Switch data from 1.0, 2.0 and 3.0 to 0.1, 0.2, and 0.3 resp.

Using integers for maths gets unstable past 38 interations even
in double precision. Using the original values/10 is safe up to
the default 100 iterations.

ACCStream.cpp

@@ -65,7 +65,7 @@ void ACCStream<T>::copy()
 template <class T>
 void ACCStream<T>::mul()
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
 
   unsigned int array_size = this->array_size;
   T *b = this->b;
@@ -94,7 +94,7 @@ void ACCStream<T>::add()
 template <class T>
 void ACCStream<T>::triad()
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
 
   unsigned int array_size = this->array_size;
   T *a = this->a;
@@ -133,4 +133,3 @@ std::string getDeviceDriver(const int)
 }
 template class ACCStream<float>;
 template class ACCStream<double>;
-

CUDAStream.cu

@@ -118,7 +118,7 @@ void CUDAStream<T>::copy()
 template <typename T>
 __global__ void mul_kernel(T * b, const T * c)
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   const int i = blockDim.x * blockIdx.x + threadIdx.x;
   b[i] = scalar * c[i];
 }
@@ -151,7 +151,7 @@ void CUDAStream<T>::add()
 template <typename T>
 __global__ void triad_kernel(T * a, const T * b, const T * c)
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   const int i = blockDim.x * blockIdx.x + threadIdx.x;
   a[i] = b[i] + scalar * c[i];
 }

KOKKOSStream.cpp

@@ -84,7 +84,7 @@ void KOKKOSStream<T>::mul()
   View<double*, DEVICE> b(*d_b);
   View<double*, DEVICE> c(*d_c);
 
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   parallel_for(array_size, KOKKOS_LAMBDA (const int index)
   {
     b[index] = scalar*c[index];
@@ -114,7 +114,7 @@ void KOKKOSStream<T>::triad()
   View<double*, DEVICE> b(*d_b);
   View<double*, DEVICE> c(*d_c);
 
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   parallel_for(array_size, KOKKOS_LAMBDA (const int index)
   {
     a[index] = b[index] + scalar*c[index];
@@ -142,4 +142,3 @@ std::string getDeviceDriver(const int device)
 
 //template class KOKKOSStream<float>;
 template class KOKKOSStream<double>;
-

OCLStream.cpp

@@ -14,7 +14,7 @@ void getDeviceList(void);
 
 std::string kernels{R"CLC(
 
-  constant TYPE scalar = 3.0;
+  constant TYPE scalar = 0.3;
 
   kernel void copy(
     global const TYPE * restrict a,
@@ -253,4 +253,3 @@ std::string getDeviceDriver(const int device)
 
 template class OCLStream<float>;
 template class OCLStream<double>;
-

OMP3Stream.cpp

@@ -56,7 +56,7 @@ void OMP3Stream<T>::copy()
 template <class T>
 void OMP3Stream<T>::mul()
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   #pragma omp parallel for
   for (int i = 0; i < array_size; i++)
   {
@@ -77,7 +77,7 @@ void OMP3Stream<T>::add()
 template <class T>
 void OMP3Stream<T>::triad()
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   #pragma omp parallel for
   for (int i = 0; i < array_size; i++)
   {
@@ -103,4 +103,3 @@ std::string getDeviceDriver(const int)
 
 template class OMP3Stream<float>;
 template class OMP3Stream<double>;
-

OMP45Stream.cpp

@@ -64,7 +64,7 @@ void OMP45Stream<T>::copy()
 template <class T>
 void OMP45Stream<T>::mul()
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
 
   unsigned int array_size = this->array_size;
   T *b = this->b;
@@ -93,7 +93,7 @@ void OMP45Stream<T>::add()
 template <class T>
 void OMP45Stream<T>::triad()
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
 
   unsigned int array_size = this->array_size;
   T *a = this->a;
@@ -132,4 +132,3 @@ std::string getDeviceDriver(const int)
 }
 template class OMP45Stream<float>;
 template class OMP45Stream<double>;
-

RAJAStream.cpp

@@ -77,7 +77,7 @@ void RAJAStream<T>::mul()
 {
   T* b = d_b;
   T* c = d_c;
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   forall<policy>(index_set, [=] RAJA_DEVICE (int index)
   {
     b[index] = scalar*c[index];
@@ -102,7 +102,7 @@ void RAJAStream<T>::triad()
   T* a = d_a;
   T* b = d_b;
   T* c = d_c;
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   forall<policy>(index_set, [=] RAJA_DEVICE (int index)
   {
     a[index] = b[index] + scalar*c[index];
@@ -128,4 +128,3 @@ std::string getDeviceDriver(const int device)
 
 template class RAJAStream<float>;
 template class RAJAStream<double>;
-

SYCLStream.cpp

@@ -78,7 +78,7 @@ void SYCLStream<T>::copy()
 template <class T>
 void SYCLStream<T>::mul()
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   queue->submit([&](handler &cgh)
   {
     auto kb = d_b->template get_access<access::mode::write>(cgh);
@@ -110,7 +110,7 @@ void SYCLStream<T>::add()
 template <class T>
 void SYCLStream<T>::triad()
 {
-  const T scalar = 3.0;
+  const T scalar = 0.3;
   queue->submit([&](handler &cgh)
   {
     auto ka = d_a->template get_access<access::mode::write>(cgh);

main.cpp

@@ -83,8 +83,8 @@ void run()
     std::cout << "Precision: double" << std::endl;
 
   // Create host vectors
-  std::vector<T> a(ARRAY_SIZE, 1.0);
+  std::vector<T> a(ARRAY_SIZE, 0.1);
-  std::vector<T> b(ARRAY_SIZE, 2.0);
+  std::vector<T> b(ARRAY_SIZE, 0.2);
   std::vector<T> c(ARRAY_SIZE, 0.0);
   std::streamsize ss = std::cout.precision();
   std::cout << std::setprecision(1) << std::fixed
@@ -216,11 +216,11 @@ template <typename T>
 void check_solution(const unsigned int ntimes, std::vector<T>& a, std::vector<T>& b, std::vector<T>& c)
 {
   // Generate correct solution
-  T goldA = 1.0;
+  T goldA = 0.1;
-  T goldB = 2.0;
+  T goldB = 0.2;
   T goldC = 0.0;
 
-  const T scalar = 3.0;
+  const T scalar = 0.3;
 
   for (unsigned int i = 0; i < ntimes; i++)
   {