Aggregate initialise numeric types, resolves #134

src/acc/ACCStream.cpp

@@ -149,7 +149,7 @@ void ACCStream<T>::nstream()
 template <class T>
 T ACCStream<T>::dot()
 {
-  T sum = 0.0;
+  T sum{};
 
   int array_size = this->array_size;
   T * restrict a = this->a;

src/hip/HIPStream.cpp

@@ -244,7 +244,7 @@ __global__ void dot_kernel(const T * a, const T * b, T * sum, int array_size)
   const size_t local_i = threadIdx.x;
   size_t i = blockDim.x * blockIdx.x + local_i;
 
-  tb_sum[local_i] = 0.0;
+  tb_sum[local_i]{};
   for (; i < array_size; i += blockDim.x*gridDim.x)
     tb_sum[local_i] += a[i] * b[i];
 
@@ -269,7 +269,7 @@ T HIPStream<T>::dot()
   hipDeviceSynchronize();
   check_error();
 
-  T sum = 0.0;
+  T sum{};
   for (int i = 0; i < dot_num_blocks; i++)
     sum += sums[i];
 

src/kokkos/KokkosStream.cpp

@@ -140,7 +140,7 @@ T KokkosStream<T>::dot()
   Kokkos::View<T*> a(*d_a);
   Kokkos::View<T*> b(*d_b);
 
-  T sum = 0.0;
+  T sum{};
 
   Kokkos::parallel_reduce(array_size, KOKKOS_LAMBDA (const long index, T &tmp)
   {

src/main.cpp

@@ -309,7 +309,7 @@ void run()
   stream->init_arrays(startA, startB, startC);
 
   // Result of the Dot kernel, if used.
-  T sum = 0.0;
+  T sum{};
 
   std::vector<std::vector<double>> timings;
 
@@ -467,7 +467,7 @@ void check_solution(const unsigned int ntimes, std::vector<T>& a, std::vector<T>
   T goldA = startA;
   T goldB = startB;
   T goldC = startC;
-  T goldSum = 0.0;
+  T goldSum{};
 
   const T scalar = startScalar;
 
@@ -493,11 +493,11 @@ void check_solution(const unsigned int ntimes, std::vector<T>& a, std::vector<T>
   goldSum = goldA * goldB * ARRAY_SIZE;
 
   // Calculate the average error
-  long double errA = std::accumulate(a.begin(), a.end(), 0.0, [&](double sum, const T val){ return sum + std::fabs(val - goldA); });
+  long double errA = std::accumulate(a.begin(), a.end(), T{}, [&](double sum, const T val){ return sum + std::fabs(val - goldA); });
   errA /= a.size();
-  long double errB = std::accumulate(b.begin(), b.end(), 0.0, [&](double sum, const T val){ return sum + std::fabs(val - goldB); });
+  long double errB = std::accumulate(b.begin(), b.end(), T{}, [&](double sum, const T val){ return sum + std::fabs(val - goldB); });
   errB /= b.size();
-  long double errC = std::accumulate(c.begin(), c.end(), 0.0, [&](double sum, const T val){ return sum + std::fabs(val - goldC); });
+  long double errC = std::accumulate(c.begin(), c.end(), T{}, [&](double sum, const T val){ return sum + std::fabs(val - goldC); });
   errC /= c.size();
   long double errSum = std::fabs((sum - goldSum)/goldSum);
 

src/ocl/OCLStream.cpp

@@ -260,7 +260,7 @@ T OCLStream<T>::dot()
   );
   cl::copy(queue, d_sum, sums.begin(), sums.end());
 
-  T sum = 0.0;
+  T sum{};
   for (T val : sums)
     sum += val;
 

src/omp/OMPStream.cpp

@@ -220,7 +220,7 @@ void OMPStream<T>::nstream()
 template <class T>
 T OMPStream<T>::dot()
 {
-  T sum = 0.0;
+  T sum{};
 
 #ifdef OMP_TARGET_GPU
   int array_size = this->array_size;

src/raja/RAJAStream.cpp

@@ -131,7 +131,7 @@ T RAJAStream<T>::dot()
   T* RAJA_RESTRICT a = d_a;
   T* RAJA_RESTRICT b = d_b;
 
-  RAJA::ReduceSum<reduce_policy, T> sum(0.0);
+  RAJA::ReduceSum<reduce_policy, T> sum(T{});
 
   forall<policy>(range, [=] RAJA_DEVICE (RAJA::Index_type index)
   {

src/std-data/STDDataStream.cpp

@@ -94,7 +94,7 @@ template <class T>
 T STDDataStream<T>::dot()
 {
   // sum = 0; sum += a[i]*b[i]; return sum;
-  return std::transform_reduce(exe_policy, a, a + array_size, b, 0.0);
+  return std::transform_reduce(exe_policy, a, a + array_size, b, T{});
 }
 
 void listDevices(void)

src/std-indices/STDIndicesStream.cpp

@@ -105,7 +105,7 @@ template <class T>
 T STDIndicesStream<T>::dot()
 {
   // sum = 0; sum += a[i]*b[i]; return sum;
-  return std::transform_reduce(exe_policy, a, a + array_size, b, 0.0);
+  return std::transform_reduce(exe_policy, a, a + array_size, b, T{});
 }
 
 void listDevices(void)

src/std-ranges/STDRangesStream.cpp

@@ -135,7 +135,7 @@ T STDRangesStream<T>::dot()
   return
     std::transform_reduce(
       exe_policy,
-      a, a + array_size, b, 0.0);
+      a, a + array_size, b, T{});
 }
 
 void listDevices(void)

src/sycl/SYCLStream.cpp

@@ -191,7 +191,7 @@ T SYCLStream<T>::dot()
       size_t li = item.get_local_id(0);
       size_t global_size = item.get_global_range()[0];
 
-      wg_sum[li] = 0.0;
+      wg_sum[li] = {};
       for (; i < N; i += global_size)
         wg_sum[li] += ka[i] * kb[i];
 
@@ -208,7 +208,7 @@ T SYCLStream<T>::dot()
     });
   });
 
-  T sum = 0.0;
+  T sum{};
   auto h_sum = d_sum->template get_access<access::mode::read>();
   for (int i = 0; i < dot_num_groups; i++)
   {