Optimization of C code

Question

For an assignment of a course called High Performance Computing, I required to optimize the following code fragment:

int foobar(int a, int b, int N) {     int i, j, k, x, y;     x = 0;     y = 0;     k = 256;     for (i = 0; i <= N; i++) {         for (j = i + 1; j <= N; j++) {             x = x + 4*(2*i+j)*(i+2*k);             if (i > j){                y = y + 8*(i-j);             }else{                y = y + 8*(j-i);             }         }     }     return x; } 

Using some recommendations, I managed to optimize the code (or at least I think so), such as:

1. Constant Propagation
2. Algebraic Simplification
3. Copy Propagation
4. Common Subexpression Elimination
5. Dead Code Elimination
6. Loop Invariant Removal
7. bitwise shifts instead of multiplication as they are less expensive.

Here's my code:

int foobar(int a, int b, int N) {      int i, j, x, y, t;     x = 0;     y = 0;     for (i = 0; i <= N; i++) {         t = i + 512;         for (j = i + 1; j <= N; j++) {             x = x + ((i<<3) + (j<<2))*t;         }     }     return x; } 

According to my instructor, a well optimized code instructions should have fewer or less costly instructions in assembly language level.And therefore must be run, the instructions in less time than the original code, ie calculations are made with::

execution time = instruction count * cycles per instruction

When I generate assembly code using the command: gcc -o code_opt.s -S foobar.c,

the generated code has many more lines than the original despite having made ​​some optimizations, and run-time is lower, but not as much as in the original code. What am I doing wrong?

Do not paste the assembly code as both are very extensive. So I'm calling the function "foobar" in the main and I am measuring the execution time using the time command in linux

int main () {     int a,b,N;      scanf ("%d %d %d",&a,&b,&N);     printf ("%d\n",foobar (a,b,N));     return 0; } 

Answer 1

Initially:

for (i = 0; i <= N; i++) {     for (j = i + 1; j <= N; j++) {         x = x + 4*(2*i+j)*(i+2*k);         if (i > j){            y = y + 8*(i-j);         }else{            y = y + 8*(j-i);         }     } } 

Removing y calculations:

for (i = 0; i <= N; i++) {     for (j = i + 1; j <= N; j++) {         x = x + 4*(2*i+j)*(i+2*k);     } } 

Splitting i, j, k:

for (i = 0; i <= N; i++) {     for (j = i + 1; j <= N; j++) {         x = x + 8*i*i + 16*i*k ;                // multiple of  1  (no j)         x = x + (4*i + 8*k)*j ;                 // multiple of  j     } } 

Moving them externally (and removing the loop that runs N-i times):

for (i = 0; i <= N; i++) {     x = x + (8*i*i + 16*i*k) * (N-i) ;     x = x + (4*i + 8*k) * ((N*N+N)/2 - (i*i+i)/2) ; } 

Rewritting:

for (i = 0; i <= N; i++) {     x = x +         ( 8*k*(N*N+N)/2 ) ;     x = x +   i   * ( 16*k*N + 4*(N*N+N)/2 + 8*k*(-1/2) ) ;     x = x +  i*i  * ( 8*N + 16*k*(-1) + 4*(-1/2) + 8*k*(-1/2) );     x = x + i*i*i * ( 8*(-1) + 4*(-1/2) ) ; } 

Rewritting - recalculating:

for (i = 0; i <= N; i++) {     x = x + 4*k*(N*N+N) ;                            // multiple of 1     x = x +   i   * ( 16*k*N + 2*(N*N+N) - 4*k ) ;   // multiple of i     x = x +  i*i  * ( 8*N - 20*k - 2 ) ;             // multiple of i^2     x = x + i*i*i * ( -10 ) ;                        // multiple of i^3 } 

Another move to external (and removal of the i loop):

x = x + ( 4*k*(N*N+N) )              * (N+1) ; x = x + ( 16*k*N + 2*(N*N+N) - 4*k ) * ((N*(N+1))/2) ; x = x + ( 8*N - 20*k - 2 )           * ((N*(N+1)*(2*N+1))/6); x = x + (-10)                        * ((N*N*(N+1)*(N+1))/4) ; 

Both the above loop removals use the summation formulas:

Sum(1, i = 0..n) = n+1
Sum(i¹, i = 0..n) = n(n + 1)/2
Sum(i², i = 0..n) = n(n + 1)(2n + 1)/6
Sum(i³, i = 0..n) = n²(n + 1)²/4