How about more complex functions ?

Instruction set of a CPU

The instructions that a CPU can execute can e divided into 3 categories:

Data movement (= copy)
Arithmetic (+, -, *, %, /), logic (and, or, not, including bitwise operations), shift or rotate instructions
Branching (including call and return)

Take a look at the list of instructions that the popular Intel can execute: click here

How does a computer compute more complex values, like "sin(x)"

Answer:

Use interpolation !!!!
From Mathematics:
(Google "Taylor serie" and "Lagrange interpolation" for more details.)

I found a highly optimized (= very good approximation with very few operations) of the sin(x) function:

Here is the code in C:

#define pi 3.14159265358979l double mySine(double x) { const double B = 4.0/pi; // 2 special "interpolation constants const double C = 4.0/(pi*pi); double y; y = B*x - C*x*x; // Highly optimized (= hokus pokus) y = 0.775*y + 0.225*y*y; // approximation of sin(x) return y; }

Example Program: (Demo above code)

Prog file: click here

How to run the program:

Right click on link and save in a scratch directory
To compile: gcc sin-appr.c -lm
To run: ./a.out

Output:

x = 0.0, sin(x) = 0.000000, mySine(x) = 0.000000, Diff = 0.000000 ( NaN%) x = 0.1, sin(x) = 0.099833, mySine(x) = 0.098954, Diff = 0.000879 (0.88%) x = 0.2, sin(x) = 0.198669, mySine(x) = 0.197580, Diff = 0.001089 (0.55%) x = 0.3, sin(x) = 0.295520, mySine(x) = 0.294617, Diff = 0.000903 (0.31%) x = 0.4, sin(x) = 0.389418, mySine(x) = 0.388895, Diff = 0.000524 (0.13%) x = 0.5, sin(x) = 0.479426, mySine(x) = 0.479329, Diff = 0.000097 (0.02%) x = 0.6, sin(x) = 0.564642, mySine(x) = 0.564926, Diff = -0.000284 (0.05%) x = 0.7, sin(x) = 0.644218, mySine(x) = 0.644781, Diff = -0.000564 (0.09%) x = 0.8, sin(x) = 0.717356, mySine(x) = 0.718077, Diff = -0.000721 (0.10%) x = 0.9, sin(x) = 0.783327, mySine(x) = 0.784086, Diff = -0.000759 (0.10%) x = 1.0, sin(x) = 0.841471, mySine(x) = 0.842168, Diff = -0.000697 (0.08%) x = 1.1, sin(x) = 0.891207, mySine(x) = 0.891773, Diff = -0.000565 (0.06%) x = 1.2, sin(x) = 0.932039, mySine(x) = 0.932438, Diff = -0.000399 (0.04%) x = 1.3, sin(x) = 0.963558, mySine(x) = 0.963792, Diff = -0.000234 (0.02%) x = 1.4, sin(x) = 0.985450, mySine(x) = 0.985549, Diff = -0.000099 (0.01%) x = 1.5, sin(x) = 0.997495, mySine(x) = 0.997513, Diff = -0.000018 (0.00%)

As you know, sin(x) is periodic.

The values compared are between [0..π/2]; which is the main period.

You can always reduce any x value to some value inside this range (and then to obtain the function value).

Doing so little work to get to < 1% error in sin(x) for any value of x is not too shaby !!!!

Experiment

I found this page on a high accurate approximation of sin/cos:

//always wrap input angle to -PI..PI if (x < -3.14159265) x += 6.28318531; else if (x > 3.14159265) x -= 6.28318531; //compute sine if (x < 0) { sin = 1.27323954 * x + .405284735 * x * x; if (sin < 0) sin = .225 * (sin *-sin - sin) + sin; else sin = .225 * (sin * sin - sin) + sin; } else { sin = 1.27323954 * x - 0.405284735 * x * x; if (sin < 0) sin = .225 * (sin *-sin - sin) + sin; else sin = .225 * (sin * sin - sin) + sin; } //compute cosine: sin(x + PI/2) = cos(x) x += 1.57079632; if (x > 3.14159265) x -= 6.28318531; if (x < 0) { cos = 1.27323954 * x + 0.405284735 * x * x; if (cos < 0) cos = .225 * (cos *-cos - cos) + cos; else cos = .225 * (cos * cos - cos) + cos; } else { cos = 1.27323954 * x - 0.405284735 * x * x; if (cos < 0) cos = .225 * (cos *-cos - cos) + cos; else cos = .225 * (cos * cos - cos) + cos; }

The URL: http://lab.polygonal.de/?p=205

Notice you only use arithmetic opertions !!!

Program it and see how accurate it is....