diff --git a/example/Performance/memBW/main.cu b/example/Performance/memBW/main.cu
index adb19adfcc97e0e688b5fb9270263c8fe5aa461e..0738bcf4f463785ef505655633888a8156b6a5d2 100644
--- a/example/Performance/memBW/main.cu
+++ b/example/Performance/memBW/main.cu
@@ -5,7 +5,7 @@
//! Memory bandwidth with small calculations
template<typename vector_type, typename vector_type2>
-inline __global__ void translate_fill_prop_write(vector_type vd_out, vector_type2 vd_in)
+__global__ void translate_fill_prop_write(vector_type vd_out, vector_type2 vd_in)
{
auto p = blockIdx.x * blockDim.x + threadIdx.x;
@@ -25,7 +25,7 @@ inline __global__ void translate_fill_prop_write(vector_type vd_out, vector_type
template<typename vector_type, typename vector_type2>
-inline __global__ void translate_fill_prop_read(vector_type vd_out, vector_type2 vd_in)
+__global__ void translate_fill_prop_read(vector_type vd_out, vector_type2 vd_in)
{
auto p = blockIdx.x * blockDim.x + threadIdx.x;
@@ -43,56 +43,9 @@ inline __global__ void translate_fill_prop_read(vector_type vd_out, vector_type2
vd_in.template get<0>(p)[1] = e+f+g;
}
-/////////////////////////////// Lambda based
-
-template<typename vector_type, typename vector_type2>
-inline __device__ void translate_fill_prop_write_notls(vector_type vd_out, vector_type2 vd_in, dim3 & blockIdx, dim3 & threadIdx)
-{
- auto p = blockIdx.x * blockDim.x + threadIdx.x;
-
- float a = vd_in.template get<0>(p)[0];
- float b = vd_in.template get<0>(p)[1];
-
- vd_out.template get<0>(p) = a + b;
-
- vd_out.template get<1>(p)[0] = a;
- vd_out.template get<1>(p)[1] = b;
-
- vd_out.template get<2>(p)[0][0] = a;
- vd_out.template get<2>(p)[0][1] = b;
- vd_out.template get<2>(p)[1][0] = a + b;
- vd_out.template get<2>(p)[1][1] = b - a;
-
- vd_in.template get<0>(p)[0] = a;
- vd_in.template get<0>(p)[1] = b;
-}
-
-
-template<typename vector_type, typename vector_type2>
-inline __device__ void translate_fill_prop_read_notls(vector_type vd_out, vector_type2 vd_in, dim3 & blockIdx, dim3 & threadIdx)
-{
- auto p = blockIdx.x * blockDim.x + threadIdx.x;
-
- float a = vd_out.template get<0>(p);
-
- float b = vd_out.template get<1>(p)[0];
- float c = vd_out.template get<1>(p)[1];
-
- float d = vd_out.template get<2>(p)[0][0];
- float e = vd_out.template get<2>(p)[0][1];
- float f = vd_out.template get<2>(p)[1][0];
- float g = vd_out.template get<2>(p)[1][1];
-
- float h = vd_in.template get<0>(p)[0];
- float i = vd_in.template get<0>(p)[1];
-
- vd_in.template get<0>(p)[0] = a+b+c+d;
- vd_in.template get<0>(p)[1] = e+f+g+h+i;
-}
-
// Arrays
-inline __global__ void translate_fill_prop_write_array(float * vd_out_scal,
+__global__ void translate_fill_prop_write_array(float * vd_out_scal,
float * vd_out_vec,
float * vd_out_mat,
float * vd_in_vec,
@@ -116,7 +69,7 @@ inline __global__ void translate_fill_prop_write_array(float * vd_out_scal,
template<typename vector_type, typename vector_type2>
-inline __global__ void translate_fill_prop_read_array(vector_type vd_out, vector_type2 vd_in)
+__global__ void translate_fill_prop_read_array(vector_type vd_out, vector_type2 vd_in)
{
auto p = blockIdx.x * blockDim.x + threadIdx.x;
@@ -134,6 +87,66 @@ inline __global__ void translate_fill_prop_read_array(vector_type vd_out, vector
vd_in.template get<0>(p)[1] = e+f+g;
}
+template<typename in_type, typename out_type>
+void check_write(in_type & in, out_type & out)
+{
+ out.template deviceToHost<0,1,2>();
+ in.template deviceToHost<0>();
+
+ bool success = true;
+ for (int i = 0 ; i < 16777216 ; i++)
+ {
+ float a = in.template get<0>(i)[0];
+ float b = in.template get<0>(i)[1];
+
+ success &= out.template get<0>(i) == a + b;
+
+ success &= out.template get<1>(i)[0] == a;
+ success &= out.template get<1>(i)[1] == b;
+
+ success &= out.template get<2>(i)[0][0] == a;
+ success &= out.template get<2>(i)[0][1] == b;
+ success &= out.template get<2>(i)[1][0] == a + b;
+ success &= out.template get<2>(i)[1][1] == b - a;
+ }
+
+ if (success == false)
+ {
+ std::cout << "FAIL" << std::endl;
+ exit(1);
+ }
+}
+
+template<typename in_type, typename out_type>
+void check_read(in_type & in, out_type & out)
+{
+ out.template deviceToHost<0,1,2>();
+ in.template deviceToHost<0>();
+
+ bool success = true;
+ for (int i = 0 ; i < 16777216 ; i++)
+ {
+ float a = out.template get<0>(i);
+
+ float b = out.template get<1>(i)[0];
+ float c = out.template get<1>(i)[1];
+
+ float d = out.template get<2>(i)[0][0];
+ float e = out.template get<2>(i)[0][1];
+ float f = out.template get<2>(i)[1][0];
+ float g = out.template get<2>(i)[1][1];
+
+ success &= in.template get<0>(i)[0] == (a+b+c+d);
+ success &= in.template get<0>(i)[1] == (e+f+g);
+ }
+
+ if (success == false)
+ {
+ std::cout << "FAIL" << std::endl;
+ exit(1);
+ }
+}
+
int main(int argc, char *argv[])
{
init_wrappers();
@@ -159,6 +172,8 @@ int main(int argc, char *argv[])
openfpm::vector<double> res;
res.resize(100);
+ in.hostToDevice<0>();
+
for (int i = 0 ; i < 110 ; i++)
{
cudaDeviceSynchronize();
@@ -183,6 +198,8 @@ int main(int argc, char *argv[])
double dev_write_tls = 0.0;
standard_deviation(res,mean_write_tls,dev_write_tls);
+ check_write(in,out);
+
for (int i = 0 ; i < 110 ; i++)
{
cudaDeviceSynchronize();
@@ -207,6 +224,10 @@ int main(int argc, char *argv[])
double dev_read_tls = 0.0;
standard_deviation(res,mean_read_tls,dev_read_tls);
+ check_read(in,out);
+
+ //////////////
+
/////////////////////////////////////////// LAMBDA //////////////////////////////////////////
@@ -219,25 +240,22 @@ int main(int argc, char *argv[])
auto vd_out = out.toKernel();
auto vd_in = in.toKernel();
- auto lamb = [&] __device__ (dim3 & blockIdx, dim3 & threadIdx)
+ auto lamb = [vd_out,vd_in] __device__ (dim3 & blockIdx, dim3 & threadIdx)
{
auto p = blockIdx.x * blockDim.x + threadIdx.x;
- float a = vd_out.template get<0>(p);
-
- float b = vd_out.template get<1>(p)[0];
- float c = vd_out.template get<1>(p)[1];
-
- float d = vd_out.template get<2>(p)[0][0];
- float e = vd_out.template get<2>(p)[0][1];
- float f = vd_out.template get<2>(p)[1][0];
- float g = vd_out.template get<2>(p)[1][1];
-
- float h = vd_in.template get<0>(p)[0];
- float i = vd_in.template get<0>(p)[1];
-
- vd_in.template get<0>(p)[0] = a+b+c+d;
- vd_in.template get<0>(p)[1] = e+f+g+h+i;
+ float a = vd_in.template get<0>(p)[0];
+ float b = vd_in.template get<0>(p)[1];
+
+ vd_out.template get<0>(p) = a + b;
+
+ vd_out.template get<1>(p)[0] = a;
+ vd_out.template get<1>(p)[1] = b;
+
+ vd_out.template get<2>(p)[0][0] = a;
+ vd_out.template get<2>(p)[0][1] = b;
+ vd_out.template get<2>(p)[1][0] = a + b;
+ vd_out.template get<2>(p)[1][1] = b - a;
};
CUDA_LAUNCH_LAMBDA(ite, lamb);
@@ -280,12 +298,9 @@ int main(int argc, char *argv[])
float e = vd_out.template get<2>(p)[0][1];
float f = vd_out.template get<2>(p)[1][0];
float g = vd_out.template get<2>(p)[1][1];
-
- float h = vd_in.template get<0>(p)[0];
- float i = vd_in.template get<0>(p)[1];
vd_in.template get<0>(p)[0] = a+b+c+d;
- vd_in.template get<0>(p)[1] = e+f+g+h+i;
+ vd_in.template get<0>(p)[1] = e+f+g;
};
CUDA_LAUNCH_LAMBDA(ite, lamb);
@@ -305,11 +320,44 @@ int main(int argc, char *argv[])
double dev_read_lamb = 0.0;
standard_deviation(res,mean_read_lamb,dev_read_lamb);
+ #ifdef CUDIFY_USE_CUDA
+
+ for (int i = 0 ; i < 110 ; i++)
+ {
+ cudaDeviceSynchronize();
+ timer t;
+ t.start();
+
+ float * a = (float *)in.getDeviceBuffer<0>();
+ float * b = (float *)out.getDeviceBuffer<1>();
+
+ cudaMemcpy(a,b,2*16777216*4,cudaMemcpyDeviceToDevice);
+
+ cudaDeviceSynchronize();
+
+ t.stop();
+
+ if (i >=10)
+ {res.get(i-10) = nele*4*4 / t.getwct() * 1e-9;}
+
+ std::cout << "Time: " << t.getwct() << std::endl;
+ std::cout << "BW: " << nele*4*4 / t.getwct() * 1e-9 << " GB/s" << std::endl;
+ }
+
+ double mean_read_mes = 0.0;
+ double dev_read_mes = 0.0;
+ standard_deviation(res,mean_read_mes,dev_read_mes);
+
+ std::cout << "Average measured: " << mean_read_mes << " deviation: " << dev_read_mes << std::endl;
+
+ #endif
+
std::cout << "Average READ with TLS: " << mean_read_tls << " deviation: " << dev_read_tls << std::endl;
std::cout << "Average WRITE with TLS: " << mean_write_tls << " deviation: " << dev_write_tls << std::endl;
std::cout << "Average READ with lamb: " << mean_read_lamb << " deviation: " << dev_read_lamb << std::endl;
std::cout << "Average WRITE with lamb: " << mean_write_lamb << " deviation: " << dev_write_lamb << std::endl;
+
}
#else