performance measurements
Each table row shows performance measurements for this Numba program with a particular command-line input value N.
| N | CPU secs | Elapsed secs | Memory KB | Code B | ≈ CPU Load |
|---|---|---|---|---|---|
| 550 | 1.39 | 1.41 | 130,424 | 667 | 21% 13% 15% 17% 14% 18% 99% 14% |
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.
notes
spectral-norm Numba 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 numba import jit
from math import sqrt
from sys import argv
import numpy
@jit
def eval_A(i, j):
ij = i+j
return 1.0 / (ij * (ij + 1) / 2 + i + 1)
@jit(forceobj=True)
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
@jit(forceobj=True)
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
@jit(forceobj=True)
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, 12 Jan 2022 12:00:26 GMT COMMAND LINE: /usr/bin/python3 spectralnorm.numba 550 PROGRAM OUTPUT: 1.274224125