## performance measurements

Each table row shows performance measurements for this Nuitka program with a particular command-line input value N.

N  CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
5500.460.4635,584642  4% 0% 100% 0%
5500.460.4637,412642  4% 2% 100% 0%
5500.450.4727,620642  98% 0% 0% 4%

Read the ↓ make, command line, and program output logs to see how this program was run.

Read spectral-norm benchmark to see what this program should do.

## spectral-norm Nuitka #3 program source code

```# The Computer Language Benchmarks Game
# http://benchmarksgame.alioth.debian.org/
#
# Contributed by Sebastien Loisel
# Fixed by Isaac Gouy
# Sped up by Josh Goldfoot
# Dirtily sped up by Simon Descarpentries
# Used list comprehension by Vadim Zelenin
# 2to3
# Sped up with numpy by @tim_1729

from math      import sqrt
from sys       import argv
import numpy

def eval_A(i, j):
ij = i+j
return 1.0 / (ij * (ij + 1) / 2 + i + 1)

def eval_A_times_u(u):
local_eval_A = eval_A

n = u.shape[0]
# output is n items
iis = numpy.arange(n)
iis = numpy.reshape(iis,(n,1))
j = numpy.arange(n)
j = numpy.tile(j,(n,1)) # j is a matrix. Every row is [ 0, 1, 2, ...]
u_j = numpy.tile(u,(n,1))
output = numpy.sum(local_eval_A(iis,j)*u_j,axis=1)
return output

def eval_At_times_u(u):
local_eval_A = eval_A

n = u.shape[0]
# output is n items
# each item is sum of things in loop
iis = numpy.arange(n)
iis = numpy.reshape(iis,(n,1))
j = numpy.arange(n)
j = numpy.tile(j,(n,1))
u_j = numpy.tile(u,(n,1))
output = numpy.sum(local_eval_A(j,iis)*u_j,axis=1)
return output

def eval_AtA_times_u(u):
return eval_At_times_u(eval_A_times_u(u))

def main():
n = int(argv[1])
u = numpy.ones(n)
local_eval_AtA_times_u = eval_AtA_times_u

for dummy in range(10):
v = local_eval_AtA_times_u(u)
u = local_eval_AtA_times_u(v)

vBv = numpy.sum( u * v )
vv = numpy.sum( v * v )

print("%0.9f" % (numpy.sqrt(vBv/vv)))

if __name__ == "__main__":
main()
```

### make, command-line, and program output logs

```Wed, 11 Mar 2020 19:45:22 GMT

MAKE:
make[1]: Vstupuje se do adresáře „/home/dundee/workspace/benchmarksgame/bencher/tmp/spectralnorm/tmp“
nuitka3 --remove-output spectralnorm.nuitka-3.nuitka
Nuitka:WARNING:Not recursing to 'numpy' (/usr/lib/python3.8/site-packages/numpy), please specify --nofollow-imports (do not warn), --follow-imports (recurse to all), --nofollow-import-to=numpy (ignore it), --follow-import-to=numpy (recurse to it) to change.
cp spectralnorm.nuitka-3.nuitka.bin spectralnorm.nuitka-3.nuitka_run