Created attachment 462692 [details] array-map.mjs A lot of modern JS uses .map and .forEach. Many codebases use these functions more frequently than for loops. For small array literals with constant values, V8 is about 3x faster than what JSC is doing. I've attached a benchmark script Bun using a copy of JSC from September 17th, 2022: cpu: Apple M1 Max runtime: bun 0.1.14 (arm64-darwin) benchmark time (avg) (min … max) p75 p99 p995 ------------------------------------------------------------- ----------------------------- Array.map x 0 50.91 ns/iter (45.7 ns … 274.74 ns) 47.35 ns 113.15 ns 131.34 ns Array.map x 1 55.15 ns/iter (51.91 ns … 453.84 ns) 52.44 ns 101.3 ns 119.57 ns Array.map x 2 58.1 ns/iter (51.91 ns … 183.54 ns) 52.77 ns 116.05 ns 151.96 ns Array.map x 3 52.16 ns/iter (46.56 ns … 152.19 ns) 47.15 ns 105.3 ns 125.74 ns Array.map x 4 78.14 ns/iter (51.94 ns … 164.94 ns) 83.45 ns 129.8 ns 139.77 ns Array.map x 5 54.94 ns/iter (51.36 ns … 226.1 ns) 53.67 ns 101.87 ns 109.88 ns Array.map x 6 55.97 ns/iter (51.9 ns … 257.6 ns) 54.43 ns 105.08 ns 165.98 ns Array.map x 7 55.5 ns/iter (51.84 ns … 162.09 ns) 54.43 ns 102.56 ns 112.98 ns Array.map x 8 57.03 ns/iter (51.84 ns … 476.93 ns) 54.97 ns 121.98 ns 148.4 ns Array.map x 9 56.4 ns/iter (51.85 ns … 370.1 ns) 54.74 ns 116.15 ns 131.97 ns Array.map x 10 56.05 ns/iter (51.86 ns … 212.73 ns) 54.53 ns 103.42 ns 108.92 ns Array.map x 11 55.92 ns/iter (51.86 ns … 187.18 ns) 54.53 ns 103.99 ns 133.61 ns Array.map x 12 55.93 ns/iter (51.88 ns … 272.41 ns) 54.48 ns 107.03 ns 120.77 ns Array.map x 13 56.08 ns/iter (51.86 ns … 174.88 ns) 54.64 ns 115.71 ns 127.24 ns Array.map x 14 55.97 ns/iter (51.88 ns … 191.69 ns) 54.55 ns 110.09 ns 119.5 ns Array.map x 15 55.87 ns/iter (51.86 ns … 357.33 ns) 54.51 ns 102.73 ns 111.7 ns Array.map x 16 55.98 ns/iter (51.85 ns … 181.74 ns) 54.52 ns 106.4 ns 117.05 ns Array.map x 17 56.25 ns/iter (51.88 ns … 380.5 ns) 54.54 ns 106.85 ns 117.7 ns Array.map x 18 55.41 ns/iter (51.85 ns … 127.13 ns) 54.54 ns 97.5 ns 103.66 ns Array.map x 19 55.73 ns/iter (51.87 ns … 267.85 ns) 54.61 ns 100.46 ns 106.79 ns inline Array.map x 0 31.8 ns/iter (28.91 ns … 239.6 ns) 31.2 ns 73.13 ns 84.8 ns inline Array.map x 1 33.6 ns/iter (30.74 ns … 106.19 ns) 33.89 ns 77.63 ns 90.15 ns inline Array.map x 2 34.59 ns/iter (31.94 ns … 239.49 ns) 34.82 ns 75.1 ns 85.36 ns inline Array.map x 3 36.49 ns/iter (33.39 ns … 151.94 ns) 36.17 ns 79.87 ns 93.93 ns inline Array.map x 4 38.94 ns/iter (35.6 ns … 295.58 ns) 38.79 ns 87.57 ns 93.78 ns inline Array.map x 5 40.37 ns/iter (36.88 ns … 268.68 ns) 39.93 ns 92.47 ns 97.58 ns inline Array.map x 6 43.33 ns/iter (39.58 ns … 272.25 ns) 42.77 ns 93.85 ns 101.4 ns inline Array.map x 7 44.73 ns/iter (40.56 ns … 505.39 ns) 43.34 ns 99.42 ns 138.26 ns inline Array.map x 8 41.82 ns/iter (37.98 ns … 161.33 ns) 41.22 ns 89.9 ns 98.47 ns inline Array.map x 9 42.2 ns/iter (38.85 ns … 104.19 ns) 41.62 ns 87.07 ns 92.6 ns inline Array.map x 10 54.53 ns/iter (49.97 ns … 185.29 ns) 53.61 ns 105.6 ns 113.41 ns inline Array.map x 11 55.63 ns/iter (50.92 ns … 251.47 ns) 54.47 ns 103.83 ns 173.58 ns inline Array.map x 12 56.66 ns/iter (51.74 ns … 278.88 ns) 56.14 ns 105.58 ns 107.75 ns inline Array.map x 13 57.31 ns/iter (52.67 ns … 212.94 ns) 56.72 ns 103.72 ns 115.22 ns inline Array.map x 14 53.85 ns/iter (48.2 ns … 203.39 ns) 54 ns 107.08 ns 115.79 ns inline Array.map x 15 55.64 ns/iter (48.61 ns … 265.81 ns) 55.93 ns 107.91 ns 114.97 ns inline Array.map x 16 56.43 ns/iter (49.25 ns … 408.1 ns) 55.23 ns 111.18 ns 137.67 ns inline Array.map x 17 57.4 ns/iter (50.05 ns … 143.59 ns) 56.14 ns 110.2 ns 116.92 ns inline Array.map x 18 58.43 ns/iter (51.64 ns … 267.74 ns) 58.65 ns 112.74 ns 121.68 ns inline Array.map x 19 59.89 ns/iter (51.9 ns … 476.5 ns) 59.19 ns 109.14 ns 112.25 ns Node v18.9.1: benchmark time (avg) (min … max) p75 p99 p995 ------------------------------------------------------------- ----------------------------- Array.map x 0 34.04 ns/iter (29.44 ns … 467.84 ns) 33.85 ns 42.88 ns 43.56 ns Array.map x 1 40.11 ns/iter (30.09 ns … 244.13 ns) 41.4 ns 109.83 ns 130.5 ns Array.map x 2 35.94 ns/iter (25.49 ns … 533.06 ns) 39.04 ns 47.24 ns 47.97 ns Array.map x 3 34.42 ns/iter (28.05 ns … 42.55 ns) 35.67 ns 39.95 ns 40.68 ns Array.map x 4 32.94 ns/iter (28 ns … 45.35 ns) 33.4 ns 38.43 ns 40.02 ns Array.map x 5 36.87 ns/iter (28.02 ns … 51.1 ns) 38.55 ns 45.81 ns 47.34 ns Array.map x 6 34.6 ns/iter (28.05 ns … 47.17 ns) 36.35 ns 41.41 ns 42.43 ns Array.map x 7 32.59 ns/iter (28 ns … 40.6 ns) 32.58 ns 37.35 ns 38.05 ns Array.map x 8 32.49 ns/iter (28.05 ns … 45.3 ns) 32.5 ns 36.84 ns 37.49 ns Array.map x 9 32.61 ns/iter (28 ns … 49.33 ns) 32.5 ns 38.6 ns 42.77 ns Array.map x 10 32.45 ns/iter (28.01 ns … 39.56 ns) 32.42 ns 36.15 ns 36.83 ns Array.map x 11 34.8 ns/iter (28.02 ns … 404.71 ns) 34.34 ns 66.5 ns 84.86 ns Array.map x 12 32.45 ns/iter (28.02 ns … 46.71 ns) 32.46 ns 35.9 ns 37.15 ns Array.map x 13 32.37 ns/iter (27.99 ns … 41.37 ns) 32.42 ns 37.14 ns 38.39 ns Array.map x 14 32.52 ns/iter (27.99 ns … 42.66 ns) 32.52 ns 36.39 ns 38.6 ns Array.map x 15 31.69 ns/iter (28.01 ns … 55.96 ns) 32.58 ns 34.9 ns 39.68 ns Array.map x 16 30.77 ns/iter (28.13 ns … 40.82 ns) 33.07 ns 35.27 ns 36.27 ns Array.map x 17 30.73 ns/iter (28.13 ns … 40.67 ns) 33 ns 35.59 ns 36.96 ns Array.map x 18 30.77 ns/iter (28.13 ns … 39.08 ns) 33.2 ns 34.04 ns 34.35 ns Array.map x 19 31.03 ns/iter (28.11 ns … 46.27 ns) 33.08 ns 37.92 ns 42.6 ns inline Array.map x 0 7.59 ns/iter (6.05 ns … 415.02 ns) 10.49 ns 11.85 ns 13.33 ns inline Array.map x 1 6.01 ns/iter (5.25 ns … 20.8 ns) 5.45 ns 10.9 ns 11.81 ns inline Array.map x 2 7.41 ns/iter (6.56 ns … 15.85 ns) 6.75 ns 11.69 ns 11.84 ns inline Array.map x 3 9.02 ns/iter (8.1 ns … 22.63 ns) 8.31 ns 13.24 ns 13.82 ns inline Array.map x 4 11.25 ns/iter (10.13 ns … 25.14 ns) 10.54 ns 16.12 ns 17.26 ns inline Array.map x 5 12.33 ns/iter (10.62 ns … 22.12 ns) 11.62 ns 16.96 ns 17.82 ns inline Array.map x 6 13.37 ns/iter (11.57 ns … 27.57 ns) 12.72 ns 17.59 ns 18.2 ns inline Array.map x 7 14.45 ns/iter (13.08 ns … 29.82 ns) 17.48 ns 19.14 ns 20.86 ns inline Array.map x 8 15.47 ns/iter (14.03 ns … 25.82 ns) 18.61 ns 19.32 ns 20.18 ns inline Array.map x 9 16.58 ns/iter (15 ns … 33.03 ns) 19.65 ns 20.6 ns 21.1 ns inline Array.map x 10 17.6 ns/iter (15.88 ns … 28.53 ns) 20.45 ns 22.87 ns 23.76 ns inline Array.map x 11 18.26 ns/iter (16.79 ns … 51.02 ns) 21.28 ns 24.35 ns 25.29 ns inline Array.map x 12 18.79 ns/iter (17.72 ns … 35.87 ns) 17.79 ns 23.95 ns 24.26 ns inline Array.map x 13 19.9 ns/iter (18.65 ns … 33.07 ns) 19.28 ns 26.57 ns 29.35 ns inline Array.map x 14 20.79 ns/iter (19.58 ns … 31.04 ns) 19.68 ns 25.87 ns 26.63 ns inline Array.map x 15 21.73 ns/iter (20.52 ns … 40.35 ns) 20.59 ns 26.63 ns 27.52 ns inline Array.map x 16 22.82 ns/iter (21.45 ns … 35.67 ns) 22.2 ns 29.01 ns 30.38 ns inline Array.map x 17 23.75 ns/iter (22.39 ns … 34.28 ns) 22.57 ns 28.8 ns 29.43 ns inline Array.map x 18 24.75 ns/iter (23.32 ns … 35.58 ns) 23.55 ns 29.62 ns 30.4 ns inline Array.map x 19 25.69 ns/iter (24.25 ns … 36.99 ns) 25.53 ns 30.86 ns 31.65 ns
<rdar://problem/100541275>
WIP cpu: unknown runtime: unknown (unknown) benchmark time (avg) (min … max) p75 p99 p995 ------------------------------------------------------------- ----------------------------- Array.map x 0 28.49 ns/iter (26.84 ns … 148.08 ns) 27.63 ns 59.3 ns 76.17 ns Array.map x 1 33.21 ns/iter (31.63 ns … 97.94 ns) 32.53 ns 62.02 ns 83.18 ns Array.map x 2 32.17 ns/iter (27.21 ns … 130.01 ns) 31.69 ns 73.57 ns 78.73 ns Array.map x 3 45.48 ns/iter (27.2 ns … 127.62 ns) 69.28 ns 81.28 ns 98.59 ns Array.map x 4 28.96 ns/iter (27.14 ns … 94.2 ns) 28.05 ns 64.62 ns 76.08 ns Array.map x 5 28.55 ns/iter (27.17 ns … 91.72 ns) 28.03 ns 39 ns 64.9 ns Array.map x 6 28.46 ns/iter (27.17 ns … 80.81 ns) 28.04 ns 39.17 ns 57.07 ns Array.map x 7 28.88 ns/iter (27.17 ns … 93.39 ns) 28.1 ns 62.61 ns 72.78 ns Array.map x 8 29.12 ns/iter (27.18 ns … 161.94 ns) 28.07 ns 67.97 ns 82.15 ns Array.map x 9 28.59 ns/iter (27.18 ns … 85.14 ns) 28.05 ns 47 ns 64.41 ns Array.map x 10 28.52 ns/iter (27.19 ns … 78.88 ns) 28.09 ns 39.6 ns 58.16 ns Array.map x 11 29.13 ns/iter (27.17 ns … 110.19 ns) 28.13 ns 79.15 ns 84.6 ns Array.map x 12 29.03 ns/iter (27.15 ns … 91.61 ns) 28.22 ns 65.89 ns 80.31 ns Array.map x 13 29.14 ns/iter (27.18 ns … 93.42 ns) 28.17 ns 69.51 ns 82.66 ns Array.map x 14 29.16 ns/iter (27.16 ns … 99.3 ns) 28.18 ns 70.8 ns 82.09 ns Array.map x 15 29.07 ns/iter (27.18 ns … 94.77 ns) 28.15 ns 65.42 ns 81.82 ns Array.map x 16 29.27 ns/iter (27.17 ns … 97.29 ns) 28.2 ns 71.23 ns 79.35 ns Array.map x 17 29.23 ns/iter (27.19 ns … 97.42 ns) 28.23 ns 67.93 ns 76.22 ns Array.map x 18 29.18 ns/iter (27.17 ns … 91.88 ns) 28.22 ns 71.79 ns 80.78 ns Array.map x 19 29.26 ns/iter (27.2 ns … 94.75 ns) 28.17 ns 71.42 ns 81.85 ns inline Array.map x 0 32.57 ns/iter (31.2 ns … 84.23 ns) 32.45 ns 41.88 ns 47.78 ns inline Array.map x 1 32.66 ns/iter (31.48 ns … 101.39 ns) 32.6 ns 42.28 ns 43.43 ns inline Array.map x 2 33.92 ns/iter (32.6 ns … 91.01 ns) 33.83 ns 44.92 ns 58.12 ns inline Array.map x 3 34.96 ns/iter (33.48 ns … 103.55 ns) 34.86 ns 45.21 ns 54.17 ns inline Array.map x 4 37.74 ns/iter (35.86 ns … 95.65 ns) 37.72 ns 48.17 ns 59.15 ns inline Array.map x 5 38.56 ns/iter (36.45 ns … 100.56 ns) 38.18 ns 54.9 ns 74.98 ns inline Array.map x 6 29.37 ns/iter (28.24 ns … 51.83 ns) 29.28 ns 38.95 ns 39.67 ns inline Array.map x 7 30.77 ns/iter (29.32 ns … 56.58 ns) 30.72 ns 40.22 ns 40.66 ns inline Array.map x 8 27.2 ns/iter (25.83 ns … 82.72 ns) 27.17 ns 37.07 ns 37.49 ns inline Array.map x 9 27.97 ns/iter (26.78 ns … 52.23 ns) 27.91 ns 37.84 ns 38.38 ns inline Array.map x 10 34.38 ns/iter (32.41 ns … 68.93 ns) 34.26 ns 44.48 ns 44.83 ns inline Array.map x 11 36.91 ns/iter (34.84 ns … 79.72 ns) 36.84 ns 47.31 ns 47.94 ns inline Array.map x 12 36.76 ns/iter (34.66 ns … 111.31 ns) 36.54 ns 46.86 ns 47.39 ns inline Array.map x 13 32.41 ns/iter (30.93 ns … 69.17 ns) 32.26 ns 43.06 ns 43.51 ns inline Array.map x 14 33.86 ns/iter (32.17 ns … 76.42 ns) 33.71 ns 43.96 ns 44.37 ns inline Array.map x 15 34.65 ns/iter (33.05 ns … 68.21 ns) 34.45 ns 44.38 ns 44.65 ns inline Array.map x 16 35.84 ns/iter (34.27 ns … 58.6 ns) 35.66 ns 45.48 ns 45.77 ns inline Array.map x 17 36.43 ns/iter (34.9 ns … 61.27 ns) 36.23 ns 46.1 ns 46.3 ns inline Array.map x 18 37.62 ns/iter (36.07 ns … 93.94 ns) 37.4 ns 47.55 ns 47.75 ns inline Array.map x 19 38.46 ns/iter (36.96 ns … 63.12 ns) 38.29 ns 47.67 ns 48.23 ns
Probably this is good enough since non-inline one is more important use case than inline case. inline one can be improved if we introduce a bit more complicated MovHint analysis. benchmark time (avg) (min … max) p75 p99 p995 ------------------------------------------------------------- ----------------------------- Array.map x 0 24.54 ns/iter (22.94 ns … 131.96 ns) 23.7 ns 52.89 ns 72.85 ns Array.map x 1 29.48 ns/iter (28.38 ns … 91.36 ns) 29.17 ns 39.09 ns 40.02 ns Array.map x 2 27.35 ns/iter (23.62 ns … 108.33 ns) 24.51 ns 68.3 ns 70.45 ns Array.map x 3 39.27 ns/iter (23.61 ns … 136.4 ns) 64.96 ns 76.57 ns 78.4 ns Array.map x 4 24.36 ns/iter (23.29 ns … 49.6 ns) 24.05 ns 34.45 ns 34.77 ns Array.map x 5 24.56 ns/iter (23.29 ns … 76.57 ns) 24.07 ns 36.74 ns 50.33 ns Array.map x 6 24.4 ns/iter (23.31 ns … 35.53 ns) 24.1 ns 34.31 ns 34.61 ns Array.map x 7 24.61 ns/iter (23.29 ns … 84.06 ns) 24.1 ns 34.63 ns 49.02 ns Array.map x 8 24.47 ns/iter (23.29 ns … 65.72 ns) 24.13 ns 34.63 ns 36.55 ns Array.map x 9 24.39 ns/iter (23.27 ns … 35.66 ns) 24.11 ns 34.44 ns 34.56 ns Array.map x 10 24.46 ns/iter (23.28 ns … 68.06 ns) 24.13 ns 34.26 ns 34.59 ns Array.map x 11 24.45 ns/iter (23.28 ns … 87.8 ns) 24.17 ns 34.46 ns 34.82 ns Array.map x 12 24.5 ns/iter (23.28 ns … 70.95 ns) 24.16 ns 34.5 ns 35.24 ns Array.map x 13 24.47 ns/iter (23.28 ns … 75.69 ns) 24.12 ns 34.26 ns 34.57 ns Array.map x 14 24.54 ns/iter (23.29 ns … 89.96 ns) 24.14 ns 34.45 ns 35.22 ns Array.map x 15 24.47 ns/iter (23.28 ns … 57.91 ns) 24.19 ns 34.42 ns 34.66 ns Array.map x 16 24.62 ns/iter (23.29 ns … 69.3 ns) 24.22 ns 34.65 ns 49 ns Array.map x 17 24.6 ns/iter (23.27 ns … 73.38 ns) 24.18 ns 34.9 ns 43.3 ns Array.map x 18 24.65 ns/iter (23.29 ns … 90.89 ns) 24.2 ns 35.15 ns 42.95 ns Array.map x 19 24.58 ns/iter (23.28 ns … 80.27 ns) 24.21 ns 34.79 ns 37.04 ns inline Array.map x 0 19.7 ns/iter (18.96 ns … 33.95 ns) 19.6 ns 28.68 ns 29.1 ns inline Array.map x 1 23.67 ns/iter (22.77 ns … 53.31 ns) 23.57 ns 33.13 ns 33.54 ns inline Array.map x 2 24.75 ns/iter (23.66 ns … 66.57 ns) 24.56 ns 35.31 ns 35.83 ns inline Array.map x 3 26.4 ns/iter (24.76 ns … 113.46 ns) 25.85 ns 50.35 ns 55.89 ns inline Array.map x 4 26.9 ns/iter (25.72 ns … 61.44 ns) 26.7 ns 36.27 ns 36.78 ns inline Array.map x 5 26.71 ns/iter (25.53 ns … 77.83 ns) 26.63 ns 36.52 ns 37.21 ns inline Array.map x 6 28.69 ns/iter (27.15 ns … 61.93 ns) 28.81 ns 38.05 ns 38.55 ns inline Array.map x 7 32.51 ns/iter (30.23 ns … 77.6 ns) 33 ns 44.39 ns 44.99 ns inline Array.map x 8 26.38 ns/iter (25.42 ns … 94.17 ns) 26.2 ns 35.94 ns 36.53 ns inline Array.map x 9 26.95 ns/iter (26.03 ns … 48.96 ns) 26.85 ns 36.67 ns 37.02 ns inline Array.map x 10 29.16 ns/iter (28.09 ns … 54.53 ns) 28.98 ns 38.25 ns 38.58 ns inline Array.map x 11 30.03 ns/iter (29 ns … 52.77 ns) 29.88 ns 38.81 ns 39.3 ns inline Array.map x 12 31.15 ns/iter (30.15 ns … 69.39 ns) 30.95 ns 39.96 ns 40.58 ns inline Array.map x 13 31.98 ns/iter (30.96 ns … 54.88 ns) 31.78 ns 41.58 ns 41.92 ns inline Array.map x 14 33.01 ns/iter (31.87 ns … 49.52 ns) 32.68 ns 42.47 ns 42.64 ns inline Array.map x 15 33.81 ns/iter (32.65 ns … 58.02 ns) 33.47 ns 43.13 ns 43.36 ns inline Array.map x 16 35.03 ns/iter (33.81 ns … 62.9 ns) 34.71 ns 44.63 ns 45.16 ns inline Array.map x 17 35.81 ns/iter (34.46 ns … 118.63 ns) 35.45 ns 45.33 ns 45.87 ns inline Array.map x 18 36.77 ns/iter (35.35 ns … 58.17 ns) 36.57 ns 46.85 ns 47.06 ns inline Array.map x 19 37.95 ns/iter (36.56 ns … 65.8 ns) 37.68 ns 48.07 ns 48.39 ns
Pull request: https://github.com/WebKit/WebKit/pull/4909
Committed 255105@main (3c9c31d0fd7c): <https://commits.webkit.org/255105@main> Reviewed commits have been landed. Closing PR #4909 and removing active labels.