Benchmark
Time (sec)
Speed
Unpack a 1 million element 1-dimensional array and save it to memory as 64-bit real numbers:
CImage:Set(table) where table has 1 million elements.
0.0791
12.7 million elements / sec
Unpack a 250,000 element 1-dimensional array and save it to memory as 64-bit real numbers:
CImage:Set(table) using 250,000 elements.
0.0181
13.8 million elements / sec
Unpack a 10,000 element 1-dimensional array and save it to memory as 64-bit real numbers:
CImage:Set(table) using 10,000 elements.
0.000766
13.1 million elements / sec
Store 1 million table elements:
t={}
for k=1,1000000 do
t[k]=k
end
0.220
4.54 million elements / sec
Store 10 million table elements in a global table:
t={}
for k=1,10000000 do
t[k]=k
end
2.53
3.95 million elements / sec
Perform 10 million multiply operations using local values:
local n=0
local m=0
for i=1,10000000 do
k=n*m
end
0.314
31.9 million multiply's / sec
Perform 10 million divides using local values:
local n=0
local m=15
for i=1,10000000 do
k=n/m
end
0.323
31.0 million divides's / sec
Perform 10 million adds using local values:
local m=0
local n=0
for i=1,10000000 do
k=n+m
end
0.316
31.6 million adds / sec
Perform 10 million adds using global values:
n=0
m=0
for i = 1,10000000 do
k=n+m
end
0.898
11.1 million adds / sec
Perform 10 million adds to a number using global values:
k=0
for i=1,10000000 do
k=k+1
end
0.809
12.4 million adds / sec
Perform 10 million empty loops:
k=0
for k=1,100000000 do
end
0.177
56.5 million loops / sec
Perform 10 million divides and save in a local table:
local t={}
local m=3
for i=1,10000000 do
t[k]=k/m
end
1.46
6.85 million / sec
Least squares solution of 100 points with 4 parameters and 3 variables using a "hyperplane" basis function declared in the script
0.042
24 fits / sec
Least squares solution of 100 points with 4 parameters and 3 variables using internal "hyperplane" basis function
0.000556
1,800 fits / sec
Least squares solution of 10 points with 4 parameters and 3 variables using internal "hyperplane" basis function
0.000055
18,000 fits / sec
Least squares solution of 1000 points using a 3x2 (6 parameter) 2-D polynomial.
0.0008
1,250 fits / sec
Least squares solution using CLsqFit class to fit 10 points with a 3x2 (6 parameter) 2-D polynomial.
0.000041
24,400 fits / sec
Least squares solution using CLsqFit class to fit 1000 points with a 6-th order 1-D polynomial.
0.0011
900 fits /sec
Create 1 million uniformly distributed randomillion numbers.
0.243
4.1 million numbers / sec
Create 1 million Gaussian distributed randomillion numbers
1.16
862,000 numbers / sec
Histogramillion of 1 million real numbers using 100 bins
0.167
6 million numbers / sec
Add two 1200x800 64-bit real images
0.00425
236 images / sec
Add two 1200x800 32-bit real images
0.00198
500 images / sec
Add two 1200x800 16-bit integer images
0.00142
704 images / sec
Add two 1200x800 24-bit RGB images
0.00414
242 images / sec
Add two 1200x960 48-bit URGB images
0.00444
225 images / sec
Multiply 1200x800 32-bit real images
0.0033
300 images / sec
Multiply 1200x800 32-bit real image by a number
0.00475
210 images / sec
Divide two 1200x800 32-bit real images
0.0094
106 images sec
The following sequence of arithmetic operations is executed:
Create a table of CImage objects, as Im
= {}
Im[1] = create 16-bit image of size
1200x800
Im[1] = convert to 32-bit real pixel
data
Im[2] = Im[1] + 1000
Im[3] = Im[1] / Im[2]
Im[4] = Im[1] ^ Im[3]
All 4 images have 32-bit real pixel type. This process involves creation of four 4MB images plus the operations applied to them. The last operation, an exponentiation, is the most numerically intensive computation.
0.097
10.3 million pixels / sec
Apply the sequence of operations in the previous example but also display all four images in a new image window. This requires computing the image histogram, transfer function, and palette mapping for each image.
0.369
Load a 1 megapixel 16-bit image from a hard drive, compute the image histogram, autoscale the transfer function using gamma=0.6, and display in a new window.
0.125
8 images / sec