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MiraiMC/patches/server/0098-c2me-vectorizations.vectorize_noise.patch
Etil a564c20639 Update c2me: optimization.math
2022-01-16 18:31:47 +01:00

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From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
From: ishland <ishlandmc@yeah.net>
Date: Tue, 21 Sep 2021 10:37:45 +0200
Subject: [PATCH] c2me: vectorizations.vectorize_noise
Original code by RelativityMC, licensed under MIT
You can find the original code on https://github.com/RelativityMC/C2ME-fabric (Yarn mappings)
diff --git a/src/main/java/com/ishland/c2me/libs/vectorized_algorithms/VectorizedAlgorithms.java b/src/main/java/com/ishland/c2me/libs/vectorized_algorithms/VectorizedAlgorithms.java
new file mode 100644
index 0000000000000000000000000000000000000000..77aed653efa723b17e1943e40202954d730f4b47
--- /dev/null
+++ b/src/main/java/com/ishland/c2me/libs/vectorized_algorithms/VectorizedAlgorithms.java
@@ -0,0 +1,9 @@
+package com.ishland.c2me.libs.vectorized_algorithms;
+
+public class VectorizedAlgorithms {
+
+ public static double perlinNoiseVectorized(byte[] p, int sectionX, int sectionY, int sectionZ, double localX, double localY, double localZ, double fadeLocalX) {
+ return VectorizedPerlinNoise.sample(p, sectionX, sectionY, sectionZ, localX, localY, localZ, fadeLocalX);
+ }
+
+}
diff --git a/src/main/java/com/ishland/c2me/libs/vectorized_algorithms/VectorizedPerlinNoise.java b/src/main/java/com/ishland/c2me/libs/vectorized_algorithms/VectorizedPerlinNoise.java
new file mode 100644
index 0000000000000000000000000000000000000000..6679e557f4a3c7dbe88c77c605c97ff673425d7e
--- /dev/null
+++ b/src/main/java/com/ishland/c2me/libs/vectorized_algorithms/VectorizedPerlinNoise.java
@@ -0,0 +1,115 @@
+package com.ishland.c2me.libs.vectorized_algorithms;
+
+import jdk.incubator.vector.DoubleVector;
+import jdk.incubator.vector.VectorSpecies;
+
+public class VectorizedPerlinNoise {
+
+ protected static final int[][] GRADIENTS = new int[][]{{1, 1, 0}, {-1, 1, 0}, {1, -1, 0}, {-1, -1, 0}, {1, 0, 1}, {-1, 0, 1}, {1, 0, -1}, {-1, 0, -1}, {0, 1, 1}, {0, -1, 1}, {0, 1, -1}, {0, -1, -1}, {1, 1, 0}, {0, -1, 1}, {-1, 1, 0}, {0, -1, -1}};
+ private static final VectorSpecies<Double> speciesPreferred = DoubleVector.SPECIES_PREFERRED;
+ private static final VectorSpecies<Double> speciesGrad = speciesPreferred.length() > 8 ? DoubleVector.SPECIES_512 : speciesPreferred;
+ private static final VectorSpecies<Double> speciesPerlinFade = speciesPreferred.length() > 4 ? DoubleVector.SPECIES_256 : speciesPreferred;
+
+ static {
+ System.out.println("Using vector size of " + speciesGrad.vectorBitSize() + " bits for grad()");
+ System.out.println("Using vector size of " + speciesPerlinFade.vectorBitSize() + " bits for perlinFade()");
+ }
+
+ private static double lerp(double delta, double start, double end) {
+ return start + delta * (end - start);
+ }
+
+ static double sample(byte[] p, int sectionX, int sectionY, int sectionZ, double localX, double localY, double localZ, double fadeLocalX) {
+ int i = p[sectionX & 0xFF] & 255;
+ int j = p[sectionX + 1 & 0xFF] & 255;
+ int k = p[i + sectionY & 0xFF] & 255;
+ int l = p[i + sectionY + 1 & 0xFF] & 255;
+ int m = p[j + sectionY & 0xFF] & 255;
+ int n = p[j + sectionY + 1 & 0xFF] & 255;
+
+ // grad ops
+ double[] gradX = new double[] {
+ GRADIENTS[p[k + sectionZ & 0xFF] & 15][0],
+ GRADIENTS[p[m + sectionZ & 0xFF] & 15][0],
+ GRADIENTS[p[l + sectionZ & 0xFF] & 15][0],
+ GRADIENTS[p[n + sectionZ & 0xFF] & 15][0],
+ GRADIENTS[p[k + sectionZ + 1 & 0xFF] & 15][0],
+ GRADIENTS[p[m + sectionZ + 1 & 0xFF] & 15][0],
+ GRADIENTS[p[l + sectionZ + 1 & 0xFF] & 15][0],
+ GRADIENTS[p[n + sectionZ + 1 & 0xFF] & 15][0],
+ };
+ double[] mulX = new double[] {
+ localX, localX - 1.0, localX, localX - 1.0,
+ localX, localX - 1.0, localX, localX - 1.0,
+ };
+ double[] gradY = new double[] {
+ GRADIENTS[p[k + sectionZ & 0xFF] & 15][1],
+ GRADIENTS[p[m + sectionZ & 0xFF] & 15][1],
+ GRADIENTS[p[l + sectionZ & 0xFF] & 15][1],
+ GRADIENTS[p[n + sectionZ & 0xFF] & 15][1],
+ GRADIENTS[p[k + sectionZ + 1 & 0xFF] & 15][1],
+ GRADIENTS[p[m + sectionZ + 1 & 0xFF] & 15][1],
+ GRADIENTS[p[l + sectionZ + 1 & 0xFF] & 15][1],
+ GRADIENTS[p[n + sectionZ + 1 & 0xFF] & 15][1],
+ };
+ double[] mulY = new double[] {
+ localY, localY, localY - 1.0, localY - 1.0,
+ localY, localY, localY - 1.0, localY - 1.0,
+ };
+ double[] gradZ = new double[] {
+ GRADIENTS[p[k + sectionZ & 0xFF] & 15][2],
+ GRADIENTS[p[m + sectionZ & 0xFF] & 15][2],
+ GRADIENTS[p[l + sectionZ & 0xFF] & 15][2],
+ GRADIENTS[p[n + sectionZ & 0xFF] & 15][2],
+ GRADIENTS[p[k + sectionZ + 1 & 0xFF] & 15][2],
+ GRADIENTS[p[m + sectionZ + 1 & 0xFF] & 15][2],
+ GRADIENTS[p[l + sectionZ + 1 & 0xFF] & 15][2],
+ GRADIENTS[p[n + sectionZ + 1 & 0xFF] & 15][2],
+ };
+ double[] mulZ = new double[] {
+ localZ, localZ, localZ, localZ,
+ localZ - 1.0, localZ - 1.0, localZ - 1.0, localZ - 1.0,
+ };
+
+ double[] gradResArray = new double[8];
+ for (int i1 = 0; i1 < gradX.length; i1 += speciesGrad.length()) {
+ final DoubleVector gradXVector = DoubleVector.fromArray(speciesGrad, gradX, i1);
+ final DoubleVector mulXVector = DoubleVector.fromArray(speciesGrad, mulX, i1);
+ final DoubleVector resX = gradXVector.mul(mulXVector);
+ final DoubleVector gradYVector = DoubleVector.fromArray(speciesGrad, gradY, i1);
+ final DoubleVector mulYVector = DoubleVector.fromArray(speciesGrad, mulY, i1);
+ final DoubleVector resY = gradYVector.mul(mulYVector);
+ final DoubleVector gradZVector = DoubleVector.fromArray(speciesGrad, gradZ, i1);
+ final DoubleVector mulZVector = DoubleVector.fromArray(speciesGrad, mulZ, i1);
+ final DoubleVector resZ = gradZVector.mul(mulZVector);
+ final DoubleVector res = resX.add(resY).add(resZ);
+ res.intoArray(gradResArray, i1);
+ }
+
+ // fade ops
+ // perlinFade(value): value * value * value * (value * (value * 6.0 - 15.0) + 10.0)
+ final double[] fades = new double[]{localX, fadeLocalX, localZ, 0.0};
+ final double[] fadeResArray = new double[4];
+ for (int i1 = 0; i1 < fades.length; i1 += speciesPerlinFade.length()) {
+ final DoubleVector vector = DoubleVector.fromArray(speciesPerlinFade, fades, i1);
+ final DoubleVector res = vector
+ .mul(6.0)
+ .add(-15.0)
+ .mul(vector)
+ .add(10.0)
+ .mul(vector)
+ .mul(vector)
+ .mul(vector);
+ res.intoArray(fadeResArray, i1);
+ }
+
+ // lerp(delta, start, end): start + delta * (end - start)
+
+ return lerp(
+ fadeResArray[2],
+ lerp(fadeResArray[1], lerp(fadeResArray[0], gradResArray[0], gradResArray[1]), lerp(fadeResArray[0], gradResArray[2], gradResArray[3])),
+ lerp(fadeResArray[1], lerp(fadeResArray[0], gradResArray[4], gradResArray[5]), lerp(fadeResArray[0], gradResArray[6], gradResArray[7]))
+ );
+ }
+
+}
diff --git a/src/main/java/net/minecraft/world/level/levelgen/synth/ImprovedNoise.java b/src/main/java/net/minecraft/world/level/levelgen/synth/ImprovedNoise.java
index de5ab4040204e63efd4c536106cc83f7b15c90a7..026848b6e3ccf68e5d536f79f1a025f7f8352fe2 100644
--- a/src/main/java/net/minecraft/world/level/levelgen/synth/ImprovedNoise.java
+++ b/src/main/java/net/minecraft/world/level/levelgen/synth/ImprovedNoise.java
@@ -1,5 +1,6 @@
package net.minecraft.world.level.levelgen.synth;
+import com.ishland.c2me.libs.vectorized_algorithms.VectorizedAlgorithms; // Mirai
import com.google.common.annotations.VisibleForTesting;
import net.minecraft.util.Mth;
import net.minecraft.world.level.levelgen.RandomSource;
@@ -88,26 +89,36 @@ public final class ImprovedNoise {
return this.p[hash & 255] & 255;
}
+ // Mirai start
+ /**
+ * @author ishland
+ * @reason vectorized perlin
+ */
private double sampleAndLerp(int sectionX, int sectionY, int sectionZ, double localX, double localY, double localZ, double fadeLocalX) {
- int i = this.p(sectionX);
- int j = this.p(sectionX + 1);
- int k = this.p(i + sectionY);
- int l = this.p(i + sectionY + 1);
- int m = this.p(j + sectionY);
- int n = this.p(j + sectionY + 1);
- double d = gradDot(this.p(k + sectionZ), localX, localY, localZ);
- double e = gradDot(this.p(m + sectionZ), localX - 1.0D, localY, localZ);
- double f = gradDot(this.p(l + sectionZ), localX, localY - 1.0D, localZ);
- double g = gradDot(this.p(n + sectionZ), localX - 1.0D, localY - 1.0D, localZ);
- double h = gradDot(this.p(k + sectionZ + 1), localX, localY, localZ - 1.0D);
- double o = gradDot(this.p(m + sectionZ + 1), localX - 1.0D, localY, localZ - 1.0D);
- double p = gradDot(this.p(l + sectionZ + 1), localX, localY - 1.0D, localZ - 1.0D);
- double q = gradDot(this.p(n + sectionZ + 1), localX - 1.0D, localY - 1.0D, localZ - 1.0D);
- double r = Mth.smoothstep(localX);
- double s = Mth.smoothstep(fadeLocalX);
- double t = Mth.smoothstep(localZ);
- return Mth.lerp3(r, s, t, d, e, f, g, h, o, p, q);
+ if (wtf.etil.mirai.MiraiConfig.vectorizedPerlinNoise) {
+ return VectorizedAlgorithms.perlinNoiseVectorized(p, sectionX, sectionY, sectionZ, localX, localY, localZ, fadeLocalX);
+ } else {
+ int i = this.p(sectionX);
+ int j = this.p(sectionX + 1);
+ int k = this.p(i + sectionY);
+ int l = this.p(i + sectionY + 1);
+ int m = this.p(j + sectionY);
+ int n = this.p(j + sectionY + 1);
+ double d = gradDot(this.p(k + sectionZ), localX, localY, localZ);
+ double e = gradDot(this.p(m + sectionZ), localX - 1.0D, localY, localZ);
+ double f = gradDot(this.p(l + sectionZ), localX, localY - 1.0D, localZ);
+ double g = gradDot(this.p(n + sectionZ), localX - 1.0D, localY - 1.0D, localZ);
+ double h = gradDot(this.p(k + sectionZ + 1), localX, localY, localZ - 1.0D);
+ double o = gradDot(this.p(m + sectionZ + 1), localX - 1.0D, localY, localZ - 1.0D);
+ double p = gradDot(this.p(l + sectionZ + 1), localX, localY - 1.0D, localZ - 1.0D);
+ double q = gradDot(this.p(n + sectionZ + 1), localX - 1.0D, localY - 1.0D, localZ - 1.0D);
+ double r = Mth.smoothstep(localX);
+ double s = Mth.smoothstep(fadeLocalX);
+ double t = Mth.smoothstep(localZ);
+ return Mth.lerp3(r, s, t, d, e, f, g, h, o, p, q);
+ }
}
+ // Mirai end
private double sampleWithDerivative(int sectionX, int sectionY, int sectionZ, double localX, double localY, double localZ, double[] ds) {
int i = this.p(sectionX);
diff --git a/src/main/java/wtf/etil/mirai/MiraiConfig.java b/src/main/java/wtf/etil/mirai/MiraiConfig.java
index 1ba057cbd0ec23cd7ef3d3d1c7685f44cfe34eec..90cf922c8df669ac80451d64b376918dece09dc9 100644
--- a/src/main/java/wtf/etil/mirai/MiraiConfig.java
+++ b/src/main/java/wtf/etil/mirai/MiraiConfig.java
@@ -247,4 +247,9 @@ public class MiraiConfig {
riskyMathRoundOpt = getBoolean("use-risky-mathround-opt", riskyMathRoundOpt);
}
+ public static boolean vectorizedPerlinNoise = false;
+ private static void vectorizedNoise() {
+ vectorizedPerlinNoise = getBoolean("use-vectorized-perlin-noise", vectorizedPerlinNoise);
+ }
+
}
\ No newline at end of file
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