1. Loop Optimization “Programs spend 90% of time in loops”
Loop optimizations well studied
“simple” optimizations
“loop mangeling”

2. Loop Invariant Code Motion
Identify code that computes same value during each iteration
Move loop invariant code to above loop
“Standard” optimization in most compilers

3. Loop Invariant Example
for (i = 0; i < N; i++)
for(j=0; j < N; j++) {
c[i][j] = 0;
for(k=0; k < N; k++)
c[i][j] += a[i][k] * b[k][j]; }

4. Example (cont.) “Assembler” for Innermost (k) loop t2 = t1 + j
L1: t1 = i * N
t2 = t1 + j
t3 = t2 * 4
t4 = &c + t3
t12 = t1 + k
t13 = t12 * 4
t14 = &a + t13
t21 = k * N
t22 = t21 + j
t23 = t22 * 4
t24 = &b + t23
t31 = *t14 * *t24
*t4 = *t4 + t31
k = k + 1
if( k < N) goto L1
“Assembler” for Innermost (k) loop

5. Example (cont.) t1 = i * N t2 = t1 + j t3 = t2 * 4 t4 = &c + t3
L1: t12 = t1 + k
t13 = t12 * 4
t14 = &a + t13
t21 = k * N
t22 = t21 + j
t23 = t22 * 4
t24 = &b + t23
t31 = *t14 * *t24
*t4 = *t4 + t31
k = k + 1
if( k < N) goto L1

6. Induction Variables Changes by constant amount per iteration
Often used in array address computation
Simplification of induction variables
Strength reduction --- convert * to +

7. Example (cont.) t1 = i * N t2 = t1 + j t3 = t2 * 4 t4 = &c + t3
t14 = &a
t24 = &b
t32 = N * 4
t33 = t32 + &a
L1: t31 = *t14 * *t24
*t4 = *t4 + t31
t14 = t14 + 4
t24 = t24 + t32
if(t14 < t33) goto L1

8. Loop Transformations More sophisticated
Relatively few compilers include them
Loop Interchange – for nested loops
Unroll and Jam – for nested loops
Loop fusion
Loop distribution
Loop unrolling