Why different sums for these two functions for large sets of data?

Discussion in 'C++' started by Eric Lilja, May 24, 2005.

  1. Eric Lilja

    Eric Lilja Guest

    Hello, consider the following two functions:

    /* function foo() */
    void foo()
    float y = 0.0f;
    float sum = 0.0f;

    for(int i = 0; i < num; ++i)
    for(int j = 0; j < num; ++j)
    const float& x = myDataX;

    y = myDataY[j];

    sum += x + y;

    std::cout << "sum = " << sum << std::endl;

    /* function bar() */
    void bar()
    float sum = 0.0f;
    float y_sum = 0.0f;

    for(int y = 0; y < num; ++y)
    y_sum += myDataY[y];

    for(int x = 0; x < num; ++x)
    float x_times_num = myDataX[x] * num;

    float value = (x_times_num + y_sum);
    sum += value;

    std::cout << "sum = " << sum << std::endl;

    If myDataX and myDataY are small arrays, both functions produce the correct
    sum and bar() seems to be a bit faster (I removed code for timing when
    posting). But for large sets of data, bar() produces a too large sum but is
    very much faster. Why? Where's the bug in bar()? I have a feeling it has to
    do with the fact that I'm using floats and floats don't always behave as one
    might expect unless you understand in detail how they're represented
    internally. I want to fix bar() so it produces the correct sum for large
    data sets, and, hopefully still doing it faster than foo(). I am compiling
    with debug info and will all optimizations disabled.

    If you see any bugs, have suggestions on how to improve the speed of my
    functions, please reply. I need to calculate the sum calculated by foo() and
    bar() as fast as possible.

    Example data set that works for both:
    const int num = 4;
    myDataX = new float[num];
    myDataY = new float[num];
    myDataX[0] = 1;
    myDataX[1] = 2;
    myDataX[2] = 3;
    myDataX[3] = 4;

    myDataY[0] = 5;
    myDataY[1] = 6;
    myDataY[2] = 7;
    myDataY[3] = 8;

    Example data set (large) where bar() produces an incorrect sum:
    const int num = 20000;
    myDataX = new float[num];
    myDataY = new float[num];

    std::fill(myDataX, &myDataX[num-1], 0.1f);
    std::fill(myDataY, &myDataY[num-1], 0.1f);

    These variables are static globals in my test program.

    Thanks for any replies

    / E
    Eric Lilja, May 24, 2005
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  2. Eric Lilja

    Howard Guest

    Is that correct? I get totally bogus results when trying to run this code.
    Try setting num to 4 for this case, and see what I mean. What do you get?
    I get large negative values from both. I think the fill statement isn't
    right. (Although I don't know how to fix it, since I've never used
    std::fill with an array.)

    A few suggestions:

    1) why not use a vector, instead of an array?
    2) why not use double instead of float, (since it has better precision,
    which will help in any large summing of float values)?
    3) isn't that formula equal to just: num times (the sum of the Xs plus the
    sum of the Ys)?

    Howard, May 24, 2005
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  3. Are you sure you've got this the right way around ? Your code looks very
    inefficient. If you're trying to compute the sum

    Sum(i=0..num-1,j=0..num-1) (x_i + y_j)

    then you're doing this very inefficiently. Note that this sum exands as

    Sum(i,j) x_i + Sum(i,j) y_j

    Now because x_i is independent of j, and x_j is independent of x_i, you can
    collapse a subscript of each sum, and get:

    size * (Sum(i) x_i +sum(j) x_j)


    The resulting code looks like this:

    float bar ( float*x, float* y, int size )
    double sumx = 0, sumy = 0;
    for (int i = 0; i < size; ++i)
    sumx += *x++;
    sumy += *y++;
    return size*(sumx + sumy);

    or alternatively, as an STL one liner:
    float bar ( float*x, float* y, int size )
    return size * (std::accumulate(x,x+size,0.f) +

    This should be (and is, according to my test with your data) more accurate
    than your foo() because it only performs 2*(size)+1 floating point additions,
    and one multiplication, compared to yours : 2*size*size floating point
    additions. When I ran the test (with my version of bar), I got these results:
    foo: 4.1943e+06
    bar: 8e+07

    even with only 200 elements in the array, I get:
    foo: 8003.11
    bar: 8000

    Donovan Rebbechi, May 24, 2005
  4. Eric Lilja

    Eric Lilja Guest

    Hi Donovan and thanks for your reply (see below),

    [my OP snipped]
    I tried that version and compared it with the original version that I was
    given (that I've been trying to improve upon and that I didn't show in my
    OP). Here's a complete program with output for the two varaints. As you can
    see the results are equal for the small data set but way off for the large
    data set:

    #include <algorithm>
    #include <cstddef>
    #include <cstring>
    #include <iomanip>
    #include <iostream>

    static double
    un_optimized(const float *myDataX, const float *myDataY,
    std::size_t num)
    unsigned int i, j;
    float sum = 0;

    for( i = 0; i < num; i++ )
    for( j = 0; j < num; j++ )
    float x = myDataX;
    float y = myDataY[j];
    float value = x+y;

    return sum;

    static double
    optimized(const float *myDataX, const float *myDataY, std::size_t num)
    double sumx = 0, sumy = 0;

    for(unsigned int i = 0; i < num; ++i)
    sumx += *myDataX++;
    sumy += *myDataY++;

    return (num*(sumx + sumy));

    std::size_t num = 20000;
    float *myDataX = new float[num];
    float *myDataY = new float[num];

    std::fill(myDataX, &myDataX[num], 0.1f);
    std::fill(myDataY, &myDataY[num], 0.1f);
    //std::memset(myDataX, 1, num);
    //std::memset(myDataY, 1, num);

    std::cout << std::fixed << std::showpoint << std::setprecision(8);

    std::cout << "sum for un_optimized(): "
    << un_optimized(myDataX, myDataY, num) << std::endl;
    std::cout << "sum for optmized(): "
    << optimized(myDataX, myDataY, num) << std::endl;

    delete [] myDataX;
    delete [] myDataY;

    num = 4;
    float myDataX2[] = {1,2,3,4};
    float myDataY2[] = {5,6,7,8};

    std::cout << "sum for un_optimized(): "
    << un_optimized(myDataX2, myDataY2, num) << std::endl;
    std::cout << "sum for optmized(): "
    << optimized(myDataX2, myDataY2, num) << std::endl;

    return 0;

    sum for un_optimized(): 4194304.00000000
    sum for optmized(): 80000001.19209290
    sum for un_optimized(): 144.00000000
    sum for optmized(): 144.00000000

    Any comments??
    / Eric
    Eric Lilja, May 24, 2005
  5. Eric Lilja

    Shezan Baig Guest

    How about just:

    static double optimized(const float *myDataX,
    const float *myDataY,
    std::size_t num)
    float x = *myDataX, y = *myDataY;
    return num * num * x * y;

    (Since you are relying on the fact that all elements in each array
    contain the same value, you don't even need the loop).

    Hope this helps,
    Shezan Baig, May 24, 2005

  6. That should be:

    std::fill(myDataX, myDataX + num, 0.1f);
    std::fill(myDataY, myDataY + num, 0.1f);

    The 2nd arg needs to be an 'end()' iterator,
    i.e. 'one past the end'.

    Larry I Smith, May 24, 2005
  7. Eric Lilja wrote:

    Oops, the above MUST be 'double sum = 0;'
    Otherwise it will overflow for large values of 'num'.


    Change 'sum' to 'double' in un_optimized() (see my comments above)
    then this program outputs:

    sum for un_optimized(): 80000001.19209290
    sum for optmized(): 80000001.19209290
    sum for un_optimized(): 144.00000000
    sum for optmized(): 144.00000000

    Larry I Smith, May 24, 2005

  8. floats usually have a precision of 6-7 digits. When your result becomes
    larger than that compared to the values that you are adding, you loose the
    values. This is a bigger problem in foo() because you only add x+y in each
    loop. In bar() you add num*x+num*y in each loop, which is a larger value.
    If you use double instead you will have around 15 digits precision and that
    will solve the problem in both functions.

    Niels Dybdahl
    Niels Dybdahl, May 25, 2005
  9. Until you know what you do and are willing and have the knowledge
    to fight that beast:
    * avoid 'float'
    * and use 'double' instead.
    Karl Heinz Buchegger, May 25, 2005
  10. Eric Lilja

    Old Wolf Guest

    This is a bizarre way to write that algorithm, consider:

    for(int i = 0; i < num; ++i)
    for(int j = 0; j < num; ++j)
    sum += myDataX + myDataY[j];
    What makes you so sure that foo() is right and bar() is wrong?

    Every floating point operation incurs a small precision error,
    and foo does many many more operations than bar, so my guess
    would be that bar's result is more correct.
    1. Use the simpler version everyone's already suggested
    2. Use 'double' for your intermediate results. That will probably
    be faster than using 'float' , as an added bonus.
    3. In your compiler, turn on 'fast floating point' option. This
    will exponentially increase the speed of your program, but
    it may violate ISO C requirements for what to do when precision
    is lost (ie. you may get a slightly different answer, for
    better or worse).

    Why is 'double' maybe faster ? Many CPUs have builtin instructions
    for arithmetic in 'double', and when you store the result in a
    float, it has to perform a truncation operation (and if it has to
    conform to ISO C, an even slower truncation operation).
    Those fills are wrong, you are not filling the last member.
    As well as the option suggested by Larry, consider this one:

    std::fill_n(myDataX, num, 0.1f);

    An even better option would be to use RAII:

    std::vector<float> myDataX(num, 0.1f);

    The correct answer to this calculation is 20000 *
    (20000 * (0.1 + 0.1)) ie 80000000.
    So it looks like bar() is indeed giving the more accurate
    answer than foo().
    Old Wolf, May 26, 2005
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