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analysis.ipynb
{
"cells": [
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "\u001b[1m117×4 DataFrame\u001b[0m\n\u001b[1m Row \u001b[0m│\u001b[1m basesize \u001b[0m\u001b[1m needleloc \u001b[0m\u001b[1m executor \u001b[0m\u001b[1m trial \u001b[0m\n\u001b[1m \u001b[0m│\u001b[90m Int64 \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m Symbol \u001b[0m\u001b[90m Trial… \u001b[0m\n─────┼────────────────────────────────────────────────────────\n 1 │ 4096 65536 DepthFirstEx Trial(151.959 μs)\n 2 │ 4096 65536 WorkStealingEx Trial(767.383 μs)\n 3 │ 4096 65536 ThreadedEx Trial(260.148 μs)\n 4 │ 4096 8388608 DepthFirstEx Trial(16.429 ms)\n 5 │ 4096 8388608 WorkStealingEx Trial(1.422 ms)\n 6 │ 4096 8388608 ThreadedEx Trial(2.188 ms)\n 7 │ 4096 1048576 DepthFirstEx Trial(2.030 ms)\n 8 │ 4096 1048576 WorkStealingEx Trial(1.408 ms)\n ⋮ │ ⋮ ⋮ ⋮ ⋮\n 111 │ 8192 524288 ThreadedEx Trial(213.269 μs)\n 112 │ 8192 4194304 DepthFirstEx Trial(3.933 ms)\n 113 │ 8192 4194304 WorkStealingEx Trial(1.154 ms)\n 114 │ 8192 4194304 ThreadedEx Trial(707.694 μs)\n 115 │ 8192 32768 DepthFirstEx Trial(72.069 μs)\n 116 │ 8192 32768 WorkStealingEx Trial(394.487 μs)\n 117 │ 8192 32768 ThreadedEx Trial(175.528 μs)\n\u001b[36m 102 rows omitted\u001b[0m",
"text/html": [
"<table class=\"data-frame\"><thead><tr><th></th><th>basesize</th><th>needleloc</th><th>executor</th><th>trial</th></tr><tr><th></th><th>Int64</th><th>Int64</th><th>Symbol</th><th>Trial…</th></tr></thead><tbody><p>117 rows × 4 columns</p><tr><th>1</th><td>4096</td><td>65536</td><td>DepthFirstEx</td><td>151.959 μs</td></tr><tr><th>2</th><td>4096</td><td>65536</td><td>WorkStealingEx</td><td>767.383 μs</td></tr><tr><th>3</th><td>4096</td><td>65536</td><td>ThreadedEx</td><td>260.148 μs</td></tr><tr><th>4</th><td>4096</td><td>8388608</td><td>DepthFirstEx</td><td>16.429 ms</td></tr><tr><th>5</th><td>4096</td><td>8388608</td><td>WorkStealingEx</td><td>1.422 ms</td></tr><tr><th>6</th><td>4096</td><td>8388608</td><td>ThreadedEx</td><td>2.188 ms</td></tr><tr><th>7</th><td>4096</td><td>1048576</td><td>DepthFirstEx</td><td>2.030 ms</td></tr><tr><th>8</th><td>4096</td><td>1048576</td><td>WorkStealingEx</td><td>1.408 ms</td></tr><tr><th>9</th><td>4096</td><td>1048576</td><td>ThreadedEx</td><td>458.276 μs</td></tr><tr><th>10</th><td>4096</td><td>16384</td><td>DepthFirstEx</td><td>80.750 μs</td></tr><tr><th>11</th><td>4096</td><td>16384</td><td>WorkStealingEx</td><td>684.364 μs</td></tr><tr><th>12</th><td>4096</td><td>16384</td><td>ThreadedEx</td><td>216.298 μs</td></tr><tr><th>13</th><td>4096</td><td>8192</td><td>DepthFirstEx</td><td>69.600 μs</td></tr><tr><th>14</th><td>4096</td><td>8192</td><td>WorkStealingEx</td><td>688.154 μs</td></tr><tr><th>15</th><td>4096</td><td>8192</td><td>ThreadedEx</td><td>167.048 μs</td></tr><tr><th>16</th><td>4096</td><td>262144</td><td>DepthFirstEx</td><td>530.555 μs</td></tr><tr><th>17</th><td>4096</td><td>262144</td><td>WorkStealingEx</td><td>1.112 ms</td></tr><tr><th>18</th><td>4096</td><td>262144</td><td>ThreadedEx</td><td>339.667 μs</td></tr><tr><th>19</th><td>4096</td><td>4096</td><td>DepthFirstEx</td><td>69.820 μs</td></tr><tr><th>20</th><td>4096</td><td>4096</td><td>WorkStealingEx</td><td>665.344 μs</td></tr><tr><th>21</th><td>4096</td><td>4096</td><td>ThreadedEx</td><td>130.399 μs</td></tr><tr><th>22</th><td>4096</td><td>2097152</td><td>DepthFirstEx</td><td>3.700 ms</td></tr><tr><th>23</th><td>4096</td><td>2097152</td><td>WorkStealingEx</td><td>1.296 ms</td></tr><tr><th>24</th><td>4096</td><td>2097152</td><td>ThreadedEx</td><td>649.834 μs</td></tr><tr><th>&vellip;</th><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td></tr></tbody></table>"
]
},
"metadata": {},
"execution_count": 1
}
],
"cell_type": "code",
"source": [
"using BenchmarkTools\n",
"using DataFrames\n",
"using Transducers\n",
"using VegaLite\n",
"\n",
"resultpath = joinpath(@__DIR__, \"result.json\")\n",
"result, = BenchmarkTools.load(resultpath)\n",
"\n",
"df_raw =\n",
" BenchmarkTools.leaves(result) |>\n",
" Map() do ((basesize, needleloc, ex), trial)\n",
" (\n",
" basesize = parse(Int, basesize),\n",
" needleloc = parse(Int, needleloc),\n",
" executor = Symbol(ex),\n",
" trial = trial,\n",
" )\n",
" end |>\n",
" DataFrame"
],
"metadata": {},
"execution_count": 1
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "\u001b[1m234×6 DataFrame\u001b[0m\n\u001b[1m Row \u001b[0m│\u001b[1m basesize \u001b[0m\u001b[1m needleloc \u001b[0m\u001b[1m executor \u001b[0m\u001b[1m memory \u001b[0m\u001b[1m time_stat \u001b[0m\u001b[1m time_ns \u001b[0m ⋯\n\u001b[1m \u001b[0m│\u001b[90m Int64 \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m Symbol \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m String \u001b[0m\u001b[90m Float64 \u001b[0m ⋯\n─────┼──────────────────────────────────────────────────────────────────────────\n 1 │ 4096 65536 DepthFirstEx 52832 minimum 151959.0 ⋯\n 2 │ 4096 65536 WorkStealingEx 6342800 minimum 767383.0\n 3 │ 4096 65536 ThreadedEx 573328 minimum 260148.0\n 4 │ 4096 8388608 DepthFirstEx 4917072 minimum 1.6429e7\n 5 │ 4096 8388608 WorkStealingEx 6696048 minimum 1.42161e6 ⋯\n 6 │ 4096 8388608 ThreadedEx 4882080 minimum 2.18779e6\n 7 │ 4096 1048576 DepthFirstEx 622656 minimum 2.03032e6\n 8 │ 4096 1048576 WorkStealingEx 6466768 minimum 1.40804e6\n ⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋱\n 228 │ 8192 524288 ThreadedEx 423936 median 1.06226e6 ⋯\n 229 │ 8192 4194304 DepthFirstEx 1232864 median 4.38385e6\n 230 │ 8192 4194304 WorkStealingEx 3319760 median 1.44592e6\n 231 │ 8192 4194304 ThreadedEx 1253152 median 1.26035e6\n 232 │ 8192 32768 DepthFirstEx 28416 median 102459.0 ⋯\n 233 │ 8192 32768 WorkStealingEx 3183344 median 493381.0\n 234 │ 8192 32768 ThreadedEx 269408 median 8.69268e5\n\u001b[36m 219 rows omitted\u001b[0m",
"text/html": [
"<table class=\"data-frame\"><thead><tr><th></th><th>basesize</th><th>needleloc</th><th>executor</th><th>memory</th><th>time_stat</th><th>time_ns</th></tr><tr><th></th><th>Int64</th><th>Int64</th><th>Symbol</th><th>Int64</th><th>String</th><th>Float64</th></tr></thead><tbody><p>234 rows × 6 columns</p><tr><th>1</th><td>4096</td><td>65536</td><td>DepthFirstEx</td><td>52832</td><td>minimum</td><td>151959.0</td></tr><tr><th>2</th><td>4096</td><td>65536</td><td>WorkStealingEx</td><td>6342800</td><td>minimum</td><td>767383.0</td></tr><tr><th>3</th><td>4096</td><td>65536</td><td>ThreadedEx</td><td>573328</td><td>minimum</td><td>260148.0</td></tr><tr><th>4</th><td>4096</td><td>8388608</td><td>DepthFirstEx</td><td>4917072</td><td>minimum</td><td>1.6429e7</td></tr><tr><th>5</th><td>4096</td><td>8388608</td><td>WorkStealingEx</td><td>6696048</td><td>minimum</td><td>1.42161e6</td></tr><tr><th>6</th><td>4096</td><td>8388608</td><td>ThreadedEx</td><td>4882080</td><td>minimum</td><td>2.18779e6</td></tr><tr><th>7</th><td>4096</td><td>1048576</td><td>DepthFirstEx</td><td>622656</td><td>minimum</td><td>2.03032e6</td></tr><tr><th>8</th><td>4096</td><td>1048576</td><td>WorkStealingEx</td><td>6466768</td><td>minimum</td><td>1.40804e6</td></tr><tr><th>9</th><td>4096</td><td>1048576</td><td>ThreadedEx</td><td>950528</td><td>minimum</td><td>458276.0</td></tr><tr><th>10</th><td>4096</td><td>16384</td><td>DepthFirstEx</td><td>28576</td><td>minimum</td><td>80750.0</td></tr><tr><th>11</th><td>4096</td><td>16384</td><td>WorkStealingEx</td><td>6333584</td><td>minimum</td><td>684364.0</td></tr><tr><th>12</th><td>4096</td><td>16384</td><td>ThreadedEx</td><td>370048</td><td>minimum</td><td>216298.0</td></tr><tr><th>13</th><td>4096</td><td>8192</td><td>DepthFirstEx</td><td>26080</td><td>minimum</td><td>69600.0</td></tr><tr><th>14</th><td>4096</td><td>8192</td><td>WorkStealingEx</td><td>6332848</td><td>minimum</td><td>688154.0</td></tr><tr><th>15</th><td>4096</td><td>8192</td><td>ThreadedEx</td><td>345600</td><td>minimum</td><td>167048.0</td></tr><tr><th>16</th><td>4096</td><td>262144</td><td>DepthFirstEx</td><td>166096</td><td>minimum</td><td>530555.0</td></tr><tr><th>17</th><td>4096</td><td>262144</td><td>WorkStealingEx</td><td>6381600</td><td>minimum</td><td>1.11229e6</td></tr><tr><th>18</th><td>4096</td><td>262144</td><td>ThreadedEx</td><td>680016</td><td>minimum</td><td>339667.0</td></tr><tr><th>19</th><td>4096</td><td>4096</td><td>DepthFirstEx</td><td>25888</td><td>minimum</td><td>69820.0</td></tr><tr><th>20</th><td>4096</td><td>4096</td><td>WorkStealingEx</td><td>6332576</td><td>minimum</td><td>665344.0</td></tr><tr><th>21</th><td>4096</td><td>4096</td><td>ThreadedEx</td><td>93168</td><td>minimum</td><td>130399.0</td></tr><tr><th>22</th><td>4096</td><td>2097152</td><td>DepthFirstEx</td><td>1239120</td><td>minimum</td><td>3.69973e6</td></tr><tr><th>23</th><td>4096</td><td>2097152</td><td>WorkStealingEx</td><td>6591872</td><td>minimum</td><td>1.29592e6</td></tr><tr><th>24</th><td>4096</td><td>2097152</td><td>ThreadedEx</td><td>1442032</td><td>minimum</td><td>649834.0</td></tr><tr><th>&vellip;</th><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td></tr></tbody></table>"
]
},
"metadata": {},
"execution_count": 2
}
],
"cell_type": "code",
"source": [
"begin\n",
" df_tmp = select(df_raw, Not(:trial))\n",
" df_tmp[!, :minimum] = map(trial -> minimum(trial).time, df_raw.trial)\n",
" df_tmp[!, :median] = map(trial -> median(trial).time, df_raw.trial)\n",
" df_tmp[!, :memory] = map(trial -> trial.memory, df_raw.trial)\n",
" df_stats = stack(\n",
" df_tmp,\n",
" [:minimum, :median],\n",
" variable_name = :time_stat,\n",
" value_name = :time_ns,\n",
" )\n",
"end"
],
"metadata": {},
"execution_count": 2
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "\u001b[1m156×7 DataFrame\u001b[0m\n\u001b[1m Row \u001b[0m│\u001b[1m basesize \u001b[0m\u001b[1m needleloc \u001b[0m\u001b[1m executor \u001b[0m\u001b[1m memory \u001b[0m\u001b[1m time_stat \u001b[0m\u001b[1m time_ns \u001b[0m ⋯\n\u001b[1m \u001b[0m│\u001b[90m Int64 \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m Symbol \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m String \u001b[0m\u001b[90m Float64 \u001b[0m ⋯\n─────┼──────────────────────────────────────────────────────────────────────────\n 1 │ 4096 65536 DepthFirstEx 52832 minimum 151959.0 ⋯\n 2 │ 4096 65536 WorkStealingEx 6342800 minimum 767383.0\n 3 │ 4096 8388608 DepthFirstEx 4917072 minimum 1.6429e7\n 4 │ 4096 8388608 WorkStealingEx 6696048 minimum 1.42161e6\n 5 │ 4096 1048576 DepthFirstEx 622656 minimum 2.03032e6 ⋯\n 6 │ 4096 1048576 WorkStealingEx 6466768 minimum 1.40804e6\n 7 │ 4096 16384 DepthFirstEx 28576 minimum 80750.0\n 8 │ 4096 16384 WorkStealingEx 6333584 minimum 684364.0\n ⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋱\n 150 │ 8192 131072 WorkStealingEx 3191312 median 656260.0 ⋯\n 151 │ 8192 524288 DepthFirstEx 163232 median 629234.0\n 152 │ 8192 524288 WorkStealingEx 3237024 median 1.61668e6\n 153 │ 8192 4194304 DepthFirstEx 1232864 median 4.38385e6\n 154 │ 8192 4194304 WorkStealingEx 3319760 median 1.44592e6 ⋯\n 155 │ 8192 32768 DepthFirstEx 28416 median 102459.0\n 156 │ 8192 32768 WorkStealingEx 3183344 median 493381.0\n\u001b[36m 1 column and 141 rows omitted\u001b[0m",
"text/html": [
"<table class=\"data-frame\"><thead><tr><th></th><th>basesize</th><th>needleloc</th><th>executor</th><th>memory</th><th>time_stat</th><th>time_ns</th><th>speedup</th></tr><tr><th></th><th>Int64</th><th>Int64</th><th>Symbol</th><th>Int64</th><th>String</th><th>Float64</th><th>Float64</th></tr></thead><tbody><p>156 rows × 7 columns</p><tr><th>1</th><td>4096</td><td>65536</td><td>DepthFirstEx</td><td>52832</td><td>minimum</td><td>151959.0</td><td>1.71196</td></tr><tr><th>2</th><td>4096</td><td>65536</td><td>WorkStealingEx</td><td>6342800</td><td>minimum</td><td>767383.0</td><td>0.339007</td></tr><tr><th>3</th><td>4096</td><td>8388608</td><td>DepthFirstEx</td><td>4917072</td><td>minimum</td><td>1.6429e7</td><td>0.133167</td></tr><tr><th>4</th><td>4096</td><td>8388608</td><td>WorkStealingEx</td><td>6696048</td><td>minimum</td><td>1.42161e6</td><td>1.53896</td></tr><tr><th>5</th><td>4096</td><td>1048576</td><td>DepthFirstEx</td><td>622656</td><td>minimum</td><td>2.03032e6</td><td>0.225716</td></tr><tr><th>6</th><td>4096</td><td>1048576</td><td>WorkStealingEx</td><td>6466768</td><td>minimum</td><td>1.40804e6</td><td>0.325471</td></tr><tr><th>7</th><td>4096</td><td>16384</td><td>DepthFirstEx</td><td>28576</td><td>minimum</td><td>80750.0</td><td>2.67861</td></tr><tr><th>8</th><td>4096</td><td>16384</td><td>WorkStealingEx</td><td>6333584</td><td>minimum</td><td>684364.0</td><td>0.316057</td></tr><tr><th>9</th><td>4096</td><td>8192</td><td>DepthFirstEx</td><td>26080</td><td>minimum</td><td>69600.0</td><td>2.40011</td></tr><tr><th>10</th><td>4096</td><td>8192</td><td>WorkStealingEx</td><td>6332848</td><td>minimum</td><td>688154.0</td><td>0.242748</td></tr><tr><th>11</th><td>4096</td><td>262144</td><td>DepthFirstEx</td><td>166096</td><td>minimum</td><td>530555.0</td><td>0.640211</td></tr><tr><th>12</th><td>4096</td><td>262144</td><td>WorkStealingEx</td><td>6381600</td><td>minimum</td><td>1.11229e6</td><td>0.305376</td></tr><tr><th>13</th><td>4096</td><td>4096</td><td>DepthFirstEx</td><td>25888</td><td>minimum</td><td>69820.0</td><td>1.86765</td></tr><tr><th>14</th><td>4096</td><td>4096</td><td>WorkStealingEx</td><td>6332576</td><td>minimum</td><td>665344.0</td><td>0.195987</td></tr><tr><th>15</th><td>4096</td><td>2097152</td><td>DepthFirstEx</td><td>1239120</td><td>minimum</td><td>3.69973e6</td><td>0.175644</td></tr><tr><th>16</th><td>4096</td><td>2097152</td><td>WorkStealingEx</td><td>6591872</td><td>minimum</td><td>1.29592e6</td><td>0.501447</td></tr><tr><th>17</th><td>4096</td><td>2048</td><td>DepthFirstEx</td><td>25840</td><td>minimum</td><td>63919.0</td><td>1.81556</td></tr><tr><th>18</th><td>4096</td><td>2048</td><td>WorkStealingEx</td><td>6332576</td><td>minimum</td><td>675144.0</td><td>0.171888</td></tr><tr><th>19</th><td>4096</td><td>131072</td><td>DepthFirstEx</td><td>89120</td><td>minimum</td><td>272897.0</td><td>0.781899</td></tr><tr><th>20</th><td>4096</td><td>131072</td><td>WorkStealingEx</td><td>6356880</td><td>minimum</td><td>877112.0</td><td>0.243273</td></tr><tr><th>21</th><td>4096</td><td>524288</td><td>DepthFirstEx</td><td>318000</td><td>minimum</td><td>990061.0</td><td>0.3434</td></tr><tr><th>22</th><td>4096</td><td>524288</td><td>WorkStealingEx</td><td>6508976</td><td>minimum</td><td>1.39974e6</td><td>0.242893</td></tr><tr><th>23</th><td>4096</td><td>4194304</td><td>DepthFirstEx</td><td>2470832</td><td>minimum</td><td>7.6164e6</td><td>0.142991</td></tr><tr><th>24</th><td>4096</td><td>4194304</td><td>WorkStealingEx</td><td>6624112</td><td>minimum</td><td>1.35167e6</td><td>0.805731</td></tr><tr><th>&vellip;</th><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td></tr></tbody></table>"
]
},
"metadata": {},
"execution_count": 3
}
],
"cell_type": "code",
"source": [
"begin\n",
" df = transform(groupby(df_stats, [:basesize, :needleloc, :time_stat])) do group\n",
" baseline = only(eachrow(filter(:executor => ==(:ThreadedEx), group)))\n",
" (speedup = baseline.time_ns ./ group.time_ns,)\n",
" end\n",
" filter!(:executor => !(==(:ThreadedEx)), df)\n",
" df\n",
"end"
],
"metadata": {},
"execution_count": 3
},
{
"outputs": [],
"cell_type": "code",
"source": [
"plt1 = @vlplot(\n",
" facet = {row = {field = :executor, type = :nominal}, column = {field = :time_stat, type = :nominal}},\n",
" spec = {\n",
" layer = [\n",
" {\n",
" mark = {type = :line, point = true},\n",
" encoding = {\n",
" x = {field = :needleloc, scale = {type = :log, base = 2}},\n",
" y = {field = :speedup, axis = {title = \"Speedup (T_default / T_\\$executor)\"}},\n",
" color = {field = :basesize, type = :nominal},\n",
" },\n",
" },\n",
" {\n",
" mark = :rule,\n",
" encoding = {y = {datum = 1}},\n",
" },\n",
" ],\n",
" },\n",
" data = df,\n",
")\n",
"\n",
"plt2 = @vlplot(\n",
" mark = {type = :line, point = true},\n",
" x = {field = :needleloc, scale = {type = :log, base = 2}},\n",
" y = {field = :time_ns, axis = {title = \"Time [ns]\"}},\n",
" color = {field = :basesize, type = :nominal},\n",
" row = :executor,\n",
" column = :time_stat,\n",
" resolve = {scale = {y = \"independent\"}},\n",
" data = df_stats,\n",
")\n",
"\n",
"plt3 = @vlplot(\n",
" mark = {type = :line, point = true, clip = true},\n",
" x = {field = :needleloc, scale = {type = :log, base = 2}},\n",
" y = {field = :time_ns, axis = {title = \"Time [ns]\"}, scale = {domain = [0, 2_500_000]}},\n",
" color = {field = :basesize, type = :nominal},\n",
" row = :executor,\n",
" column = :time_stat,\n",
" data = df_stats,\n",
")\n",
"nothing"
],
"metadata": {},
"execution_count": 4
},
{
"cell_type": "markdown",
"source": [
"## Notes\n",
"\n",
"#### Summary\n",
"\n",
"Peformance of parallel `findfirst` with different scheduling strategies\n",
"(\"executors\") are benchmarked. `DepthFirstEx` is useful when the latency of\n",
"the \"hit case\" is important and/or the needle is expected to be at somehwere\n",
"in the beginning of the collection. Otherwise, `ThreadedEx` (default) is a\n",
"good option. For consistent latency, `WorkStealingEx` may be useful.\n",
"\n",
"#### Benchmarked problem\n",
"\n",
"```julia\n",
"const DATA_LENGTH = 2^23\n",
"xs = rand(DATA_LENGTH)\n",
"xs[needleloc] = 2\n",
"@benchmarkable(Folds.findfirst(>(1), xs, $Executor(basesize = $basesize)))\n",
"```\n",
"\n",
"#### Speedup"
],
"metadata": {}
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "@vlplot(\n facet={\n row={\n field=\"executor\",\n type=\"nominal\"\n },\n column={\n field=\"time_stat\",\n type=\"nominal\"\n }\n },\n spec={\n layer=[\n {\n mark={\n type=\"line\",\n point=true\n },\n encoding={\n x={\n field=\"needleloc\",\n scale={\n type=\"log\",\n base=2\n }\n },\n y={\n field=\"speedup\",\n axis={\n title=\"Speedup (T_default / T_$executor)\"\n }\n },\n color={\n field=\"basesize\",\n type=\"nominal\"\n }\n }\n },\n {\n mark=\"rule\",\n encoding={\n y={\n datum=1\n }\n }\n }\n ]\n },\n data={\n values=...\n }\n)",
"image/png": 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opacity=\"1\"></path></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">8192</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g><g transform=\"translate(0,32)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h46v12.5h-46Z\" pointer-events=\"none\" opacity=\"1\"></path><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#e45756\" stroke=\"#e45756\" stroke-width=\"1.5\" opacity=\"1\"></path></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">16384</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g><g class=\"mark-text role-legend-title\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,9)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">basesize</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g></g></svg>\n"
]
},
"metadata": {},
"execution_count": 5
}
],
"cell_type": "code",
"source": [
"plt1"
],
"metadata": {},
"execution_count": 5
},
{
"cell_type": "markdown",
"source": [
"Speedup of `DepthFirstEx` (first row) and `WorkStealingEx` (second row) with\n",
"respect to the default `ThreadedEx` executor.\n",
"\n",
"Since **the x axis logarithmic**, note that the range of large speedup for\n",
"`DepthFirstEx` is overly emphasized; i.e., `DepthFirstEx` does _not_ perform\n",
"better on average if the location of the needle is expected to be uniformly\n",
"distributed. On the other hand, `DepthFirstEx` is a good choice when it is\n",
"important to finish fast when the reduction can be terminated early.\n",
"\n",
"`WorkStealingEx` seems to perform better in some limited range."
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"#### Run-time"
],
"metadata": {}
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "@vlplot(\n mark={\n type=\"line\",\n point=true\n },\n resolve={\n scale={\n y=\"independent\"\n }\n },\n data={\n values=...\n },\n encoding={\n x={\n field=\"needleloc\",\n scale={\n type=\"log\",\n base=2\n }\n },\n y={\n field=\"time_ns\",\n axis={\n title=\"Time [ns]\"\n }\n },\n color={\n field=\"basesize\",\n type=\"nominal\"\n },\n row={\n field=\"executor\"\n },\n column={\n field=\"time_stat\"\n }\n }\n)",
"image/png": 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font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">ThreadedEx</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g><g transform=\"translate(-77,464)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v200h0Z\"></path><g><g class=\"mark-group role-title\"><g transform=\"translate(-20.000000000000004,100)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-text role-title-text\" role=\"graphics-symbol\" aria-roledescription=\"title\" aria-label=\"Title text 'WorkStealingEx'\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(0,0) rotate(-90) translate(0,8)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">WorkStealingEx</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g><g class=\"mark-group role-column-header column_header\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,-1)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v0h-200Z\"></path><g><g class=\"mark-group role-title\"><g transform=\"translate(100,-20)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-text role-title-text\" role=\"graphics-symbol\" aria-roledescription=\"title\" aria-label=\"Title text 'median'\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(0,8)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">median</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g><g transform=\"translate(301,-1)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v0h-200Z\"></path><g><g class=\"mark-group role-title\"><g transform=\"translate(100,-20)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-text role-title-text\" role=\"graphics-symbol\" aria-roledescription=\"title\" aria-label=\"Title text 'minimum'\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(0,8)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">minimum</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g><g class=\"mark-group role-column-footer column_footer\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,670)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v0h-200Z\"></path><g><g class=\"mark-group role-axis\" role=\"graphics-symbol\" aria-roledescription=\"axis\" aria-label=\"X-axis titled 'needleloc' for a log scale with values from 2,048 to 8,388,608\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-rule role-axis-tick\" pointer-events=\"none\"><line transform=\"translate(0,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(17,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(33,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(50,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(67,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(83,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(100,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(117,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(133,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(150,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(167,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(183,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(200,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">2,048</text><text text-anchor=\"middle\" transform=\"translate(16.666666666666647,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">4,096</text><text text-anchor=\"middle\" transform=\"translate(33.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">8,192</text><text text-anchor=\"middle\" transform=\"translate(49.99999999999998,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">16,384</text><text text-anchor=\"middle\" transform=\"translate(66.66666666666664,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">32,768</text><text text-anchor=\"middle\" transform=\"translate(83.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">65,536</text><text text-anchor=\"middle\" transform=\"translate(99.99999999999997,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">131,072</text><text text-anchor=\"middle\" transform=\"translate(116.66666666666666,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">262,144</text><text text-anchor=\"middle\" transform=\"translate(133.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">524,288</text><text text-anchor=\"middle\" transform=\"translate(149.99999999999997,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">1,048,576</text><text text-anchor=\"middle\" transform=\"translate(166.66666666666666,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">2,097,152</text><text text-anchor=\"middle\" transform=\"translate(183.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">4,194,304</text><text text-anchor=\"end\" transform=\"translate(200,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">8,388,608</text></g><g class=\"mark-rule role-axis-domain\" pointer-events=\"none\"><line transform=\"translate(0,0)\" x2=\"200\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(100,30)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">needleloc</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g><g transform=\"translate(301,670)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v0h-200Z\"></path><g><g class=\"mark-group role-axis\" role=\"graphics-symbol\" aria-roledescription=\"axis\" aria-label=\"X-axis titled 'needleloc' for a log scale with values from 2,048 to 8,388,608\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-rule role-axis-tick\" pointer-events=\"none\"><line transform=\"translate(0,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(17,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(33,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(50,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(67,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(83,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(100,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(117,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(133,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(150,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(167,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(183,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(200,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">2,048</text><text text-anchor=\"middle\" transform=\"translate(16.666666666666647,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">4,096</text><text text-anchor=\"middle\" transform=\"translate(33.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">8,192</text><text text-anchor=\"middle\" transform=\"translate(49.99999999999998,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">16,384</text><text text-anchor=\"middle\" transform=\"translate(66.66666666666664,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">32,768</text><text text-anchor=\"middle\" transform=\"translate(83.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">65,536</text><text text-anchor=\"middle\" transform=\"translate(99.99999999999997,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">131,072</text><text text-anchor=\"middle\" transform=\"translate(116.66666666666666,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">262,144</text><text text-anchor=\"middle\" transform=\"translate(133.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">524,288</text><text text-anchor=\"middle\" transform=\"translate(149.99999999999997,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">1,048,576</text><text text-anchor=\"middle\" transform=\"translate(166.66666666666666,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">2,097,152</text><text text-anchor=\"middle\" transform=\"translate(183.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">4,194,304</text><text text-anchor=\"end\" transform=\"translate(200,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">8,388,608</text></g><g class=\"mark-rule role-axis-domain\" pointer-events=\"none\"><line transform=\"translate(0,0)\" x2=\"200\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(100,30)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">needleloc</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g><g class=\"mark-group role-scope cell\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0.5,0.5h200v200h-200Z\" stroke=\"#ddd\"></path><g><g class=\"mark-group role-axis\" aria-hidden=\"true\"><g transform=\"translate(0.5,200.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-rule role-axis-grid\" pointer-events=\"none\"><line transform=\"translate(0,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(17,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(33,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(50,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(67,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(83,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(100,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(117,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(133,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(150,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(167,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(183,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(200,-200)\" x2=\"0\" y2=\"200\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g><g class=\"mark-group role-axis\" aria-hidden=\"true\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-rule role-axis-grid\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"200\" y2=\"0\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,144)\" x2=\"200\" y2=\"0\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,89)\" x2=\"200\" y2=\"0\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,33)\" x2=\"200\" y2=\"0\" stroke=\"#ddd\" stroke-width=\"1\" opacity=\"1\"></line></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g><g class=\"mark-group role-axis\" role=\"graphics-symbol\" aria-roledescription=\"axis\" aria-label=\"Y-axis titled 'Time [ns]' for a linear scale with values from 0 to 18,000,000\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-rule role-axis-tick\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,144)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,89)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,33)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-label\" pointer-events=\"none\"><text text-anchor=\"end\" transform=\"translate(-7,203)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">0</text><text text-anchor=\"end\" transform=\"translate(-7,147.44444444444443)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">5,000,000</text><text text-anchor=\"end\" transform=\"translate(-7,91.88888888888889)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">10,000,000</text><text text-anchor=\"end\" transform=\"translate(-7,36.33333333333333)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">15,000,000</text></g><g class=\"mark-rule role-axis-domain\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"0\" y2=\"-200\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(-65,100) rotate(-90) translate(0,-2)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">Time [ns]</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g><g class=\"mark-group role-scope child_layer_0_pathgroup\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"></path><g><g class=\"mark-line role-mark child_layer_0_marks\" role=\"graphics-object\" aria-roledescription=\"line mark container\"><path aria-label=\"needleloc: 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aria-roledescription=\"line mark\" d=\"M0,198.99884444444444L16.666666666666647,198.94234444444444L33.33333333333331,198.9712888888889L49.99999999999998,198.88428333333331L66.66666666666664,198.86156666666665L83.33333333333331,198.5160111111111L99.99999999999997,197.73351666666667L116.66666666666666,196.31181111111113L133.33333333333331,193.0085111111111L149.99999999999997,186.98966666666666L166.66666666666666,174.6172111111111L183.33333333333331,151.29058333333333L200,107.37101111111112\" stroke=\"#f58518\" stroke-width=\"2\"></path></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g><g class=\"mark-symbol role-mark child_layer_1_marks\" role=\"graphics-object\" aria-roledescription=\"symbol mark container\"><path aria-label=\"needleloc: 65536; Time [ns]: 217033; basesize: 4096\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(83.33333333333331,197.58852222222222)\" 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opacity=\"1\"></path><path aria-label=\"needleloc: 262144; Time [ns]: 815613; basesize: 8192\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(116.66666666666666,98.04837500000001)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#f58518\" stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 4096; Time [ns]: 368597; basesize: 8192\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(16.666666666666647,153.92537499999997)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#f58518\" stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 2097152; Time [ns]: 1134791; basesize: 8192\" role=\"graphics-symbol\" aria-roledescription=\"point\" 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stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 32768; Time [ns]: 394487; basesize: 8192\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(66.66666666666664,150.689125)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#f58518\" stroke-width=\"2\" opacity=\"1\"></path></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g><g class=\"mark-group role-legend\" role=\"graphics-symbol\" aria-roledescription=\"legend\" aria-label=\"Symbol legend titled 'basesize' for fill color and stroke color with 3 values: 4096, 8192, 16384\"><g transform=\"translate(527,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h53v61h-53Z\" pointer-events=\"none\"></path><g><g class=\"mark-group role-legend-entry\"><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-group role-scope\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h46v12.5h-46Z\" pointer-events=\"none\" opacity=\"1\"></path><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#4c78a8\" stroke=\"#4c78a8\" stroke-width=\"1.5\" opacity=\"1\"></path></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">4096</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h46v12.5h-46Z\" pointer-events=\"none\" opacity=\"1\"></path><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#f58518\" stroke=\"#f58518\" stroke-width=\"1.5\" opacity=\"1\"></path></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">8192</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g><g transform=\"translate(0,32)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h46v12.5h-46Z\" pointer-events=\"none\" opacity=\"1\"></path><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#e45756\" stroke=\"#e45756\" stroke-width=\"1.5\" opacity=\"1\"></path></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">16384</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g><g class=\"mark-text role-legend-title\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,9)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">basesize</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g></g></svg>\n"
]
},
"metadata": {},
"execution_count": 6
}
],
"cell_type": "code",
"source": [
"plt2"
],
"metadata": {},
"execution_count": 6
},
{
"cell_type": "markdown",
"source": [
"**NOTE**: x axis logarithmic.\n",
"\n",
"* `DepthFirstEx` behaves consistently well up until the location of the needle\n",
" is around the `basesize`.\n",
"\n",
"* The run-time of `ThreadedEx` (middle row) shows drastically different\n",
" shape of when the median (left) or the minimum (right) is plotted. This\n",
" is likely due to the randomization nature of Julia's scheduling (as of v1.5).\n",
"\n",
"* The peformance of `WorkStealingEx` is more consistent than `ThreadedEx`."
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"#### Run-time (zoom)"
],
"metadata": {}
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "@vlplot(\n mark={\n type=\"line\",\n point=true,\n clip=true\n },\n data={\n values=...\n },\n encoding={\n x={\n field=\"needleloc\",\n scale={\n type=\"log\",\n base=2\n }\n },\n y={\n field=\"time_ns\",\n axis={\n title=\"Time [ns]\"\n },\n scale={\n domain=[\n 0,\n 2500000\n ]\n }\n },\n color={\n field=\"basesize\",\n type=\"nominal\"\n },\n row={\n field=\"executor\"\n },\n column={\n field=\"time_stat\"\n }\n }\n)",
"image/png": 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rotate(-90) translate(0,8)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">DepthFirstEx</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g><g transform=\"translate(-1,222)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v200h0Z\"></path><g><g class=\"mark-group role-axis\" role=\"graphics-symbol\" aria-roledescription=\"axis\" aria-label=\"Y-axis titled 'Time [ns]' for a linear scale with values from 0 to 2,600,000\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-rule role-axis-tick\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,162)\" x2=\"-5\" y2=\"0\" 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opacity=\"1\">1,000,000</text><text text-anchor=\"end\" transform=\"translate(-7,87.61538461538463)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">1,500,000</text><text text-anchor=\"end\" transform=\"translate(-7,49.153846153846146)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">2,000,000</text><text text-anchor=\"end\" transform=\"translate(-7,10.692307692307686)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">2,500,000</text></g><g class=\"mark-rule role-axis-domain\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"0\" y2=\"-200\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(-59,100) rotate(-90) translate(0,-2)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">Time [ns]</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g><g class=\"mark-group role-title\"><g transform=\"translate(-90,100)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-text role-title-text\" role=\"graphics-symbol\" aria-roledescription=\"title\" aria-label=\"Title text 'ThreadedEx'\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(0,0) rotate(-90) translate(0,8)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">ThreadedEx</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g><g transform=\"translate(-1,444)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v200h0Z\"></path><g><g class=\"mark-group role-axis\" role=\"graphics-symbol\" aria-roledescription=\"axis\" aria-label=\"Y-axis titled 'Time [ns]' for a linear scale with values from 0 to 2,600,000\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-rule role-axis-tick\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,162)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,123)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,85)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,46)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(0,8)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g 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aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g><g class=\"mark-group role-column-footer column_footer\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,645)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v0h-200Z\"></path><g><g class=\"mark-group role-axis\" role=\"graphics-symbol\" aria-roledescription=\"axis\" aria-label=\"X-axis titled 'needleloc' for a log scale with values from 2,048 to 8,388,608\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-rule role-axis-tick\" pointer-events=\"none\"><line transform=\"translate(0,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(17,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(33,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" 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opacity=\"1\"></line><line transform=\"translate(200,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">2,048</text><text text-anchor=\"middle\" transform=\"translate(16.666666666666647,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">4,096</text><text text-anchor=\"middle\" transform=\"translate(33.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">8,192</text><text text-anchor=\"middle\" transform=\"translate(49.99999999999998,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">16,384</text><text text-anchor=\"middle\" transform=\"translate(66.66666666666664,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">32,768</text><text text-anchor=\"middle\" transform=\"translate(83.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">65,536</text><text text-anchor=\"middle\" transform=\"translate(99.99999999999997,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">131,072</text><text text-anchor=\"middle\" transform=\"translate(116.66666666666666,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">262,144</text><text text-anchor=\"middle\" transform=\"translate(133.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">524,288</text><text text-anchor=\"middle\" transform=\"translate(149.99999999999997,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">1,048,576</text><text text-anchor=\"middle\" transform=\"translate(166.66666666666666,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">2,097,152</text><text text-anchor=\"middle\" transform=\"translate(183.33333333333331,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">4,194,304</text><text text-anchor=\"end\" transform=\"translate(200,15)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"0\">8,388,608</text></g><g class=\"mark-rule role-axis-domain\" pointer-events=\"none\"><line transform=\"translate(0,0)\" x2=\"200\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(100,30)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">needleloc</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g><g transform=\"translate(222,645)\"><path class=\"background\" 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transform=\"translate(83,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(100,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(117,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(133,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(150,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(167,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(183,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line><line transform=\"translate(200,0)\" x2=\"0\" y2=\"5\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"></line></g><g class=\"mark-text role-axis-label\" pointer-events=\"none\"><text text-anchor=\"start\" 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stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 2048; Time [ns]: 190628; basesize: 16384\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(0,185.33630769230768)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#e45756\" stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 131072; Time [ns]: 418966; basesize: 16384\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(99.99999999999997,167.77184615384616)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#e45756\" stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 524288; Time [ns]: 1023911; basesize: 16384\" role=\"graphics-symbol\" aria-roledescription=\"point\" 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opacity=\"1\"></path><path aria-label=\"needleloc: 131072; Time [ns]: 562715; basesize: 8192\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(99.99999999999997,156.71423076923077)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#f58518\" stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 524288; Time [ns]: 1079211; basesize: 8192\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(133.33333333333331,116.98376923076923)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#f58518\" stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 4194304; Time [ns]: 1153610; basesize: 8192\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(183.33333333333331,111.26076923076921)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#f58518\" stroke-width=\"2\" opacity=\"1\"></path><path aria-label=\"needleloc: 32768; Time [ns]: 394487; basesize: 8192\" role=\"graphics-symbol\" aria-roledescription=\"point\" transform=\"translate(66.66666666666664,169.65484615384617)\" d=\"M2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,-2.7386127875258306,0A2.7386127875258306,2.7386127875258306,0,1,1,2.7386127875258306,0\" fill=\"#f58518\" stroke-width=\"2\" opacity=\"1\"></path></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g><g class=\"mark-group role-legend\" role=\"graphics-symbol\" aria-roledescription=\"legend\" aria-label=\"Symbol legend titled 'basesize' for fill color and stroke color with 3 values: 4096, 8192, 16384\"><g transform=\"translate(448,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h53v61h-53Z\" pointer-events=\"none\"></path><g><g class=\"mark-group role-legend-entry\"><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"></path><g><g class=\"mark-group role-scope\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h46v12.5h-46Z\" pointer-events=\"none\" opacity=\"1\"></path><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#4c78a8\" stroke=\"#4c78a8\" stroke-width=\"1.5\" opacity=\"1\"></path></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">4096</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h46v12.5h-46Z\" pointer-events=\"none\" opacity=\"1\"></path><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#f58518\" stroke=\"#f58518\" stroke-width=\"1.5\" opacity=\"1\"></path></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">8192</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g><g transform=\"translate(0,32)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h46v12.5h-46Z\" pointer-events=\"none\" opacity=\"1\"></path><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#e45756\" stroke=\"#e45756\" stroke-width=\"1.5\" opacity=\"1\"></path></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">16384</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g><g class=\"mark-text role-legend-title\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,9)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">basesize</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"></path></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"></path></g></g></g></svg>\n"
]
},
"metadata": {},
"execution_count": 7
}
],
"cell_type": "code",
"source": [
"plt3"
],
"metadata": {},
"execution_count": 7
},
{
"cell_type": "markdown",
"source": [
"**NOTE**: x axis is logarithmic.\n",
"\n",
"Same as above (`plt2`) but with the range of Y axis fixed for all plots."
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"---\n",
"\n",
"*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*"
],
"metadata": {}
}
],
"nbformat_minor": 3,
"metadata": {
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.5.2"
},
"kernelspec": {
"name": "julia-1.5",
"display_name": "Julia 1.5.2",
"language": "julia"
}
},
"nbformat": 4
}
Raw
analysis.jl
using BenchmarkTools
using DataFrames
using Transducers
using VegaLite
resultpath = joinpath(@__DIR__, "result.json")
result, = BenchmarkTools.load(resultpath)
df_raw =
BenchmarkTools.leaves(result) |>
Map() do ((basesize, needleloc, ex), trial)
(
basesize = parse(Int, basesize),
needleloc = parse(Int, needleloc),
executor = Symbol(ex),
trial = trial,
)
end |>
DataFrame
#-
begin
df_tmp = select(df_raw, Not(:trial))
df_tmp[!, :minimum] = map(trial -> minimum(trial).time, df_raw.trial)
df_tmp[!, :median] = map(trial -> median(trial).time, df_raw.trial)
df_tmp[!, :memory] = map(trial -> trial.memory, df_raw.trial)
df_stats = stack(
df_tmp,
[:minimum, :median],
variable_name = :time_stat,
value_name = :time_ns,
)
end
#-
begin
df = transform(groupby(df_stats, [:basesize, :needleloc, :time_stat])) do group
baseline = only(eachrow(filter(:executor => ==(:ThreadedEx), group)))
(speedup = baseline.time_ns ./ group.time_ns,)
end
filter!(:executor => !(==(:ThreadedEx)), df)
df
end
#-
plt1 = @vlplot(
facet = {row = {field = :executor, type = :nominal}, column = {field = :time_stat, type = :nominal}},
spec = {
layer = [
{
mark = {type = :line, point = true},
encoding = {
x = {field = :needleloc, scale = {type = :log, base = 2}},
y = {field = :speedup, axis = {title = "Speedup (T_default / T_\$executor)"}},
color = {field = :basesize, type = :nominal},
},
},
{
mark = :rule,
encoding = {y = {datum = 1}},
},
],
},
data = df,
)
plt2 = @vlplot(
mark = {type = :line, point = true},
x = {field = :needleloc, scale = {type = :log, base = 2}},
y = {field = :time_ns, axis = {title = "Time [ns]"}},
color = {field = :basesize, type = :nominal},
row = :executor,
column = :time_stat,
resolve = {scale = {y = "independent"}},
data = df_stats,
)
plt3 = @vlplot(
mark = {type = :line, point = true, clip = true},
x = {field = :needleloc, scale = {type = :log, base = 2}},
y = {field = :time_ns, axis = {title = "Time [ns]"}, scale = {domain = [0, 2_500_000]}},
color = {field = :basesize, type = :nominal},
row = :executor,
column = :time_stat,
data = df_stats,
)
nothing
# ## Notes
#
# #### Summary
#
# Peformance of parallel `findfirst` with different scheduling strategies
# ("executors") are benchmarked. `DepthFirstEx` is useful when the latency of
# the "hit case" is important and/or the needle is expected to be at somehwere
# in the beginning of the collection. Otherwise, `ThreadedEx` (default) is a
# good option. For consistent latency, `WorkStealingEx` may be useful.
#
# #### Benchmarked problem
#
# ```julia
# const DATA_LENGTH = 2^23
# xs = rand(DATA_LENGTH)
# xs[needleloc] = 2
# @benchmarkable(Folds.findfirst(>(1), xs, $Executor(basesize = $basesize)))
# ```
#
# #### Speedup
plt1
# Speedup of `DepthFirstEx` (first row) and `WorkStealingEx` (second row) with
# respect to the default `ThreadedEx` executor.
#
# Since **the x axis logarithmic**, note that the range of large speedup for
# `DepthFirstEx` is overly emphasized; i.e., `DepthFirstEx` does _not_ perform
# better on average if the location of the needle is expected to be uniformly
# distributed. On the other hand, `DepthFirstEx` is a good choice when it is
# important to finish fast when the reduction can be terminated early.
#
# `WorkStealingEx` seems to perform better in some limited range.
# #### Run-time
plt2
# **NOTE**: x axis logarithmic.
#
# * `DepthFirstEx` behaves consistently well up until the location of the needle
# is around the `basesize`.
#
# * The run-time of `ThreadedEx` (middle row) shows drastically different
# shape of when the median (left) or the minimum (right) is plotted. This
# is likely due to the randomization nature of Julia's scheduling (as of v1.5).
#
# * The peformance of `WorkStealingEx` is more consistent than `ThreadedEx`.
# #### Run-time (zoom)
plt3
# **NOTE**: x axis is logarithmic.
#
# Same as above (`plt2`) but with the range of Y axis fixed for all plots.
Raw
benchmarks.jl
using BenchmarkTools
using Folds
using FoldsThreads
const SUITE = BenchmarkGroup()
const DATA_LENGTH = 2^23
for log2_basesize in 12:14
basesize = 2^log2_basesize
SUITE[basesize] = s1 = BenchmarkGroup()
for log2_needleloc in 11:23
needleloc = 2^log2_needleloc
s1[needleloc] = s2 = BenchmarkGroup()
xs = rand(DATA_LENGTH)
xs[needleloc] = 2
s2["ThreadedEx"] =
@benchmarkable( Folds.findfirst(>(1), $xs, ThreadedEx(basesize = $basesize)))
s2["WorkStealingEx"] =
@benchmarkable(Folds.findfirst(>(1), $xs, WorkStealingEx(basesize = $basesize)))
s2["DepthFirstEx"] =
@benchmarkable(Folds.findfirst(>(1), $xs, DepthFirstEx(basesize = $basesize)))
#=
s2["SpawnAllEx"] =
@benchmarkable(Folds.findfirst(>(1), $xs, SpawnAllEx(basesize = $basesize)))
=#
end
end
Raw
Makefile
JULIA = julia --startup-file=no
export JULIA_NUM_THREADS = 32
export JULIA_LOAD_PATH = @
export JULIA_PROJECT = $(PWD)
.PHONY: rebuild
analysis.ipynb: analysis.jl result.json
$(MAKE) rebuild
rebuild:
$(JULIA) -e 'using Literate; Literate.notebook("analysis.jl")'
result.json:
$(JULIA) runbenchmarks.jl $@
Raw
Manifest.toml
# This file is machine-generated - editing it directly is not advised
[[Accessors]]
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[[ArgCheck]]
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[[Artifacts]]
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version = "1.3.0"
[[BangBang]]
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version = "0.3.30"
[[Base64]]
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[[BenchmarkTools]]
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[[CategoricalArrays]]
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[[Compat]]
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git-tree-sha1 = "919c7f3151e79ff196add81d7f4e45d91bbf420b"
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[[DataAPI]]
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[[DataFrames]]
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git-tree-sha1 = "b0db5579803eabb33f1274ca7ca2f472fdfb7f2a"
uuid = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
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[[DataStructures]]
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[[DataValueInterfaces]]
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[[DataValues]]
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[[Dates]]
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[[DefineSingletons]]
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[[DelimitedFiles]]
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[[Distributed]]
deps = ["Random", "Serialization", "Sockets"]
uuid = "8ba89e20-285c-5b6f-9357-94700520ee1b"
[[FileIO]]
deps = ["Pkg"]
git-tree-sha1 = "fee8955b9dfa7bec67117ef48085fb2b559b9c22"
uuid = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
version = "1.4.5"
[[FilePaths]]
deps = ["FilePathsBase", "Glob", "MacroTools", "Reexport", "URIParser"]
git-tree-sha1 = "85507891ca01aa1e6afaa66087bb903b7e164284"
uuid = "8fc22ac5-c921-52a6-82fd-178b2807b824"
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git-tree-sha1 = "d4f60ba7f2d961cd580fc91936578673c56943fd"
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[[Folds]]
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[[FoldsThreads]]
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git-tree-sha1 = "daaad417ce82e5fd9e91e5c54bdc1b8c2f470b69"
repo-rev = "master"
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[[Formatting]]
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[[Future]]
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[[Glob]]
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[[HTTP]]
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git-tree-sha1 = "63055ee44b5c2b95ec1921edcf856c60124ff0c3"
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[[InitialValues]]
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[[MbedTLS]]
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[[MbedTLS_jll]]
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[[Transducers]]
deps = ["ArgCheck", "BangBang", "CompositionsBase", "DefineSingletons", "Distributed", "InitialValues", "Logging", "Markdown", "MicroCollections", "Requires", "Setfield", "SplittablesBase", "Tables"]
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Raw
Project.toml
[deps]
BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
Folds = "41a02a25-b8f0-4f67-bc48-60067656b558"
FoldsThreads = "9c68100b-dfe1-47cf-94c8-95104e173443"
Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
Transducers = "28d57a85-8fef-5791-bfe6-a80928e7c999"
VegaLite = "112f6efa-9a02-5b7d-90c0-432ed331239a"
Raw
result.json
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