Let’s try this again…

In my first attempt at writing a parallel program with TBB, my speedup was disappointing (about 4%). I guessed that vector multiplication wasn’t computationally intensive enough to make good use of multiple cores. I tried to remedy that by writing a program to find points in a Julia set. The Julia set is just the set of points that don’t shoot off to infinity when they are iterated by the function:

z(n+1) = z(n) * z(n) + c

So the basic technique is to take a candidate point z and repeatedly square it and add a constant (both z and c are complex numbers). If it exceeds a bound within a set number of iterations, then z is probably not a Julia point (this is an approximate test). By varying the bound and the number of iterations, I could easily vary the computational load.

The C++ code for both the parallel and serial versions of my Julia set generator is shown below:

// example2.cpp : Defines the entry point for the console application.
//

#include “stdafx.h”
#include
#include // for complex numbers
#include “tbb/task_scheduler_init.h”
#include “tbb/parallel_for.h”
#include “tbb/blocked_range.h”
#include “tbb/tick_count.h”
using namespace tbb;
using namespace std;

typedef complex JPT;

class julia{
JPT *const z; // pointer to points to test for “Julianess”
const complex c; // complex constant in eq. z_i+1 = (z_i)^2 + c
const unsigned n; // # times to iterate equation
const double b; // Julia point if z_n >= b
bool *is_julia; // put the result here
public:
// constructor copies the arguments into local storage
julia(JPT *arg_z, complex arg_c, int arg_n, double arg_b, bool *arg_is_julia)
: z(arg_z), c(arg_c), n(arg_n), b(arg_b), is_julia(arg_is_julia) { }
// overload () so it finds julia points
void operator() (const blocked_range &r) const {
for(size_t i=r.begin(); i!=r.end(); i++) {
complex zi = z[i]; // store the point to test
is_julia[i] = true; // start off assuming it’s a Julia point
for(unsigned j=0; j= b) {
// Not a Julia point if it exceeds the bound within n iterations
is_julia[i] = false;
break;
}
zi = zi * zi + c; // keep iterating the point and see where it goes
}
}
}
};

const size_t n_pts = 100000; // number of points to test
const JPT z_lo = 0.0; // find Julia points between here…
const JPT z_hi = 1.0; // and here
const complex c_julia(-0.123,0.745); // complex constant for iterations
const unsigned n_iter = 100; // number of iterations for checking bounds
const double bound = 100000; // bound for testing “Julianess” of a point

int _tmain(int argc, _TCHAR* argv[])
{
JPT *z = (JPT*)malloc(n_pts*sizeof(JPT)); // storage for points to test
bool *is_julia = (bool*)malloc(n_pts*sizeof(bool)); // storage for test results
complex c = c_julia;
const unsigned n = n_iter;
const double b = bound;

// initialize vector with evenly-spaced points along a line
JPT spacing = (z_hi – z_lo)/JPT(n_pts-1); // spacing between points
z[0] = z_lo; // initial point
for(size_t i=1; isourcecode for this example if you want to play around with it.

About dave_vandenbout
President of XESS Corp, a manufacturer of FPGA development boards.

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