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Benchmarking Carmack’s fast inverse square root

The fast inverse square root is a clever algorithm that approximates 1/sqrt(x). It became famous when the Quake III source code was made public around 2005. While it was initially attributed to Carmack, he denied having written it. Its origins aren’t completely clear and they can be traced back way before Quake III was launched in 1999.

float fastInvSqrt(float x) {
  float xhalf = 0.5f * x;
  int i = *(int*)&x;         // evil floating point bit level hacking
  i = 0x5f3759df - (i >> 1);  // what the fuck?
  x = *(float*)&i;
  x = x*(1.5f-(xhalf*x*x));
  return x;

Lots of people have written about this hack and explained how it works. There are even mathematics papers that study the magic number 0x5f3759df alone. Many people have also asked if it’s still useful on modern processors. The most common answer is no, that this hack was useful 20+ years ago and that modern-day processors have better and faster ways to approximate the inverse square root.

We’ll put those claims to the test in this post.

How good an approximation is it?

It has been calculated that the fastInvSqrt approximates with a relative error of the order of 0.1%. If we graph it against the computer calculated 1/sqrt(x) value, we will get almost identical curves.

1/sqrt(x) and fast inverse square root plots

Benchmarking program

To evaluate the performance, we will calculate the square root of all positive float values in a loop.

/* profiling.c */
#include <limits.h>
#include <math.h>

float fastInvSqrt(float x);
float invSqrt(float x);

int main(int argc, char *argv[]) {
  float result;
  float (*f)(float);

  if (argc != 2) 
    return 1;

  if (*argv[1] == 'f')
    f = fastInvSqrt;
  else if (*argv[1] == 'i')
    f = invSqrt;
    return 1;
  int i;
  for (i=1; i < INT_MAX; i++) {
    float x = *(float *)&i;
    result = f(x);

  return result;

float fastInvSqrt(float x) {
  float xhalf = 0.5f * x;
  int i = *(int*)&x;        
  i = 0x5f3759df - (i >> 1);  
  x = *(float*)&i;
  x = x*(1.5f-(xhalf*x*x));
  return x;

float invSqrt(float x) {
  return 1/sqrt(x);

A command-line argument, either f or i, will be used to select the fastInvSqrt approximation or a regular 1/sqrt(x) in the loop.

Inspecting the generated assembly code

Let’s check the generated assembly code for both functions: fastInvSqrt and invSqrt. Both of them were generated using the gcc -Og flag, which will be the tested version.

The fastInvSqrt assembly code is almost a direct translation of the C code. We can see there are three multiplication instructions (mulss), which might determine the critical path for this algorithm.

	movaps  %xmm0, %xmm1        # %xmm1 = x
	mulss   .LC0(%rip), %xmm1   # %xmm1 = 0.5f * x
	movd    %xmm0, %eax         # %eax = x (same bytes, but as integer)
	sarl    %eax                # %eax = i >> 1
	movl    $1597463007, %edx   # %edx = 0x5f3759df
	subl    %eax, %edx          # %edx = 0x5f3759df - (i >> 1)
	movd    %edx, %xmm0         # %xmm0 = %edx bytes as float
	mulss   %xmm0, %xmm1        # %xmm1 = xhalf * x
	mulss   %xmm0, %xmm1        # %xmm1 = xhalf * x * x
	movss   .LC1(%rip), %xmm2   # %xmm2 = 1.5f
	subss   %xmm1, %xmm2        # %xmm2 = 1.5f - (xhalf*x*x)
	mulss   %xmm2, %xmm0        # %xmm0 = x*(1.5f-(xhalf*x*x))
	ret                         # return %xmm0
	.long   1056964608          # 0x3f000000 (0.5f)
	.align 4
	.long   1069547520          # 0x3fc00000 (1.5f)

The simple 1/sqrt(x) C statement is translated into several assembly instructions. We can see that even though we’re operating on afloat datatype, the machine converts it to double and then back to float to generate the results. Besides the sqrt function call, which we will leave as a black-box, there’s a division instruction (divsd), which might be the limiting step to calculate the inverse square root.

	cvtss2sd  %xmm0, %xmm0        # xmm0 = (double) x
	call      sqrt@PLT            # xmm0 = sqrt (x)
	movsd     .LC0(%rip), %xmm1   # %xmm1 = 1 (0x3ff0000000000000)
	divsd     %xmm0, %xmm1        # %xmm1 = 1 / sqrt(x)
	pxor      %xmm0, %xmm0        # %xmm0 = 0
	cvtsd2ss  %xmm1, %xmm0        # %xmm0 = (float) %xmm1
	ret                           # return %xmm0
	.long     0                   # 0x00000000
	.long     1072693248          # 0x3ff00000

Benchmarking results

The profiling program was compiled as:

$ gcc -Og -o main profiling.c -lm

The performance was evaluated using perf_events. An Intel Core i5 2500K was used for the tests.

First, the fast inverse square root approximation:

$ perf stat ./main f

 Performance counter stats for './main f':

          6.217,04 msec task-clock                #    0,997 CPUs utilized          
               996      context-switches          #    0,160 K/sec                  
                 0      cpu-migrations            #    0,000 K/sec                  
                60      page-faults               #    0,010 K/sec                  
    22.497.523.463      cycles                    #    3,619 GHz                    
     5.831.547.158      stalled-cycles-frontend   #   25,92% frontend cycles idle   
     3.229.721.280      stalled-cycles-backend    #   14,36% backend cycles idle    
    40.828.928.629      instructions              #    1,81  insn per cycle         
                                                  #    0,14  stalled cycles per insn
     6.448.514.878      branches                  # 1037,233 M/sec                  
           263.848      branch-misses             #    0,00% of all branches        

       6,235267619 seconds time elapsed

       6,198586000 seconds user
       0,019982000 seconds sys

It took about 6 seconds. The low percentage of stalled cycles (25%) and the instructions per cycle rate greater than one (1.81), indicate that the processor was able to pipeline the instructions without too much blocking.

Next, the regular 1/sqrt(x) calculation.

 perf stat ./main i

 Performance counter stats for './main i':

         26.463,06 msec task-clock                #    0,997 CPUs utilized          
             4.256      context-switches          #    0,161 K/sec                  
                 0      cpu-migrations            #    0,000 K/sec                  
                60      page-faults               #    0,002 K/sec                  
    96.271.576.226      cycles                    #    3,638 GHz                    
    78.085.953.636      stalled-cycles-frontend   #   81,11% frontend cycles idle   
    59.599.245.094      stalled-cycles-backend    #   61,91% backend cycles idle    
    53.797.950.617      instructions              #    0,56  insn per cycle         
                                                  #    1,45  stalled cycles per insn      branches                  #  650,157 M/sec                  
         1.089.687      branch-misses             #    0,01% of all branches        

      26,538942054 seconds time elapsed

      26,404007000 seconds user
       0,063980000 seconds sys

Close to 26 seconds. We have more instructions, but the greatest problem is the high percentage of stalled cycles. The low instructions per cycle rate (0.56) also indicates poor performance. In this case, the processor is blocked by costly operations, maybe the division instruction.

Surprisingly, the 20+ years old fast inverse square root approximation was able to outperform a regular 1/sqrt(x) calculation by a factor of 4x.

Should we still use the fast inverse square root?

While the results above might indicate that we could, the tests were not fair. The fast inverse square root algorithm returns an approximate result. On the other hand, 1/sqrt(x) is exact to the extent of floats precision.

In order to correct this fault, we’ll compare the fastInvSqrt approximation with another approximation, the rsqrtss instruction of modern processors.

[rsqrtss] Computes an approximate reciprocal of the square root of the low single-precision floating-point value in the source operand.

The relative error for this approximation is:
|Relative Error| ≤ 1.5 ∗ 2^−12

Intel® 64 and IA-32 architectures software developer’s manual

We have a relative error of the order of 0.01%. Even more precise than fastInvSqrt‘s 0.1%.

The following program will be used to test it.

/* invSqrt_rsqrt.c */
#include <limits.h>

float rsqrt(float x);

int main() {
  float result;
  for (int i = 1; i < INT_MAX; i++) {
    float x = *(float *)&i;
    result = rsqrt(x);

  return result;

The rsqrt function was written in assembly (to be included in the C program):

# file rsqrt.s 
        .globl  rsqrt
rsqrt:                          # float rsqrt(float x) 
        pxor    %xmm1, %xmm1    # set %xmm1 to 0
        movss   %xmm0, %xmm1    # %xmm1 = x
        rsqrtss %xmm1, %xmm0    # %xmm0 1/sqrt(x) approximation
        ret                     # return %xmm0

An executable was generated like so:

$ gcc -Og -o main_rsqrt invSqrt_rsqrt.c rsqrt.s

And, finally, the performance results:

 $ perf stat ./main_rsqrt 

 Performance counter stats for './main_rsqrt':

          4.213,01 msec task-clock                #    0,999 CPUs utilized          
               402      context-switches          #    0,095 K/sec                  
                 0      cpu-migrations            #    0,000 K/sec                  
                47      page-faults               #    0,011 K/sec                   cycles                    #    3,578 GHz                    
     6.476.764.013      stalled-cycles-frontend   #   42,97% frontend cycles idle   
        31.495.391      stalled-cycles-backend    #    0,21% backend cycles idle    
    21.483.118.113      instructions              #    1,43  insn per cycle         
                                                  #    0,30  stalled cycles per insn
     8.591.579.921      branches                  # 2039,297 M/sec                  
            46.127      branch-misses             #    0,00% of all branches        

       4,216290125 seconds time elapsed

       4,213955000 seconds user
       0,000000000 seconds sys

It took about 4 seconds. While the percentage of stalled cycles was a bit high (42%), the number of instructions was halved. Overall, it runs 30% faster than fastInvSqrt!

While this is already an improvement over the original approximation, we could get even faster results using SIMD instructions. The VRSQRTPS instruction, for example, can calculate the approximate of 1/sqrt(x) of 8 float values at a time. If it’s as fast as thersqrtss instruction, that would make it 10x faster than the original fastInvSqrt approximation.

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