Is this code parallelize ?

Accelerated Computing CUDA CUDA Programming and Performance
1

Hello All,

I have a code that is written in C and I want to write it in CUDA. But due to dependency I am not able to write in CUDA. My C code is :

int fun_2( int *i, int *k, int J, int size,  float* Array_1)

{

	int k1 = (*j1), k2 = (*j2);

	while ( Array_1[k1] < J ) 

	{

		k1++;

		(*i) = k1;

		if ( k1 >= size ) 

			return 10;

	}

	k2 = k1 - 1;

	(*k) = k2;

	

	return 0;

}

void fun_1(  float * Array_1,  float * Array_2, int size )

{ 	

	int i =  1; 

	int j = 0;

	int k = 0;

	while ( i < size )	

	{   

		Array_2[j] = ( j - Array_1[k] ) / ( Array_1[i] - Array_1[k]  );

		j++;

		fun_2( &i, &k, j, size, Array_1);

	}

}

If any one has any idea please help.

2

What are *j1 and *j2 in fun_2? What good are the return codes in fun_2 if you don’t check them? You are right there are dependencies.

It might help to explain what this code does, as it may be necessary to change the algorithm.

3

CUDAkk,

PMs to you are bouncing because you have chosen a setting of not to be contactable by the board messenger. Check out.

Here is what I wantd to tell you.

Generally, You cant parallelize code that is cumulative.

For example:

for(int i=1; i<=N; i++)

 a[i] = a[i] + a[i-1];

Things that accumulate across iterations dont lend them for parallel decomposition unless you find an alternate way out.

In your code, I dont know what is “j1” and “j2”.

But it looks like there is some cumulation for “i” and “k”. I am not very sure. I dont understand what is the instance.

A general way of doing this is : you could make a thread correspond to eac value of “j”. So, for each such “j” , you can go around and find the solution – but i am not sure if it will work - espeically if there is cumulation you generally cant