1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136
|
---
author: Willem van Bergen
title: Memory efficiency when using Ruby
---
I have been spending some time creating [a pure Ruby PNG library](https://github.com/wvanbergen/chunky_png). For this library, I need to have some representation of the image, which is composed of RGB pixels, supporting an alpha channel. Because images can be composed of a lot of pixels, I want the implementation to be as memory efficient as possible. I also would like decent performance.
A very naive Ruby implementation for an image represents the red, green, blue and alpha channel using a floating point number between 0.0 and 1.0, and might look something like this:
{% highlight ruby %}
class Pixel
attr_reader :r, :g, :b, :a
def initialize(r, g, b, a = 1.0)
@r, @g, @b, @a = r, g, b, a
end
end
class Image
attr_reader :width, :height
def initialize(width, height)
@width, @height = width, height
@pixels = Array.new(width * height)
end
def [](x,y)
@pixels[y * width + x]
end
def []=(x,y, pixel)
@pixels[y * width + x] = pixel
end
end
{% endhighlight %}
For a 10×10 image, this representation requires 4 times 100 floating point numbers, which require 8 bytes each. That’s already over 3kB for such a small image just for the floating point numbers! Ouch.
A simple improvement is to decide that 8-bit color depth is enough in the case, in which case each channel can be represented by an integer between 0 and 255. Storing such a number only costs one byte of memory. Ruby’s Fixnum class typically uses 4-byte integers. If only the 4 channels of one byte each could be combined into a single Fixnum instance… Behold!
{% highlight ruby %}
class Pixel
attr_reader :value
alias :to_i :value
def initialize(value)
@value = value
end
def self.rgba(r, g, b, a = 255)
self.new(r << 24 | g << 16 | b << 8 | a)
end
def r; (@value & 0xff000000) >> 24; end
def g; (@value & 0x00ff0000) >> 16; end
def b; (@value & 0x0000ff00) >> 8; end
def a; (@value & 0x000000ff); end
end
{% endhighlight %}
Notice the bit operations, which are extremely fast. This only requires 100 times 4 bytes = 400 bytes for storing the RGBA values for a 10×10 image, an 8 times improvement!
This implementation wraps every pixel inside an object. This is nice, because I want to access the separate channels of every pixel easily using the r, g, b, and a methods, and every other method that is defined for every pixel. However, a Ruby object instance has an overhead of at least 20 bytes. That’s 20 times 100 is about 2kB for our 10×10 image!
To get rid of the object overhead, it is possible to simply store the Fixnum value for every pixel, and only wrapping it inside a Pixel object when it is accessed. This can be done by modifying the Image class:
{% highlight ruby %}
class Image
# ...
def [](x,y)
Pixel.new(@pixels[y * width + x]) # wrap
end
def []=(x,y, pixel)
@pixels[y * width + x] = pixel.to_i # unwrap
end
end
{% endhighlight %}
As you can see, some simply changes in the representation can really make a difference in the memory usage. Can this representation be improved further?
## Integer math calculations
Because we are now using integers to represent a pixel, this can cause problems when the math requires you to use floating point numbers. For example, the formula for [alpha composition](https://en.wikipedia.org/wiki/Alpha_compositing) of two pixels is as follows:
\\[ C_o = C_a \alpha_a + C_b \alpha_b (1 - \alpha_a) \\]
in which \\(C_a\\) is the color component of the foreground pixel, \\(\alpha_a\\) the alpha channel of the foreground pixel, \\(C_b\\) and \\(\alpha_b\\) the same values for the background pixel, all of which should be values between 0 and 1.
A naive implementation could convert the integer numbers to their floating point equivalents:
{% highlight ruby %}
def compose(fg, bg)
return bg if fg.a == 0
return fg if fg.a == 255
fg_alpha = fg.a / 255.0
bg_alpha = fg.a / 255.0
alpha_complement = (1.0 - fg_alpha) * bg_alpha
new_r = (fg_alpha * fg.r + alpha_complement * bg.r).round
new_g = (fg_alpha * fg.g + alpha_complement * bg.g).round
new_b = (fg_alpha * fg.b + alpha_complement * bg.b).round
new_a = ((fg_alpha + alpha_complement) * 255).round
Pixel.rgba(new_r, new_g, new_b, new_a)
end
{% endhighlight %}
This implementation is already a little bit optimized: no unnecessary conversions and calculations are being performed. However, this composition can be done a lot quicker after realizing that 255 is almost a power of two, in which computers excel because it can use bitwise operators and shifting for some calculations.
My new approach uses a quicker implementation of multiplication of 8-bit integers that represent floating numbers between 0 and 1:
{% highlight ruby %}
def compose(fg, bg)
return bg if fg.a == 0
return fg if fg.a == 255
alpha_complement = multiply(255 - fg.a, bg.a)
new_r = multiply(fg.a, fg.r) + multiply(alpha_complement, bg.r)
new_g = multiply(fg.a, fg.g) + multiply(alpha_complement, bg.g)
new_b = multiply(fg.a, fg.b) + multiply(alpha_complement, bg.b)
new_a = fg.a + alpha_complement
Pixel.rgba(new_r, new_g, new_b, new_a)
end
# Quicker alternative for (a * b / 255.0).round
def multiply(a, b)
t = a * b + 0x80
((t >> 8) + t) >> 8
end
{% endhighlight %}
Note that the new implementation is less precise in theory, but this precision is lost anyway because we have to convert the values back to 8 bit RGBA values. Your thoughts?
|