Understanding OpenMP Reduction

Oct 13, 2025 by miodeya.com 110 views

Introduction

The OpenMP (Open Multi-Processing) API is a widely used standard for parallel programming on shared-memory architectures. One of its key features is the declare reduction clause, which allows developers to specify how to combine values from different threads during parallel execution. However, when using this clause, a common error occurs when the initializer refers to a variable that is not 'omp_priv' nor 'omp_orig'. In this article, we will delve into the details of this issue and provide a comprehensive solution.

Understanding OpenMP Reduction

Before we dive into the specifics of the error, let's briefly review how OpenMP reduction works. When using the declare reduction clause, you specify a reduction operation that combines values from different threads. The reduction operation is typically a binary operation, such as addition or multiplication, that takes two values as input and produces a single output value.

The declare reduction clause consists of three main parts:

Initializer: This is the initial value of the reduction variable.
Binary operation: This is the operation that combines two values to produce a single output value.
Combiner: This is the function that combines the output value from the binary operation with the current value of the reduction variable.

The Error: Initializer Refers to Variable Which is Not 'omp_priv' nor 'omp_orig'

When using the declare reduction clause, the initializer must refer to a variable that is either 'omp_priv' or 'omp_orig'. 'omp_priv' is a special variable that is private to each thread, while 'omp_orig' is the original value of the reduction variable.

However, if the initializer refers to a variable that is not 'omp_priv' nor 'omp_orig', the compiler will raise an error. This error can be frustrating, especially when you're not sure what's causing it.

Example Code

To illustrate this issue, let's consider the following example code:

double* max_of_two(double *r,double *n);
int npoints = 1000000;
double* xy = (double*)malloc(2npointssizeof(double));
double zero_coord[2] = {0.0,0.0};
double *max_val = zero_coord;
#pragma omp declare reduction (max : double : omp_priv(double)) 

initializer(omp_priv(max_val[0])) 

omp_out(omp_priv(max_val[0])) 

omp_in1(omp_priv(max_val[1]))
#pragma omp parallel for
for (int i = 0; i < npoints; i++) {
max_of_two(&max_val[0], &xy[2*i]);
}
#pragma omp declare reduction (max : double : omp_priv(double)) 

initializer(omp_priv(max_val[0])) 

omp_out(omp_priv(max_val[0])) 

omp_in1(omp_priv(max_val[1]))
#pragma omp parallel for
for (int i = 0; i < npoints; i++) {
max_of_two(&max_val[0], &xy[2*i]);
}

In this example, we're trying to use the declare reduction clause to combine the maximum values from different threads. However, the initializer refers to the max_val variable, which is not 'omp_priv' nor 'omp_orig'. This will raise an error at compile-time.

Solution

To fix this issue, we need to modify the initializer to refer to either 'omp_priv' or 'omp_orig'. Here's the corrected code:

double* max_of_two(double *r,double *n);
int npoints = 1000000;
double* xy = (double*)malloc(2npointssizeof(double));
double zero_coord[2] = {0.0,0.0};
double *max_val = zero_coord;
#pragma omp declare reduction (max : double : omp_priv(double)) 

initializer(omp_priv(0.0)) 

omp_out(omp_priv(max_val[0])) 

omp_in1(omp_priv(max_val[1]))
#pragma omp parallel for
for (int i = 0; i < npoints; i++) {
max_of_two(&max_val[0], &xy[2*i]);
}
#pragma omp declare reduction (max : double : omp_priv(double)) 

initializer(omp_priv(0.0)) 

omp_out(omp_priv(max_val[0])) 

omp_in1(omp_priv(max_val[1]))
#pragma omp parallel for
for (int i = 0; i < npoints; i++) {
max_of_two(&max_val[0], &xy[2*i]);
}

In this corrected version, we've modified the initializer to refer to the value 0.0, which is a valid initializer for the reduction variable.

Conclusion

In conclusion, the error "initializer refers to variable which is not 'omp_priv' nor 'omp_orig'" is a common issue when using the declare reduction clause in OpenMP. To fix this issue, we need to modify the initializer to refer to either 'omp_priv' or 'omp_orig'. By following the solution outlined in this article, you should be able to resolve this error and successfully compile your OpenMP code.

Best Practices

To avoid this issue in the future, follow these best practices:

Always check the documentation for the declare reduction clause to ensure you're using it correctly.
Use the omp_priv and omp_orig variables as initializers whenever possible.
Avoid using variables that are not 'omp_priv' nor 'omp_orig' as initializers.
Use the omp_out and omp_in1 clauses to specify the reduction operation and combiner function.

Introduction

In our previous article, we discussed the issue of the initializer referring to a variable that is not 'omp_priv' nor 'omp_orig' when using the declare reduction clause in OpenMP. In this article, we'll provide a Q&A section to help you better understand this issue and how to resolve it.

Q: What is the purpose of the `declare reduction` clause in OpenMP?

A: The declare reduction clause is used to specify how to combine values from different threads during parallel execution. It allows you to define a reduction operation that takes two values as input and produces a single output value.

Q: What is the difference between 'omp_priv' and 'omp_orig' variables?

A: 'omp_priv' is a special variable that is private to each thread, while 'omp_orig' is the original value of the reduction variable. When using the declare reduction clause, the initializer must refer to either 'omp_priv' or 'omp_orig'.

Q: What is the error "initializer refers to variable which is not 'omp_priv' nor 'omp_orig'"?

A: This error occurs when the initializer in the declare reduction clause refers to a variable that is not 'omp_priv' nor 'omp_orig'. This can cause the compiler to raise an error.

Q: How do I fix the error "initializer refers to variable which is not 'omp_priv' nor 'omp_orig'"?

A: To fix this issue, you need to modify the initializer to refer to either 'omp_priv' or 'omp_orig'. You can do this by changing the initializer to use the omp_priv or omp_orig variable.

Q: What are some best practices to avoid this issue in the future?

A: To avoid this issue in the future, follow these best practices:

Always check the documentation for the declare reduction clause to ensure you're using it correctly.
Use the omp_priv and omp_orig variables as initializers whenever possible.
Avoid using variables that are not 'omp_priv' nor 'omp_orig' as initializers.
Use the omp_out and omp_in1 clauses to specify the reduction operation and combiner function.

Q: Can you provide an example of how to use the `declare reduction` clause correctly?

A: Here's an example of how to use the declare reduction clause correctly:

double* max_of_two(double *r,double *n);
int npoints = 1000000;
double* xy = (double*)malloc(2npointssizeof(double));
double zero_coord[2] = {0.0,0.0};
double *max_val = zero_coord;
#pragma omp declare reduction (max : double : omp_priv(double)) 

initializer(omp_priv(0.0)) 

omp_out(omp_priv(max_val[0])) 

omp_in1(omp_priv(max_val[1]))
#pragma omp parallel for
for (int i = 0; i < npoints; i++) {
max_of_two(&max_val[0], &xy[2*i]);
}
#pragma omp declare reduction (max : double : omp_priv(double)) 

initializer(omp_priv(0.0)) 

omp_out(omp_priv(max_val[0])) 

omp_in1(omp_priv(max_val[1]))
#pragma omp parallel for
for (int i = 0; i < npoints; i++) {
max_of_two(&max_val[0], &xy[2*i]);
}

In this example, we've modified the initializer to refer to the omp_priv variable, which is a valid initializer for the reduction variable.

Conclusion

In conclusion, the error "initializer refers to variable which is not 'omp_priv' nor 'omp_orig'" is a common issue when using the declare reduction clause in OpenMP. By following the best practices outlined in this article and using the declare reduction clause correctly, you can avoid this issue and write efficient and effective OpenMP code.