C: Improving performance of function with heavy sin() usage

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I have a C function that computes the values of 4 sines based on time elapsed. Using gprof, I figured that this function uses 100% (100.7% to be exact lol) of the CPU time.

void
update_sines(void)
{
    clock_gettime(CLOCK_MONOTONIC, &spec);
    s = spec.tv_sec;
    ms = spec.tv_nsec * 0.0000001;
    etime = concatenate((long)s, ms);

    int k;
    for (k = 0; k < 799; ++k)
    {
        double A1 = 145 * sin((RAND1 * k + etime) * 0.00333) + RAND5;           // Amplitude
        double A2 = 100 * sin((RAND2 * k + etime) * 0.00333) + RAND4;           // Amplitude
        double A3 = 168 * sin((RAND3 * k + etime) * 0.00333) + RAND3;           // Amplitude
        double A4 = 136 * sin((RAND4 * k + etime) * 0.00333) + RAND2;           // Amplitude

        double B1 = 3 + RAND1 + (sin((RAND5 * k) * etime) * 0.00216);           // Period
        double B2 = 3 + RAND2 + (sin((RAND4 * k) * etime) * 0.002);         // Period
        double B3 = 3 + RAND3 + (sin((RAND3 * k) * etime) * 0.00245);           // Period
        double B4 = 3 + RAND4 + (sin((RAND2 * k) * etime) * 0.002);         // Period

        double x = k;                                   // Current x

        double C1 = 0.6 * etime;                            // X axis move
        double C2 = 0.9 * etime;                            // X axis move
        double C3 = 1.2 * etime;                            // X axis move
        double C4 = 0.8 * etime + 200;                          // X axis move

        double D1 = RAND1 + sin(RAND1 * x * 0.00166) * 4;               // Y axis move
        double D2 = RAND2 + sin(RAND2 * x * 0.002) * 4;                 // Y axis move
        double D3 = RAND3 + cos(RAND3 * x * 0.0025) * 4;                // Y axis move
        double D4 = RAND4 + sin(RAND4 * x * 0.002) * 4;                 // Y axis move

        sine1[k] = A1 * sin((B1 * x + C1) * 0.0025) + D1;
        sine2[k] = A2 * sin((B2 * x + C2) * 0.00333) + D2 + 100;
        sine3[k] = A3 * cos((B3 * x + C3) * 0.002) + D3 + 50;
        sine4[k] = A4 * sin((B4 * x + C4) * 0.00333) + D4 + 100;
    }

}

And this is the output from gprof:

Flat profile:

Each sample counts as 0.01 seconds.
  %   cumulative   self              self     total           
 time   seconds   seconds    calls  Ts/call  Ts/call  name    
100.07      0.04     0.04  

I'm currently getting a frame rate of roughly 30-31 fps using this. Now I figure there as to be a more efficient way to do this.

As you noticed I already changed all the divisions to multiplications but that had very little effect on performance.

How could I increase the performance of this math heavy function?

5 Answers

Here is a C++ snippet to use the rotation matrix suggested in the accepted answer.

   float a = 0.343;
   float b = 2.3232;
   float sina{};
   float cosa{};
   sincosf(a, &sina, &cosa);
   float resSin{};
   float resCos{};

   for (int k = 0; k < 5; k++) {
     if (k == 0) {
       sincosf(b, &resSin, &resCos);
     } else {
       float newResCos, newResSin;
       newResCos = cosa * resCos - sina * resSin;
       newResSin = sina * resCos + cosa * resSin;
       resCos = newResCos;
       resSin = newResSin;
     }
   }
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