reduce.cpp

class Reduce_Vectors
{
public:
	Reduce_Vectors(int size);
	~Reduce_Vectors();

	void init(void);
	void sum_scale_x(double scalar, feature_node *x);
	void reduce_sum(double* v);

private:
	int nr_thread;
	int size;
	double **tmp_array;
};

Reduce_Vectors::Reduce_Vectors(int size)
{
	nr_thread = omp_get_max_threads();
	this->size = size;
	tmp_array = new double*[nr_thread];
	for(int i = 0; i < nr_thread; i++)
		tmp_array[i] = new double[size];
}

Reduce_Vectors::~Reduce_Vectors(void)
{
	for(int i = 0; i < nr_thread; i++)
		delete[] tmp_array[i];
	delete[] tmp_array;
}

void Reduce_Vectors::init(void)
{
#pragma omp parallel for schedule(static)
	for(int i = 0; i < size; i++)
		for(int j = 0; j < nr_thread; j++)
			tmp_array[j][i] = 0.0;
}

void Reduce_Vectors::sum_scale_x(double scalar, feature_node *x)
{
	int thread_id = omp_get_thread_num();

	sparse_operator::axpy(scalar, x, tmp_array[thread_id]);
}

void Reduce_Vectors::reduce_sum(double* v)
{
#pragma omp parallel for schedule(static)
	for(int i = 0; i < size; i++)
	{
		v[i] = 0;
		for(int j = 0; j < nr_thread; j++)
			v[i] += tmp_array[j][i];
	}
}