# function wrappers and calling sequence for accelerated kernel evaluations in R 
# with external C code using CPU and GPU
# Sergey V. 2022

# preload static object file
dyn.load("cuda1R.so") 
printf <- function(...)print(sprintf(...))

# define R functions for cpu and gpu wrappers
kfunc_kernel.cpu <- function(x1, x2, a, b, c, kname)
{
  rst <- .Call("kfunc_kernel_cpu",
    x1,
    x2,
		a,
		b,
		c,
		kname
              )
  return(rst)
}


kfunc_kernel.gpu <- function(x1, x2, a, b, c, kname, devID=0L)
{
  rst <- .Call("kfunc_kernel_gpu",
    x1,
    x2,
		a,
		b,
		c,
		kname,
    as.integer(devID)
              )
  return(rst)
}

printf("Test kfunc_exp\n");
load('xdata1.RData');
x1 = runif(350,min=-5,max=5);
x2 = runif(75, min=-4,max=4);
printf("len(x1) = %d, len(x2) = %d\n", length(x1), length(x2));
S1 = kfunc_kernel.cpu(x1,x2,1,1,1,'exp');
print(dim(S1));
S2 = kfunc_kernel.cpu(x1,x2,1,1,1,'matern');
print(dim(S2));
printf("Test kfunc_exp gpu\n");
S1g = kfunc_kernel.gpu(x1,x2,1,1,1,'exp');
printf("Print cpu/gpu norms\n");
norm(S1)
norm(S1g)