Reduce code duplications in matrixMulWithMdSpan (#2326)

example/matrixMulWithMdspan/src/matrixMulMdSpan.cpp

@@ -71,6 +71,21 @@ struct MatrixMulKernel
  }
 };
 
+// initialize the matrix
+template<typename TMdSpan>
+inline void initializeMatrx(TMdSpan& span)
+{
+ auto const numColumns = span.extent(1);
+ for(Idx i = 0; i < span.extent(0); ++i)
+ {
+ for(Idx j = 0; j < numColumns; ++j)
+ {
+ // fill with some data
+ span(i, j) = static_cast<DataType>(i * numColumns + j);
+ }
+ }
+}
+
 // In standard projects, you typically do not execute the code with any available accelerator.
 // Instead, a single accelerator is selected once from the active accelerators and the kernels are executed with the
 // selected accelerator only. If you use the example as the starting point for your project, you can rename the
@@ -82,9 +97,9 @@ auto example(TAccTag const&) -> int
  using Dim = alpaka::DimInt<2>;
 
  // Define matrix dimensions, A is MxK and B is KxN
- const Idx M = 1024;
- const Idx N = 512;
- const Idx K = 1024;
+ Idx const M = 1024;
+ Idx const N = 512;
+ Idx const K = 1024;
 
  // Define device and queue
  using Acc = alpaka::AccCpuSerial<Dim, Idx>;
@@ -113,22 +128,8 @@ auto example(TAccTag const&) -> int
  auto mdHostB = alpaka::experimental::getMdSpan(bufHostB);
 
  // Initialize host matrices
- for(Idx i = 0; i < M; ++i)
- {
- for(Idx j = 0; j < K; ++j)
- {
- // fill with some data
- mdHostA(i, j) = static_cast<DataType>(i * K + j);
- }
- }
- for(Idx i = 0; i < K; ++i)
- {
- for(Idx j = 0; j < N; ++j)
- {
- // fill with some data
- mdHostB(i, j) = static_cast<DataType>(i * N + j);
- }
- }
+ initializeMatrx(mdHostA);
+ initializeMatrx(mdHostB);
 
  // Allocate device memory
  auto bufDevA = alpaka::allocBuf<DataType, Idx>(devAcc, extentA);