) && (y < rows))
-            if (mask[y * step_mask + x / channels] != 0)
+        if (y < mat.rows)
+        {
+            const T vals[] = {
+                val.x, val.y, val.z, val.w
+            };
+
+            T* row = mat.ptr(y);
+            const uchar* mask_row = mask.ptr(y);
+
+            for (int x = threadIdx.x; x < mat.cols * channels; x += 32)
             {
-                size_t idx = y * ( step >> shift_and_sizeof<T>::shift ) + x;
-                mat[idx] = readScalar<T>(x % channels);
+                if (mask_row[x / channels])
+                {
+                    row[x] = vals[x % channels];
+                }
             }
+        }
     }
+
     template <typename T>
     void set_to_gpu(PtrStepSzb mat, const T* scalar, PtrStepSzb mask, int channels, cudaStream_t stream)
     {
-        writeScalar(scalar);
+        typedef typename TypeVec<T, 4>::vec_type vec_type;
 
-        dim3 threadsPerBlock(32, 8, 1);
-        dim3 numBlocks (mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
+        dim3 block(32, 8);
+        dim3 grid(divUp(mat.rows, block.y));
 
-        set_to_with_mask<T><<<numBlocks, threadsPerBlock, 0, stream>>>((T*)mat.data, (uchar*)mask.data, mat.cols, mat.rows, mat.step, channels, mask.step);
+        set_to_with_mask<T><<<grid, block, 0, stream>>>(PtrStepSz<T>(mat), mask, VecTraits<vec_type>::make(scalar), channels);
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)
@@ -203,12 +176,12 @@ namespace cv { namespace gpu { namespace device
     template <typename T>
     void set_to_gpu(PtrStepSzb mat, const T* scalar, int channels, cudaStream_t stream)
     {
-        writeScalar(scalar);
+        typedef typename TypeVec<T, 4>::vec_type vec_type;
 
-        dim3 threadsPerBlock(32, 8, 1);
-        dim3 numBlocks (mat.cols * channels / threadsPerBlock.x + 1, mat.rows / threadsPerBlock.y + 1, 1);
+        dim3 block(32, 8);
+        dim3 grid(divUp(mat.rows, block.y));
 
-        set_to_without_mask<T><<<numBlocks, threadsPerBlock, 0, stream>>>((T*)mat.data, mat.cols, mat.rows, mat.step, channels);
+        set_to_without_mask<T><<<grid, block, 0, stream>>>(PtrStepSz<T>(mat), VecTraits<vec_type>::make(scalar), channels);
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)