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IainNZ/gist:7340901

Created November 6, 2013 17:52
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gistfile1.txt
{
"metadata": {
"name": "What is multiple dispatch?"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": "Multiple Dispatch helps make Julia fast. <br>\nIt also makes Julia extensible, programmable, and downright fun to play with. <br>\nIt may just be a breakthrough for parallel computation..."
},
{
"cell_type": "markdown",
"metadata": {},
"source": "1. Roman Numeral Example\n2. Function Example\n3. Parallel Computing Example"
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": "1. Roman Numeral Example (just for fun)"
},
{
"cell_type": "code",
"collapsed": false,
"input": "type Roman \n n::Int\nend\n\n# Cool roman numeral printing magic (0:9 for demo only)\nimport Base: promote_rule, convert, show\nBase.show(io::IO, r::Roman)=print(io,r.n%10==0?'0':'\u2170'+r.n%10-1)\n\n[Roman(1) Roman(2) Roman(5) Roman(9)] ",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 1,
"text": "1x4 Array{Roman,2}:\n \u2170 \u2171 \u2174 \u2178"
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": "*(i::Roman,j::Roman)=Roman(i.n*j.n) # Multiply like a Roman\n\n*(i::Number,j::Roman)=eye(i)*j.n # Multiply like a matrix constructor\n\n*(i::Roman,j::Number)=print(['\u263a' for k=1:(i.n)*j]') # Multiply like a kid",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 15,
"text": "* (generic function with 129 methods)"
}
],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": "[Roman(2)*Roman(3) Roman(3)^2] # WOW! Squaring just worked",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 21,
"text": "1x2 Array{Roman,2}:\n \u2175 \u2178"
}
],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": "7*Roman(4) # Multiply like a matrix constructor",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 17,
"text": "7x7 Array{Float64,2}:\n 4.0 0.0 0.0 0.0 0.0 0.0 0.0\n 0.0 4.0 0.0 0.0 0.0 0.0 0.0\n 0.0 0.0 4.0 0.0 0.0 0.0 0.0\n 0.0 0.0 0.0 4.0 0.0 0.0 0.0\n 0.0 0.0 0.0 0.0 4.0 0.0 0.0\n 0.0 0.0 0.0 0.0 0.0 4.0 0.0\n 0.0 0.0 0.0 0.0 0.0 0.0 4.0"
}
],
"prompt_number": 17
},
{
"cell_type": "code",
"collapsed": false,
"input": "Roman(2)*4 # Multiply like a kid",
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": "\u263a\t\u263a\t\u263a\t\u263a\t\u263a\t\u263a\t\u263a\t\u263a\n"
}
],
"prompt_number": 20
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": "2. Function Example (glimpse of why multiple dispatch is useful)"
},
{
"cell_type": "code",
"collapsed": false,
"input": "\n*(\u03b1::Number, g::Function)= x->\u03b1*g(x) # Scalar times function\n*(f::Function,\u03bb::Number) = x->f(\u03bb*x) # Scale the argument\n*(f::Function,g::Function)= x->f(g(x)) # Function Composition",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 26,
"text": "* (generic function with 132 methods)"
}
],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": "using PyPlot",
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 27
},
{
"cell_type": "code",
"collapsed": false,
"input": "x=pi*(0:.01:4)\n\nplot(x,(12*sin)(x),\"g\")\nplot(x,(sin*12)(x),\"r\")\nplot(x,(5*sin*exp)(x),\"b\")",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": "Figure(PyObject <matplotlib.figure.Figure object at 0x7826d10>)"
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 39,
"text": "1-element Array{Any,1}:\n PyObject <matplotlib.lines.Line2D object at 0x75f5750>"
}
],
"prompt_number": 39
},
{
"cell_type": "markdown",
"metadata": {},
"source": "<img src=\"https://lh4.googleusercontent.com/--z5eKJbB7sg/UffjL1iAd4I/AAAAAAAABOc/S_wDVyDOBfQ/gauss.jpg\">"
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": " \"Sin^2 phi is odious to me, even though Laplace made use of it; should\n it be feared that sin^2 phi might become ambiguous, which would perhaps\n never occur, or at most very rarely when speaking of sin(phi^2), well\n then, let us write (sin phi)^2, but not sin^2 phi, which by analogy\n should signify sin(sin phi).\""
},
{
"cell_type": "code",
"collapsed": false,
"input": "x=(0:.01:2)*pi;\nplot(x,(sin^2)(x),\"b\") # Squaring just works, y=sin(sin(x)), Gauss would be pleased!\nplot(x,sin(x).^2,\"r\") ",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
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"text": "Figure(PyObject <matplotlib.figure.Figure object at 0xa087b10>)"
},
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"metadata": {},
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"text": "1-element Array{Any,1}:\n PyObject <matplotlib.lines.Line2D object at 0x927dfd0>"
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{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": "3. Parallel Computing Examples (How did we live without it!!??)"
},
{
"cell_type": "code",
"collapsed": false,
"input": "cumprod(1:10)' %Prefix product gives factorials",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 56,
"text": "1x10 Array{Int64,2}:\n 1 2 6 24 120 720 5040 40320 362880 3628800"
}
],
"prompt_number": 56
},
{
"cell_type": "code",
"collapsed": false,
"input": "function prefix_serial(y,*)\n for i in 2:length(y)\n y[i]=y[i-1]*y[i]\n end\n y\nend",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 59,
"text": "prefix_serial (generic function with 1 method)"
}
],
"prompt_number": 59
},
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"cell_type": "code",
"collapsed": false,
"input": "prefix_serial([1:10],*)'",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 62,
"text": "1x10 Array{Int64,2}:\n 1 2 6 24 120 720 5040 40320 362880 3628800"
}
],
"prompt_number": 62
},
{
"cell_type": "code",
"collapsed": false,
"input": "prefix_serial([1:10],+)'",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 74,
"text": "1x10 Array{Int64,2}:\n 1 3 6 10 15 21 28 36 45 55"
}
],
"prompt_number": 74
},
{
"cell_type": "code",
"collapsed": false,
"input": "prefix_serial([1:10],min)'",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 76,
"text": "1x10 Array{Int64,2}:\n 1 1 1 1 1 1 1 1 1 1"
}
],
"prompt_number": 76
},
{
"cell_type": "code",
"collapsed": false,
"input": "A=[rand(1:3,2,2) for i=1:4];A[1]",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 88,
"text": "2x2 Array{Int64,2}:\n 2 2\n 3 3"
}
],
"prompt_number": 88
},
{
"cell_type": "code",
"collapsed": false,
"input": "prefix_serial(A,*)",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 89,
"text": "4-element Array{Array{Int64,2},1}:\n 2x2 Array{Int64,2}:\n 2 2\n 3 3 \n 2x2 Array{Int64,2}:\n 8 4\n 12 6 \n 2x2 Array{Int64,2}:\n 20 24\n 30 36 \n 2x2 Array{Int64,2}:\n 68 88\n 102 132"
}
],
"prompt_number": 89
},
{
"cell_type": "code",
"collapsed": false,
"input": "prefix_serial(A,kron)",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 90,
"text": "4-element Array{Array{Int64,2},1}:\n 2x2 Array{Int64,2}:\n 2 2\n 3 3 \n 4x4 Array{Int64,2}:\n 16 8 16 8\n 24 12 24 12\n 24 12 24 12\n 36 18 36 18 \n 8x8 Array{Int64,2}:\n 320 384 160 192 320 384 160 192\n 480 576 240 288 480 576 240 288\n 480 576 240 288 480 576 240 288\n 720 864 360 432 720 864 360 432\n 480 576 240 288 480 576 240 288\n 720 864 360 432 720 864 360 432\n 720 864 360 432 720 864 360 432\n 1080 1296 540 648 1080 1296 540 648 \n 16x16 Array{Int64,2}:\n 21760 28160 26112 33792 10880 14080 13056 16896 21760 28160 26112 33792 10880 14080 13056 16896\n 32640 42240 39168 50688 16320 21120 19584 25344 32640 42240 39168 50688 16320 21120 19584 25344\n 32640 42240 39168 50688 16320 21120 19584 25344 32640 42240 39168 50688 16320 21120 19584 25344\n 48960 63360 58752 76032 24480 31680 29376 38016 48960 63360 58752 76032 24480 31680 29376 38016\n 32640 42240 39168 50688 16320 21120 19584 25344 32640 42240 39168 50688 16320 21120 19584 25344\n 48960 63360 58752 76032 24480 31680 29376 38016 48960 63360 58752 76032 24480 31680 29376 38016\n 48960 63360 58752 76032 24480 31680 29376 38016 48960 63360 58752 76032 24480 31680 29376 38016\n 73440 95040 88128 114048 36720 47520 44064 57024 73440 95040 88128 114048 36720 47520 44064 57024\n 32640 42240 39168 50688 16320 21120 19584 25344 32640 42240 39168 50688 16320 21120 19584 25344\n 48960 63360 58752 76032 24480 31680 29376 38016 48960 63360 58752 76032 24480 31680 29376 38016\n 48960 63360 58752 76032 24480 31680 29376 38016 48960 63360 58752 76032 24480 31680 29376 38016\n 73440 95040 88128 114048 36720 47520 44064 57024 73440 95040 88128 114048 36720 47520 44064 57024\n 48960 63360 58752 76032 24480 31680 29376 38016 48960 63360 58752 76032 24480 31680 29376 38016\n 73440 95040 88128 114048 36720 47520 44064 57024 73440 95040 88128 114048 36720 47520 44064 57024\n 73440 95040 88128 114048 36720 47520 44064 57024 73440 95040 88128 114048 36720 47520 44064 57024\n 110160 142560 132192 171072 55080 71280 66096 85536 110160 142560 132192 171072 55080 71280 66096 85536"
}
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"prompt_number": 90
},
{
"cell_type": "code",
"collapsed": false,
"input": "# staged prefix (example with 8 elements)",
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 91
},
{
"cell_type": "code",
"collapsed": false,
"input": "function prefix8(y,*)\n if length(y)!=8; error(\"length 8 only\"); end\n for i in [2,4,6,8]; y[i]=y[i-1]*y[i]; end\n for i in [ 4, 8]; y[i]=y[i-2]*y[i]; end\n for i in [ 8]; y[i]=y[i-4]*y[i]; end\n for i in [ 6 ]; y[i]=y[i-2]*y[i]; end\n for i in [ 3,5,7 ]; y[i]=y[i-1]*y[i]; end\n y\nend",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 1,
"text": "prefix8 (generic function with 1 method)"
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": "prefix8([1:8],*)'",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": "1x8 Array{Int64,2}:\n 1 2 6 24 120 720 5040 40320"
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": "addprocs(7)",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 3,
"text": "7-element Array{Any,1}:\n 2\n 3\n 4\n 5\n 6\n 7\n 8"
}
],
"prompt_number": 3
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": "@spawnat : One of many parallel programming primitives in Julia"
},
{
"cell_type": "code",
"collapsed": false,
"input": "r=@spawnat 3 x=randn(4,4) # Execute on processor 3, return a pointer to the answer",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": "RemoteRef(3,1,6)"
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": "fetch(r)",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": "4x4 Array{Float64,2}:\n 1.06088 -0.734633 0.580743 0.659417 \n 0.755944 0.735749 -0.139172 0.0996647\n 1.11658 -0.616243 -0.180218 -0.507076 \n 0.273514 -0.933803 -2.05133 -1.38384 "
}
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"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": "*(r1::RemoteRef,r2::RemoteRef)=@spawnat r2.where fetch(r1)*fetch(r2)",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": "* (generic function with 127 methods)"
}
],
"prompt_number": 6
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": "The above makes the prefix code parallel "
},
{
"cell_type": "code",
"collapsed": false,
"input": "A=[@spawnat i randn(5000,5000) for i=1:8]",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 7,
"text": "8-element Array{Any,1}:\n RemoteRef(1,1,8) \n RemoteRef(2,1,9) \n RemoteRef(3,1,10)\n RemoteRef(4,1,11)\n RemoteRef(5,1,12)\n RemoteRef(6,1,13)\n RemoteRef(7,1,14)\n RemoteRef(8,1,15)"
}
],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": "@time @sync prefix8(A,*)",
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": "elapsed time: 168"
},
{
"output_type": "stream",
"stream": "stdout",
"text": ".724089338 seconds (274694192 bytes allocated)\n"
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 8,
"text": "8-element Array{Any,1}:\n RemoteRef(1,1,8) \n RemoteRef(2,1,16)\n RemoteRef(3,1,24)\n RemoteRef(4,1,20)\n RemoteRef(5,1,25)\n RemoteRef(6,1,23)\n RemoteRef(7,1,26)\n RemoteRef(8,1,22)"
}
],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": "A=randn(5000,5000);B=randn(5000,5000);\ntic();A*B;t=toc();t*11",
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": "elapsed time: "
},
{
"output_type": "stream",
"stream": "stdout",
"text": "40.91440721 seconds\n"
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 9,
"text": "450.05847931"
}
],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": "",
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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