Function main

compute/example/black_scholes.cpp:31–168

this example demostrates a black-scholes option pricing kernel.

// this example demostrates a black-scholes option pricing kernel.
int main()
{
    // number of options
    const int N = 4000000;

    // black-scholes parameters
    const float risk_free_rate = 0.02f;
    const float volatility = 0.30f;

    // get default device and setup context
    compute::device gpu = compute::system::default_device();
    compute::context context(gpu);
    compute::command_queue queue(context, gpu);
    std::cout << "device: " << gpu.name() << std::endl;

    // initialize option data on host
    std::vector<float> stock_price_data(N);
    std::vector<float> option_strike_data(N);
    std::vector<float> option_years_data(N);

    std::srand(5347);
    for(int i = 0; i < N; i++){
        stock_price_data[i] = rand_float(5.0f, 30.0f);
        option_strike_data[i] = rand_float(1.0f, 100.0f);
        option_years_data[i] = rand_float(0.25f, 10.0f);
    }

    // create memory buffers on the device
    compute::vector<float> call_result(N, context);
    compute::vector<float> put_result(N, context);
    compute::vector<float> stock_price(N, context);
    compute::vector<float> option_strike(N, context);
    compute::vector<float> option_years(N, context);

    // copy initial values to the device
    compute::copy_n(stock_price_data.begin(), N, stock_price.begin(), queue);
    compute::copy_n(option_strike_data.begin(), N, option_strike.begin(), queue);
    compute::copy_n(option_years_data.begin(), N, option_years.begin(), queue);

    // source code for black-scholes program
    const char source[] = BOOST_COMPUTE_STRINGIZE_SOURCE(
        // approximation of the cumulative normal distribution function
        static float cnd(float d)
        {
            const float A1 =  0.319381530f;
            const float A2 = -0.356563782f;
            const float A3 =  1.781477937f;
            const float A4 = -1.821255978f;
            const float A5 =  1.330274429f;
            const float RSQRT2PI = 0.39894228040143267793994605993438f;

            float K = 1.0f / (1.0f + 0.2316419f * fabs(d));
            float cnd =
                RSQRT2PI * exp(-0.5f * d * d) *
                (K * (A1 + K * (A2 + K * (A3 + K * (A4 + K * A5)))));

            if(d > 0){
                cnd = 1.0f - cnd;