Merge branch 'master' of github.com:mosaic-group/openfpm

example/Vector/7_SPH_dlb/main.cpp

@@ -303,7 +303,7 @@ inline double Wab(double r)
 	if (r < 1.0)
 		return (1.0 - 3.0/2.0*r*r + 3.0/4.0*r*r*r)*a2;
 	else if (r < 2.0)
-		return (1.0/4.0*(2.0 - r*r)*(2.0 - r*r)*(2.0 - r*r))*a2;
+		return (1.0/4.0*(2.0 - r)*(2.0 - r)*(2.0 - r))*a2;
 	else
 		return 0.0;
 }
@@ -1031,7 +1031,7 @@ int main(int argc, char* argv[])
 
 	// extended boundary around the domain, and the processor domain
 	Ghost<3,double> g(2*H);
-	
+
 	//! \cond [Initialization and parameters] \endcond
 
 	/*!
@@ -1493,4 +1493,3 @@ int main(int argc, char* argv[])
 	 *
 	 */
 }
-

example/Vector/7_SPH_dlb_gpu/main.cu

@@ -45,12 +45,12 @@
  *
  * my_kernel<<<wthr,thr>>>(arguments ... )
  *
- * Where wthr is the number of workgroups and thr is the number of threads in a workgroup and arguments... are the arguments to pass to the kernel. 
+ * Where wthr is the number of workgroups and thr is the number of threads in a workgroup and arguments... are the arguments to pass to the kernel.
  * Equivalently we can launch a kernel with the macro CUDA_LAUNCH_DIM3(my_kernel,wthr,thr,arguments...) or CUDA_LAUNCH(my_kernel,ite,arguments) where
  * ite has been taken using getDomainIteratorGPU. There are several advantage on using CUDA_LAUNCH. The first advantage in using the macro is enabling SE_CLASS1
  * all kernel launch become synchronous and an error check is performed before continue to the next kernel making debugging easier. Another feature is the possibility
- * to run CUDA code on CPU without a GPU. compiling with "CUDA_ON_CPU=1 make" (Note openfpm must be compiled with GPU support (-g)  or with CUDA_ON_CPU support 
- * (-c "... --enable_cuda_on_cpu"). You can compile this example on CPU. You do not have to change a single line of code for this example. (Check the video to see this 
+ * to run CUDA code on CPU without a GPU. compiling with "CUDA_ON_CPU=1 make" (Note openfpm must be compiled with GPU support (-g)  or with CUDA_ON_CPU support
+ * (-c "... --enable_cuda_on_cpu"). You can compile this example on CPU. You do not have to change a single line of code for this example. (Check the video to see this
  * feature in action). All the openfpm GPU example and CUDA example can run on CPU if they use CUDA_LAUNCH as macro. We are planning to support
  * AMD GPUs as well using this system.
  *
@@ -223,7 +223,7 @@ inline __device__ __host__ real_number Wab(real_number r)
 	if (r < 1.0)
 		return (1.0 - 3.0/2.0*r*r + 3.0/4.0*r*r*r)*a2;
 	else if (r < 2.0)
-		return (1.0/4.0*(2.0 - r*r)*(2.0 - r*r)*(2.0 - r*r))*a2;
+		return (1.0/4.0*(2.0 - r)*(2.0 - r)*(2.0 - r))*a2;
 	else
 		return 0.0;
 }
@@ -839,7 +839,7 @@ int main(int argc, char* argv[])
 
 		++obstacle_box;
 	}
-	
+
 	vd.map();
 
 	// Now that we fill the vector with particles
@@ -848,7 +848,7 @@ int main(int argc, char* argv[])
 	vd.addComputationCosts(md);
 	vd.getDecomposition().decompose();
 	vd.map();
-    
+
 	///////////////////////////
 
 	// Ok the initialization is done on CPU on GPU we are doing the main loop, so first we offload all properties on GPU
@@ -958,7 +958,7 @@ int main(int argc, char* argv[])
 
 	openfpm_finalize();
 }
- 
+
 #else
 
 int main(int argc, char* argv[])

example/Vector/7_SPH_dlb_gpu_more_opt/main.cu

@@ -225,7 +225,7 @@ inline __device__ __host__ real_number Wab(real_number r)
 	if (r < 1.0)
 		return (1.0 - 3.0/2.0*r*r + 3.0/4.0*r*r*r)*a2;
 	else if (r < 2.0)
-		return (1.0/4.0*(2.0 - r*r)*(2.0 - r*r)*(2.0 - r*r))*a2;
+		return (1.0/4.0*(2.0 - r)*(2.0 - r)*(2.0 - r))*a2;
 	else
 		return 0.0;
 }
@@ -1101,7 +1101,7 @@ int main(int argc, char* argv[])
 
 	openfpm_finalize();
 }
- 
+
 #else
 
 int main(int argc, char* argv[])

example/Vector/7_SPH_dlb_gpu_opt/main.cu

@@ -215,7 +215,7 @@ inline __device__ __host__ real_number Wab(real_number r)
 	if (r < 1.0)
 		return (1.0 - 3.0/2.0*r*r + 3.0/4.0*r*r*r)*a2;
 	else if (r < 2.0)
-		return (1.0/4.0*(2.0 - r*r)*(2.0 - r*r)*(2.0 - r*r))*a2;
+		return (1.0/4.0*(2.0 - r)*(2.0 - r)*(2.0 - r))*a2;
 	else
 		return 0.0;
 }
@@ -681,7 +681,6 @@ inline void sensor_pressure(Vector & vd,
 			CUDA_LAUNCH_DIM3(sensor_pressure_gpu,1,1,vd.toKernel(),NN.toKernel(),probe,(real_number *)press_tmp_.toKernel());
 
 			vd.template restoreOrder<>(NN);
-
 			// move calculated pressure on
 			press_tmp_.deviceToHost();
 			press_tmp = *(real_number *)press_tmp_.getPointer();
@@ -998,7 +997,7 @@ int main(int argc, char* argv[])
 
 	openfpm_finalize();
 }
- 
+
 #else
 
 int main(int argc, char* argv[])

example/Vector/7_SPH_dlb_opt/main.cpp

@@ -383,11 +383,11 @@ inline double Wab(double r)
 	r /= H;
 
 	if (r < 1.0)
-	{return (1.0 - 3.0/2.0*r*r + 3.0/4.0*r*r*r)*a2;}
+	   return (1.0 - 3.0/2.0*r*r + 3.0/4.0*r*r*r)*a2;
 	else if (r < 2.0)
-	{return (1.0/4.0*(2.0 - r*r)*(2.0 - r*r)*(2.0 - r*r))*a2;}
+		return (1.0/4.0*(2.0 - r)*(2.0 - r)*(2.0 - r))*a2;
 	else
-	{return 0.0;}
+	   return 0.0;
 }
 
 const double c1 = -3.0/M_PI/H/H/H/H;
@@ -881,7 +881,7 @@ int main(int argc, char* argv[])
 	// extended boundary around the domain, and the processor domain
     // by the support of the cubic kernel
 	Ghost<3,double> g(r_gskin);
-	
+
     /*! \cond [skin_calc] \endcond */
 
 	// Eliminating the lower part of the ghost
@@ -1141,4 +1141,3 @@ int main(int argc, char* argv[])
 
 	openfpm_finalize();
 }
-