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perf(reactivity): ports alien-signals #12349

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@johnsoncodehk johnsoncodehk commented Nov 9, 2024

alien-signals(https://github.com/stackblitz/alien-signals) is a research-oriented signal library rewritten based on Vue 3.4's reactivity system. It sets several constraints to ensure the high-performance implementation of a reactivity system. (Currently, it is the fastest implementation among all signal libraries)

This PR ports the https://github.com/stackblitz/alien-signals/blob/master/src/system.ts code to https://github.com/vuejs/core/blob/main/packages/reactivity/src/effect.ts to leverage all the optimizations discovered by alien-signals.

Benefits

  • Lower memory usage: Memory usage is reduced by ~13% (2.3MB -> 2.0MB) when creating a large number of ref, computed, and effect instances.
  • Higher performance: Various performance tests now generally yield better results, especially in scenarios where a large number of computeds are read after changing a ref. Vue 3.5 had significant performance drawbacks in this case (a characteristic of pull-model reactivity systems, it can be reproduced in https://github.com/transitive-bullshit/js-reactivity-benchmark), and the current implementation resolves this issue, achieving over 30x performance improvement (proportional to scale).
  • Better code abstraction: The previous scheduling logic had coupling with external implementations (such as Dep cleanup, debug events, recurse effect handling). The current implementation eliminates these couplings.

Benchmark Results

computed

     name                                                                    hz     min     max    mean     p75     p99    p995    p999     rme  samples
   · create computed                                               6,111,709.97  0.0000  0.3307  0.0002  0.0002  0.0002  0.0002  0.0003  ±0.53%  3055856  [1.28x] ⇑
     create computed                                               4,790,560.55  0.0001  2.8602  0.0002  0.0002  0.0003  0.0003  0.0005  ±1.19%  2395281  (baseline)
   · write ref, don't read computed (without effect)               3,725,946.87  0.0002  0.1777  0.0003  0.0003  0.0003  0.0003  0.0004  ±0.16%  1862974  [1.19x] ⇑
     write ref, don't read computed (without effect)               3,138,437.74  0.0002  1.4873  0.0003  0.0003  0.0004  0.0004  0.0005  ±1.21%  1569219  (baseline)
   · write ref, don't read computed (with effect)                  1,629,737.97  0.0005  0.1867  0.0006  0.0006  0.0007  0.0007  0.0008  ±0.11%   814869  [1.20x] ⇑
     write ref, don't read computed (with effect)                  1,362,345.64  0.0006  0.1455  0.0007  0.0008  0.0008  0.0008  0.0010  ±0.13%   681173  (baseline)
   · write ref, read computed (without effect)                     1,961,824.76  0.0004  0.1808  0.0005  0.0005  0.0005  0.0006  0.0007  ±0.12%   980913  [1.06x] ⇑
     write ref, read computed (without effect)                     1,848,260.85  0.0004  0.1488  0.0005  0.0005  0.0006  0.0006  0.0007  ±0.13%   924131  (baseline)
   · write ref, read computed (with effect)                        1,475,801.43  0.0005  0.2211  0.0007  0.0007  0.0008  0.0008  0.0010  ±0.12%   737901  [1.14x] ⇑
     write ref, read computed (with effect)                        1,296,434.21  0.0007  0.2508  0.0008  0.0008  0.0008  0.0009  0.0011  ±0.16%   648218  (baseline)
   · write ref, don't read 1000 computeds (without effect)         3,300,382.44  0.0002  0.1930  0.0003  0.0003  0.0003  0.0004  0.0004  ±0.14%  1650192  [1.03x] ⇑
     write ref, don't read 1000 computeds (without effect)         3,189,502.88  0.0002  0.1763  0.0003  0.0003  0.0003  0.0004  0.0005  ±0.14%  1594752  (baseline)
   · write ref, don't read 1000 computeds (with multiple effects)      3,222.67  0.3063  0.5532  0.3103  0.3108  0.3488  0.3917  0.5250  ±0.19%     1612  [1.38x] ⇑
     write ref, don't read 1000 computeds (with multiple effects)      2,329.65  0.4206  0.6286  0.4292  0.4292  0.4997  0.5215  0.5671  ±0.19%     1165  (baseline)
   · write ref, don't read 1000 computeds (with single effect)         3,734.95  0.2648  0.3821  0.2677  0.2683  0.2855  0.2986  0.3510  ±0.09%     1868  [1.71x] ⇑
     write ref, don't read 1000 computeds (with single effect)         2,186.19  0.4434  0.6528  0.4574  0.4565  0.5061  0.5221  0.5846  ±0.16%     1094  (baseline)
   · write ref, read 1000 computeds (no effect)                        4,694.97  0.2105  0.3849  0.2130  0.2142  0.2301  0.2382  0.3271  ±0.12%     2348  [1.26x] ⇑
     write ref, read 1000 computeds (no effect)                        3,718.71  0.2292  9.4632  0.2689  0.2329  1.0790  2.5163  6.3315  ±5.98%     1860  (baseline)
   · write ref, read 1000 computeds (with multiple effects)            2,845.64  0.3453  0.6213  0.3514  0.3512  0.4014  0.4358  0.5546  ±0.21%     1423  [1.33x] ⇑
     write ref, read 1000 computeds (with multiple effects)            2,142.70  0.4569  0.7351  0.4667  0.4664  0.5183  0.5565  0.6951  ±0.22%     1072  (baseline)
   · write ref, read 1000 computeds (with single effect)               2,265.62  0.4338  0.9382  0.4414  0.4392  0.5991  0.6087  0.6304  ±0.36%     1133  [1.48x] ⇑
     write ref, read 1000 computeds (with single effect)               1,529.78  0.6415  0.8937  0.6537  0.6526  0.7195  0.7378  0.8937  ±0.18%      765  (baseline)
   · 1000 refs, read 1 computed (without effect)                      19,686.23  0.0490  0.1665  0.0508  0.0495  0.0595  0.0631  0.0935  ±0.16%     9844  [3.41x] ⇑
     1000 refs, read 1 computed (without effect)                       5,775.97  0.1611  0.3445  0.1731  0.1746  0.2057  0.2170  0.2689  ±0.18%     2888  (baseline)
   · 1000 refs, read 1 computed (with effect)                         22,764.26  0.0427  0.1713  0.0439  0.0430  0.0534  0.0585  0.0983  ±0.16%    11383  [3.63x] ⇑
     1000 refs, read 1 computed (with effect)                          6,268.22  0.1492  0.3157  0.1595  0.1620  0.1907  0.2024  0.2408  ±0.18%     3135  (baseline)

effect

     name                                                       hz      min      max     mean      p75      p99     p995     p999     rme  samples
   · single ref invoke                                2,422,374.37   0.0003   0.1300   0.0004   0.0004   0.0005   0.0005   0.0006  ±0.12%  1211188  [1.08x] ⇑
     single ref invoke                                2,253,296.36   0.0003   0.1473   0.0004   0.0005   0.0005   0.0005   0.0006  ±0.15%  1126649  (baseline)
   · create an effect that tracks 1 refs              3,041,716.41   0.0002   0.2316   0.0003   0.0003   0.0004   0.0005   0.0006  ±0.39%  1520859  [1.32x] ⇑
     create an effect that tracks 1 refs              2,305,307.54   0.0003   0.1655   0.0004   0.0004   0.0005   0.0005   0.0008  ±0.32%  1152654  (baseline)
   · create an effect that tracks 10 refs               477,709.54   0.0019   0.2655   0.0021   0.0021   0.0023   0.0025   0.0036  ±0.38%   238855  [1.57x] ⇑
     create an effect that tracks 10 refs               303,939.27   0.0031   0.2318   0.0033   0.0032   0.0035   0.0037   0.0183  ±0.34%   151970  (baseline)
   · create an effect that tracks 100 refs               51,529.46   0.0188   0.2940   0.0194   0.0190   0.0267   0.0342   0.1052  ±0.38%    25765  [1.62x] ⇑
     create an effect that tracks 100 refs               31,753.65   0.0306   0.2372   0.0315   0.0309   0.0464   0.0528   0.1848  ±0.34%    15877  (baseline)
   · create an effect that tracks 1000 refs               5,185.44   0.1884   0.4357   0.1928   0.1896   0.3253   0.3712   0.4210  ±0.41%     2593  [1.65x] ⇑
     create an effect that tracks 1000 refs               3,135.25   0.3067   1.2006   0.3190   0.3107   0.5374   0.7059   1.1851  ±0.83%     1568  (baseline)
   · create and stop an effect that tracks 1 refs     2,643,923.29   0.0003   0.2466   0.0004   0.0004   0.0005   0.0006   0.0008  ±0.40%  1321998  [1.25x] ⇑
     create and stop an effect that tracks 1 refs     2,108,885.94   0.0003   0.1770   0.0005   0.0005   0.0005   0.0006   0.0008  ±0.35%  1054443  (baseline)
   · create and stop an effect that tracks 10 refs      434,027.52   0.0022   0.2420   0.0023   0.0023   0.0024   0.0026   0.0038  ±0.28%   217014  [1.59x] ⇑
     create and stop an effect that tracks 10 refs      272,235.14   0.0035   0.3079   0.0037   0.0036   0.0040   0.0041   0.0193  ±0.36%   136118  (baseline)
   · create and stop an effect that tracks 100 refs      46,683.59   0.0209   0.2881   0.0214   0.0212   0.0246   0.0315   0.0809  ±0.33%    23342  [1.66x] ⇑
     create and stop an effect that tracks 100 refs      28,075.59   0.0343   3.7334   0.0356   0.0348   0.0508   0.0602   0.1706  ±1.48%    14038  (baseline)
   · create and stop an effect that tracks 1000 refs      4,674.21   0.2099   0.5031   0.2139   0.2114   0.2932   0.3995   0.4782  ±0.38%     2338  [1.65x] ⇑
     create and stop an effect that tracks 1000 refs      2,829.92   0.3445   0.5768   0.3534   0.3499   0.4938   0.5118   0.5708  ±0.34%     1415  (baseline)
   · 1 effect, mutate 10 refs                           131,308.76   0.0074   0.2790   0.0076   0.0076   0.0079   0.0081   0.0197  ±0.15%    65655  [2.37x] ⇑
     1 effect, mutate 10 refs                            55,475.14   0.0177   0.1079   0.0180   0.0179   0.0215   0.0318   0.0527  ±0.14%    27738  (baseline)
   · 1 effect, mutate 100 refs                            2,163.50   0.4568   0.8003   0.4622   0.4609   0.5471   0.6069   0.7550  ±0.26%     1082  [3.27x] ⇑
     1 effect, mutate 100 refs                              660.75   1.4944   1.8873   1.5134   1.5197   1.6387   1.7310   1.8873  ±0.24%      331  (baseline)
   · 1 effect, mutate 1000 refs                            23.1906  42.8559  43.6757  43.1209  43.1839  43.6757  43.6757  43.6757  ±0.39%       12  [3.47x] ⇑
     1 effect, mutate 1000 refs                             6.6868   149.16   149.78   149.55   149.71   149.78   149.78   149.78  ±0.10%       10  (baseline)
   · 10 refs branch toggle                            1,186,713.31   0.0004   6.0071   0.0008   0.0010   0.0011   0.0014   0.0015  ±4.92%   593357  [1.75x] ⇑
     10 refs branch toggle                              678,007.23   0.0007   0.2123   0.0015   0.0022   0.0022   0.0023   0.0049  ±0.23%   339004  (baseline)
   · 100 refs branch toggle                             303,335.02   0.0009   0.1054   0.0033   0.0055   0.0057   0.0057   0.0110  ±0.37%   151669  [3.03x] ⇑
     100 refs branch toggle                              99,958.91   0.0029   1.4980   0.0100   0.0166   0.0173   0.0242   0.0396  ±0.88%    49981  (baseline)
   · 1000 refs branch toggle                             33,959.34   0.0069   0.1933   0.0294   0.0513   0.0547   0.0595   0.0819  ±1.14%    16981  [3.26x] ⇑
     1000 refs branch toggle                             10,416.41   0.0265   0.4061   0.0960   0.1623   0.1861   0.2043   0.3517  ±1.97%     5209  (baseline)
   · 1 ref invoking 10 effects                          946,141.80   0.0009   0.0576   0.0011   0.0011   0.0011   0.0012   0.0014  ±0.08%   473071  [1.53x] ⇑
     1 ref invoking 10 effects                          617,154.17   0.0013   2.1592   0.0016   0.0014   0.0020   0.0020   0.0193  ±2.15%   308578  (baseline)
   · 1 ref invoking 100 effects                         137,515.93   0.0069   0.1466   0.0073   0.0073   0.0075   0.0078   0.0228  ±0.13%    68758  [1.51x] ⇑
     1 ref invoking 100 effects                          91,193.89   0.0105   0.2659   0.0110   0.0110   0.0114   0.0187   0.0313  ±0.16%    45597  (baseline)
   · 1 ref invoking 1000 effects                         13,791.02   0.0704   0.1650   0.0725   0.0727   0.0858   0.0947   0.1325  ±0.13%     6896  [1.48x] ⇑
     1 ref invoking 1000 effects                          9,339.78   0.1047   0.1980   0.1071   0.1069   0.1265   0.1379   0.1740  ±0.13%     4670  (baseline)

ref

     name                       hz     min     max    mean     p75     p99    p995    p999     rme  samples
   · create ref       4,648,340.74  0.0001  1.8655  0.0002  0.0002  0.0003  0.0003  0.0004  ±0.89%  2324171  [1.09x] ⇑
     create ref       4,261,204.35  0.0001  0.1899  0.0002  0.0003  0.0003  0.0003  0.0005  ±0.15%  2130603  (baseline)
   · write ref        3,817,925.50  0.0002  0.1143  0.0003  0.0003  0.0003  0.0003  0.0004  ±0.08%  1908963  [1.18x] ⇑
     write ref        3,248,551.04  0.0002  0.2231  0.0003  0.0003  0.0003  0.0004  0.0005  ±0.16%  1624276  (baseline)
   · read ref        11,485,907.61  0.0000  0.1316  0.0001  0.0001  0.0001  0.0001  0.0002  ±0.13%  5742954  [1.02x] ⇑
     read ref        11,264,635.57  0.0000  0.1458  0.0001  0.0001  0.0001  0.0001  0.0002  ±0.18%  5632318  (baseline)
   · write/read ref   3,576,071.66  0.0002  0.2868  0.0003  0.0003  0.0003  0.0003  0.0004  ±0.12%  1788036  [1.33x] ⇑
     write/read ref   2,694,391.71  0.0002  1.0205  0.0004  0.0004  0.0004  0.0005  0.0008  ±0.94%  1347196  (baseline)

Potential Improvements

  • Merging dirtyLevel, canPropagate, pauseLevel, and allowRecurse into one attribute should further reduce memory usage. Reaching the lowest memory usage is not the purpose of this PR, so we will not implement it here currently.

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github-actions bot commented Nov 9, 2024

Size Report

Bundles

File Size Gzip Brotli
runtime-dom.global.prod.js 102 kB (+1.21 kB) 38.1 kB (+153 B) 34.3 kB (+127 B)
vue.global.prod.js 160 kB (+1.26 kB) 58 kB (+144 B) 51.5 kB (+106 B)

Usages

Name Size Gzip Brotli
createApp (CAPI only) 47.6 kB (+713 B) 18.4 kB (+61 B) 16.8 kB (+70 B)
createApp 56 kB (+1.02 kB) 21.4 kB (+137 B) 19.5 kB (+132 B)
createSSRApp 60 kB (+1.02 kB) 23.1 kB (+113 B) 21 kB (+47 B)
defineCustomElement 60.8 kB (+1.02 kB) 23 kB (+133 B) 20.9 kB (+100 B)
overall 69.9 kB (+1.18 kB) 26.5 kB (+140 B) 24.1 kB (+120 B)

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/ecosystem-ci run

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johnsoncodehk commented Nov 13, 2024

Noticed the ref invoking x effects case somehow got slower.

This seems to be a performance regression caused by accessing cross-file variables in Node, it should be fixed by bc3af94 (#12349).

  • On main branch, run vitest bench --project=unit --outputJson=bench.json computed

Also note that when switching to the main branch, change __DEV__ in vitest.config.ts to false for apple to apple comparison.

@johnsoncodehk johnsoncodehk changed the title (PoC) Integrated with alien-signals perf(reactivity): port the reactivity system of alien-signals Nov 13, 2024
@johnsoncodehk johnsoncodehk marked this pull request as ready for review November 13, 2024 09:34
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/ecosystem-ci run

@johnsoncodehk johnsoncodehk changed the title perf(reactivity): port the reactivity system of alien-signals perf(reactivity): ports alien-signals reactivity system Nov 13, 2024
@johnsoncodehk johnsoncodehk changed the title perf(reactivity): ports alien-signals reactivity system perf(reactivity): ports alien-signals system Nov 13, 2024
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A GC regression that computed not used in effect/template cannot be released is fixed in 4114a12 (#12349) (Thanks for @JoviDeCroock bringing it up!)

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@johnsoncodehk this leak is present in alien-signals itself, might be worth tackling there as well for all other consumers of the package.

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@JoviDeCroock Yep! This is the last problem we want to solve in alien-signals.

@johnsoncodehk johnsoncodehk changed the title perf(reactivity): ports alien-signals system perf(reactivity): ports alien-signals Nov 13, 2024
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Removed namespace usage in 571ba05

Previously namespace was used because it somehow showed better perf in benchmarks, but turns out it's because Vitest benchmark currently has overhead for every access of cross-module import binding due to the way modules are evaluated.

For real-world performance, we should be benching against the bundled reactivity module, where module-root level exports are scope-hoisted into local consts. This should result in better perf than namespace access. It also is more minifier friendly and can reduce bundle size increase.

Comparing the benchmark using bundled reactivity.esm-browser.prod.js, before and after 571ba05:

· create computed                                               21,076,617.75  0.0000  0.2428  0.0000  0.0000  0.0001  0.0001  0.0002  ±0.16%  10538309  [1.01x] ⇑
     create computed                                               20,871,461.37  0.0000  0.0939  0.0000  0.0000  0.0001  0.0001  0.0002  ±0.14%  10435731  (baseline)
   · write ref, don't read computed (without effect)               21,270,929.83  0.0000  0.2626  0.0000  0.0000  0.0001  0.0001  0.0002  ±0.22%  10635465  [1.00x] ⇓
     write ref, don't read computed (without effect)               21,352,721.02  0.0000  0.3770  0.0000  0.0000  0.0001  0.0001  0.0001  ±0.28%  10676361  (baseline)
   · write ref, don't read computed (with effect)                  10,561,843.24  0.0000  0.4995  0.0001  0.0001  0.0001  0.0001  0.0002  ±0.29%   5280922  [1.03x] ⇑
     write ref, don't read computed (with effect)                  10,295,067.44  0.0000  0.7905  0.0001  0.0001  0.0001  0.0002  0.0002  ±0.44%   5147534  (baseline)
   · write ref, read computed (without effect)                     13,647,038.01  0.0000  0.2687  0.0001  0.0001  0.0001  0.0001  0.0002  ±0.20%   6823520  [1.01x] ⇑
     write ref, read computed (without effect)                     13,446,011.73  0.0000  0.1222  0.0001  0.0001  0.0001  0.0001  0.0002  ±0.13%   6723006  (baseline)
   · write ref, read computed (with effect)                         9,900,825.62  0.0000  0.2127  0.0001  0.0001  0.0002  0.0002  0.0002  ±0.19%   4950413  [0.98x] ⇓
     write ref, read computed (with effect)                        10,072,543.62  0.0000  0.3119  0.0001  0.0001  0.0001  0.0002  0.0002  ±0.26%   5036273  (baseline)
   · write ref, don't read 1000 computeds (without effect)         20,749,339.38  0.0000  0.4546  0.0000  0.0000  0.0001  0.0001  0.0001  ±0.32%  10374670  [1.00x] ⇑
     write ref, don't read 1000 computeds (without effect)         20,652,327.46  0.0000  0.5293  0.0000  0.0000  0.0001  0.0001  0.0002  ±0.43%  10326164  (baseline)
   · write ref, don't read 1000 computeds (with multiple effects)       8,481.89  0.1150  0.1683  0.1179  0.1190  0.1273  0.1297  0.1494  ±0.08%      4241  [1.08x] ⇑
     write ref, don't read 1000 computeds (with multiple effects)       7,889.51  0.1205  0.1841  0.1268  0.1285  0.1488  0.1511  0.1676  ±0.14%      3945  (baseline)
   · write ref, don't read 1000 computeds (with single effect)         30,897.47  0.0312  0.0958  0.0324  0.0322  0.0406  0.0438  0.0481  ±0.08%     15449  [1.05x] ⇑
     write ref, don't read 1000 computeds (with single effect)         29,380.96  0.0329  0.0605  0.0340  0.0343  0.0378  0.0391  0.0428  ±0.04%     14691  (baseline)
   · write ref, read 1000 computeds (no effect)                        43,131.23  0.0224  0.0852  0.0232  0.0231  0.0297  0.0318  0.0360  ±0.08%     21566  [1.05x] ⇑
     write ref, read 1000 computeds (no effect)                        40,964.36  0.0235  0.0829  0.0244  0.0243  0.0318  0.0335  0.0373  ±0.08%     20483  (baseline)
   · write ref, read 1000 computeds (with multiple effects)             8,546.06  0.1138  0.1759  0.1170  0.1184  0.1287  0.1308  0.1385  ±0.08%      4274  [1.11x] ⇑
     write ref, read 1000 computeds (with multiple effects)             7,727.43  0.1265  0.1966  0.1294  0.1310  0.1427  0.1450  0.1506  ±0.09%      3864  (baseline)
   · write ref, read 1000 computeds (with single effect)               15,886.90  0.0589  0.2281  0.0629  0.0621  0.0745  0.0818  0.2199  ±0.30%      7944  [1.02x] ⇑
     write ref, read 1000 computeds (with single effect)               15,539.78  0.0616  0.1318  0.0644  0.0637  0.0760  0.0765  0.0803  ±0.09%      7770  (baseline)
   · 1000 refs, read 1 computed (without effect)                      163,839.85  0.0054  0.1293  0.0061  0.0070  0.0075  0.0086  0.0108  ±0.10%     81920  [1.04x] ⇑
     1000 refs, read 1 computed (without effect)                      157,879.98  0.0055  0.0657  0.0063  0.0073  0.0091  0.0107  0.0163  ±0.11%     78941  (baseline)
   · 1000 refs, read 1 computed (with effect)                         186,830.01  0.0051  0.0250  0.0054  0.0054  0.0060  0.0067  0.0085  ±0.03%     93416  [1.03x] ⇑
     1000 refs, read 1 computed (with effect)                         180,595.90  0.0052  0.0614  0.0055  0.0055  0.0068  0.0093  0.0151  ±0.08%     90298  (baseline)

@yyx990803 yyx990803 mentioned this pull request Nov 14, 2024
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@yyx990803 yyx990803 changed the base branch from main to minor November 14, 2024 00:14
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6 participants