487 lines
20 KiB
Java
487 lines
20 KiB
Java
/*
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* Copyright (c) 2022, 2023, Arm Limited. All rights reserved.
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* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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*
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* This code is free software; you can redistribute it and/or modify it
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* under the terms of the GNU General Public License version 2 only, as
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* published by the Free Software Foundation.
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*
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* This code is distributed in the hope that it will be useful, but WITHOUT
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* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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* version 2 for more details (a copy is included in the LICENSE file that
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* accompanied this code).
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*
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* You should have received a copy of the GNU General Public License version
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* 2 along with this work; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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*
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* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
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* or visit www.oracle.com if you need additional information or have any
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* questions.
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*/
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package compiler.vectorapi;
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import compiler.lib.ir_framework.*;
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import java.util.Random;
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import jdk.incubator.vector.ByteVector;
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import jdk.incubator.vector.DoubleVector;
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import jdk.incubator.vector.FloatVector;
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import jdk.incubator.vector.IntVector;
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import jdk.incubator.vector.LongVector;
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import jdk.incubator.vector.ShortVector;
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import jdk.incubator.vector.VectorMask;
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import jdk.incubator.vector.VectorOperators;
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import jdk.incubator.vector.VectorSpecies;
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import jdk.test.lib.Asserts;
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import jdk.test.lib.Utils;
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/**
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* @test
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* @bug 8282431
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* @key randomness
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* @library /test/lib /
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* @requires vm.cpu.features ~= ".*sve.*"
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* @summary AArch64: Add optimized rules for masked vector multiply-add/sub for SVE
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* @modules jdk.incubator.vector
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*
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* @run driver compiler.vectorapi.VectorFusedMultiplyAddSubTest
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*/
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public class VectorFusedMultiplyAddSubTest {
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private static final VectorSpecies<Byte> B_SPECIES = ByteVector.SPECIES_MAX;
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private static final VectorSpecies<Double> D_SPECIES = DoubleVector.SPECIES_MAX;
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private static final VectorSpecies<Float> F_SPECIES = FloatVector.SPECIES_MAX;
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private static final VectorSpecies<Integer> I_SPECIES = IntVector.SPECIES_MAX;
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private static final VectorSpecies<Long> L_SPECIES = LongVector.SPECIES_MAX;
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private static final VectorSpecies<Short> S_SPECIES = ShortVector.SPECIES_MAX;
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private static int LENGTH = 128;
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private static final Random RD = Utils.getRandomInstance();
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private static byte[] ba;
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private static byte[] bb;
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private static byte[] bc;
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private static byte[] br;
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private static short[] sa;
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private static short[] sb;
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private static short[] sc;
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private static short[] sr;
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private static int[] ia;
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private static int[] ib;
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private static int[] ic;
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private static int[] ir;
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private static long[] la;
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private static long[] lb;
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private static long[] lc;
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private static long[] lr;
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private static float[] fa;
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private static float[] fb;
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private static float[] fc;
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private static float[] fr;
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private static double[] da;
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private static double[] db;
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private static double[] dc;
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private static double[] dr;
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private static boolean[] m;
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static {
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ba = new byte[LENGTH];
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bb = new byte[LENGTH];
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bc = new byte[LENGTH];
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br = new byte[LENGTH];
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sa = new short[LENGTH];
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sb = new short[LENGTH];
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sc = new short[LENGTH];
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sr = new short[LENGTH];
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ia = new int[LENGTH];
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ib = new int[LENGTH];
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ic = new int[LENGTH];
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ir = new int[LENGTH];
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la = new long[LENGTH];
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lb = new long[LENGTH];
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lc = new long[LENGTH];
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lr = new long[LENGTH];
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fa = new float[LENGTH];
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fb = new float[LENGTH];
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fc = new float[LENGTH];
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fr = new float[LENGTH];
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da = new double[LENGTH];
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db = new double[LENGTH];
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dc = new double[LENGTH];
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dr = new double[LENGTH];
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m = new boolean[LENGTH];
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for (int i = 0; i < LENGTH; i++) {
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ba[i] = (byte) RD.nextInt(25);
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bb[i] = (byte) RD.nextInt(25);
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bc[i] = (byte) RD.nextInt(25);
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sa[i] = (short) RD.nextInt(25);
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sb[i] = (short) RD.nextInt(25);
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sc[i] = (short) RD.nextInt(25);
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ia[i] = RD.nextInt(25);
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ib[i] = RD.nextInt(25);
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ic[i] = RD.nextInt(25);
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la[i] = RD.nextLong(25);
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lb[i] = RD.nextLong(25);
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lc[i] = RD.nextLong(25);
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fa[i] = RD.nextFloat((float) 25.0);
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fb[i] = RD.nextFloat((float) 25.0);
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fc[i] = RD.nextFloat((float) 25.0);
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da[i] = RD.nextDouble(25.0);
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db[i] = RD.nextDouble(25.0);
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dc[i] = RD.nextDouble(25.0);
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m[i] = RD.nextBoolean();
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}
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}
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interface BTenOp {
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byte apply(byte a, byte b, byte c);
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}
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interface STenOp {
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short apply(short a, short b, short c);
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}
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interface ITenOp {
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int apply(int a, int b, int c);
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}
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interface LTenOp {
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long apply(long a, long b, long c);
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}
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interface FTenOp {
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float apply(float a, float b, float c);
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}
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interface DTenOp {
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double apply(double a, double b, double c);
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}
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private static void assertArrayEquals(byte[] r, byte[] a, byte[] b, byte[] c, boolean[] m, BTenOp f) {
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for (int i = 0; i < LENGTH; i++) {
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if (m[i % B_SPECIES.length()]) {
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Asserts.assertEquals(f.apply(a[i], b[i], c[i]), r[i]);
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} else {
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Asserts.assertEquals(a[i], r[i]);
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}
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}
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}
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private static void assertArrayEquals(short[] r, short[] a, short[] b, short[] c, boolean[] m, STenOp f) {
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for (int i = 0; i < LENGTH; i++) {
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if (m[i % S_SPECIES.length()]) {
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Asserts.assertEquals(f.apply(a[i], b[i], c[i]), r[i]);
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} else {
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Asserts.assertEquals(a[i], r[i]);
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}
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}
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}
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private static void assertArrayEquals(int[] r, int[] a, int[] b, int[] c, boolean[] m, ITenOp f) {
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for (int i = 0; i < LENGTH; i++) {
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if (m[i % I_SPECIES.length()]) {
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Asserts.assertEquals(f.apply(a[i], b[i], c[i]), r[i]);
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} else {
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Asserts.assertEquals(a[i], r[i]);
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}
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}
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}
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private static void assertArrayEquals(long[] r, long[] a, long[] b, long[] c, boolean[] m, LTenOp f) {
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for (int i = 0; i < LENGTH; i++) {
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if (m[i % L_SPECIES.length()]) {
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Asserts.assertEquals(f.apply(a[i], b[i], c[i]), r[i]);
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} else {
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Asserts.assertEquals(a[i], r[i]);
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}
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}
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}
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private static void assertArrayEquals(float[] r, float[] a, float[] b, float[] c, boolean[] m, FTenOp f) {
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for (int i = 0; i < LENGTH; i++) {
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if (m[i % F_SPECIES.length()]) {
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Asserts.assertEquals(f.apply(a[i], b[i], c[i]), r[i]);
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} else {
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Asserts.assertEquals(a[i], r[i]);
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}
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}
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}
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private static void assertArrayEquals(double[] r, double[] a, double[] b, double[] c, boolean[] m, DTenOp f) {
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for (int i = 0; i < LENGTH; i++) {
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if (m[i % D_SPECIES.length()]) {
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Asserts.assertEquals(f.apply(a[i], b[i], c[i]), r[i]);
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} else {
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Asserts.assertEquals(a[i], r[i]);
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}
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}
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}
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private static void assertArrayEqualsNeg(float[] r, float[] a, float[] b, float[] c, boolean[] m, FTenOp f) {
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for (int i = 0; i < LENGTH; i++) {
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if (m[i % F_SPECIES.length()]) {
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Asserts.assertEquals(f.apply(a[i], b[i], c[i]), r[i]);
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} else {
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Asserts.assertEquals(-a[i], r[i]);
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}
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}
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}
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private static void assertArrayEqualsNeg(double[] r, double[] a, double[] b, double[] c, boolean[] m, DTenOp f) {
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for (int i = 0; i < LENGTH; i++) {
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if (m[i % D_SPECIES.length()]) {
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Asserts.assertEquals(f.apply(a[i], b[i], c[i]), r[i]);
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} else {
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Asserts.assertEquals(-a[i], r[i]);
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}
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}
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}
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@Test
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@IR(counts = { IRNode.VMLA_MASKED, ">= 1" })
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public static void testByteMultiplyAddMasked() {
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VectorMask<Byte> mask = VectorMask.fromArray(B_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += B_SPECIES.length()) {
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ByteVector av = ByteVector.fromArray(B_SPECIES, ba, i);
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ByteVector bv = ByteVector.fromArray(B_SPECIES, bb, i);
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ByteVector cv = ByteVector.fromArray(B_SPECIES, bc, i);
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av.add(bv.mul(cv), mask).intoArray(br, i);
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}
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assertArrayEquals(br, ba, bb, bc, m, (a, b, c) -> (byte) (a + b * c));
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}
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@Test
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@IR(counts = { IRNode.VMLS_MASKED, ">= 1" })
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public static void testByteMultiplySubMasked() {
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VectorMask<Byte> mask = VectorMask.fromArray(B_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += B_SPECIES.length()) {
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ByteVector av = ByteVector.fromArray(B_SPECIES, ba, i);
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ByteVector bv = ByteVector.fromArray(B_SPECIES, bb, i);
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ByteVector cv = ByteVector.fromArray(B_SPECIES, bc, i);
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av.sub(bv.mul(cv), mask).intoArray(br, i);
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}
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assertArrayEquals(br, ba, bb, bc, m, (a, b, c) -> (byte) (a - b * c));
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}
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@Test
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@IR(counts = { IRNode.VMLA_MASKED, ">= 1" })
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public static void testShortMultiplyAddMasked() {
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VectorMask<Short> mask = VectorMask.fromArray(S_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += S_SPECIES.length()) {
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ShortVector av = ShortVector.fromArray(S_SPECIES, sa, i);
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ShortVector bv = ShortVector.fromArray(S_SPECIES, sb, i);
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ShortVector cv = ShortVector.fromArray(S_SPECIES, sc, i);
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av.add(bv.mul(cv), mask).intoArray(sr, i);
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}
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assertArrayEquals(sr, sa, sb, sc, m, (a, b, c) -> (short) (a + b * c));
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}
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@Test
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@IR(counts = { IRNode.VMLS_MASKED, ">= 1" })
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public static void testShortMultiplySubMasked() {
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VectorMask<Short> mask = VectorMask.fromArray(S_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += S_SPECIES.length()) {
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ShortVector av = ShortVector.fromArray(S_SPECIES, sa, i);
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ShortVector bv = ShortVector.fromArray(S_SPECIES, sb, i);
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ShortVector cv = ShortVector.fromArray(S_SPECIES, sc, i);
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av.sub(bv.mul(cv), mask).intoArray(sr, i);
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}
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assertArrayEquals(sr, sa, sb, sc, m, (a, b, c) -> (short) (a - b * c));
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}
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@Test
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@IR(counts = { IRNode.VMLA_MASKED, ">= 1" })
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public static void testIntMultiplyAddMasked() {
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VectorMask<Integer> mask = VectorMask.fromArray(I_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += I_SPECIES.length()) {
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IntVector av = IntVector.fromArray(I_SPECIES, ia, i);
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IntVector bv = IntVector.fromArray(I_SPECIES, ib, i);
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IntVector cv = IntVector.fromArray(I_SPECIES, ic, i);
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av.add(bv.mul(cv), mask).intoArray(ir, i);
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}
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assertArrayEquals(ir, ia, ib, ic, m, (a, b, c) -> (int) (a + b * c));
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}
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@Test
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@IR(counts = { IRNode.VMLS_MASKED, ">= 1" })
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public static void testIntMultiplySubMasked() {
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VectorMask<Integer> mask = VectorMask.fromArray(I_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += I_SPECIES.length()) {
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IntVector av = IntVector.fromArray(I_SPECIES, ia, i);
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IntVector bv = IntVector.fromArray(I_SPECIES, ib, i);
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IntVector cv = IntVector.fromArray(I_SPECIES, ic, i);
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av.sub(bv.mul(cv), mask).intoArray(ir, i);
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}
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assertArrayEquals(ir, ia, ib, ic, m, (a, b, c) -> (int) (a - b * c));
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}
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@Test
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@IR(counts = { IRNode.VMLA_MASKED, ">= 1" })
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public static void testLongMultiplyAddMasked() {
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VectorMask<Long> mask = VectorMask.fromArray(L_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += L_SPECIES.length()) {
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LongVector av = LongVector.fromArray(L_SPECIES, la, i);
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LongVector bv = LongVector.fromArray(L_SPECIES, lb, i);
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LongVector cv = LongVector.fromArray(L_SPECIES, lc, i);
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av.add(bv.mul(cv), mask).intoArray(lr, i);
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}
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assertArrayEquals(lr, la, lb, lc, m, (a, b, c) -> (long) (a + b * c));
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}
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@Test
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@IR(counts = { IRNode.VMLS_MASKED, ">= 1" })
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public static void testLongMultiplySubMasked() {
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VectorMask<Long> mask = VectorMask.fromArray(L_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += L_SPECIES.length()) {
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LongVector av = LongVector.fromArray(L_SPECIES, la, i);
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LongVector bv = LongVector.fromArray(L_SPECIES, lb, i);
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LongVector cv = LongVector.fromArray(L_SPECIES, lc, i);
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av.sub(bv.mul(cv), mask).intoArray(lr, i);
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}
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assertArrayEquals(lr, la, lb, lc, m, (a, b, c) -> (long) (a - b * c));
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}
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@Test
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@IR(counts = { IRNode.VFMSB_MASKED, ">= 1" })
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public static void testFloatMultiplySubMasked() {
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VectorMask<Float> mask = VectorMask.fromArray(F_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += F_SPECIES.length()) {
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FloatVector av = FloatVector.fromArray(F_SPECIES, fa, i);
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FloatVector bv = FloatVector.fromArray(F_SPECIES, fb, i);
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FloatVector cv = FloatVector.fromArray(F_SPECIES, fc, i);
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av.lanewise(VectorOperators.FMA, bv.neg(), cv, mask).intoArray(fr, i);
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}
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assertArrayEquals(fr, fa, fb, fc, m, (a, b, c) -> (float) Math.fma(a, -b, c));
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}
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@Test
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@IR(counts = { IRNode.VFMAD_MASKED, ">= 1" })
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public static void testFloatMultiplyNegAMasked() {
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VectorMask<Float> mask = VectorMask.fromArray(F_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += F_SPECIES.length()) {
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FloatVector av = FloatVector.fromArray(F_SPECIES, fa, i);
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FloatVector bv = FloatVector.fromArray(F_SPECIES, fb, i);
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FloatVector cv = FloatVector.fromArray(F_SPECIES, fc, i);
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av.neg().lanewise(VectorOperators.FMA, bv, cv, mask).intoArray(fr, i);
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}
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assertArrayEqualsNeg(fr, fa, fb, fc, m, (a, b, c) -> (float) Math.fma(-a, b, c));
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}
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@Test
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@IR(counts = { IRNode.VFNMAD_MASKED, ">= 1" })
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public static void testFloatNegatedMultiplyAddMasked() {
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VectorMask<Float> mask = VectorMask.fromArray(F_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += F_SPECIES.length()) {
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FloatVector av = FloatVector.fromArray(F_SPECIES, fa, i);
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FloatVector bv = FloatVector.fromArray(F_SPECIES, fb, i);
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FloatVector cv = FloatVector.fromArray(F_SPECIES, fc, i);
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av.lanewise(VectorOperators.FMA, bv.neg(), cv.neg(), mask).intoArray(fr, i);
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}
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assertArrayEquals(fr, fa, fb, fc, m, (a, b, c) -> (float) Math.fma(a, -b, -c));
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}
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@Test
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@IR(counts = { IRNode.VFNMSB_MASKED, ">= 1" })
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public static void testFloatNegatedMultiplyNegAMasked() {
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VectorMask<Float> mask = VectorMask.fromArray(F_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += F_SPECIES.length()) {
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FloatVector av = FloatVector.fromArray(F_SPECIES, fa, i);
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FloatVector bv = FloatVector.fromArray(F_SPECIES, fb, i);
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FloatVector cv = FloatVector.fromArray(F_SPECIES, fc, i);
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av.neg().lanewise(VectorOperators.FMA, bv, cv.neg(), mask).intoArray(fr, i);
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}
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assertArrayEqualsNeg(fr, fa, fb, fc, m, (a, b, c) -> (float) Math.fma(-a, b, -c));
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}
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@Test
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@IR(counts = { IRNode.VFNMSB_MASKED, ">= 1" })
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public static void testFloatNegatedMultiplySubMasked() {
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VectorMask<Float> mask = VectorMask.fromArray(F_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += F_SPECIES.length()) {
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FloatVector av = FloatVector.fromArray(F_SPECIES, fa, i);
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FloatVector bv = FloatVector.fromArray(F_SPECIES, fb, i);
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FloatVector cv = FloatVector.fromArray(F_SPECIES, fc, i);
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av.lanewise(VectorOperators.FMA, bv, cv.neg(), mask).intoArray(fr, i);
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}
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assertArrayEquals(fr, fa, fb, fc, m, (a, b, c) -> (float) Math.fma(a, b, -c));
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}
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@Test
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@IR(counts = { IRNode.VFMSB_MASKED, ">= 1" })
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public static void testDoubleMultiplySubMasked() {
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VectorMask<Double> mask = VectorMask.fromArray(D_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += D_SPECIES.length()) {
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DoubleVector av = DoubleVector.fromArray(D_SPECIES, da, i);
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DoubleVector bv = DoubleVector.fromArray(D_SPECIES, db, i);
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DoubleVector cv = DoubleVector.fromArray(D_SPECIES, dc, i);
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av.lanewise(VectorOperators.FMA, bv.neg(), cv, mask).intoArray(dr, i);
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}
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assertArrayEquals(dr, da, db, dc, m, (a, b, c) -> (double) Math.fma(a, -b, c));
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}
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|
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@Test
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@IR(counts = { IRNode.VFMAD_MASKED, ">= 1" })
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public static void testDoubleMultiplyNegAMasked() {
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VectorMask<Double> mask = VectorMask.fromArray(D_SPECIES, m, 0);
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for (int i = 0; i < LENGTH; i += D_SPECIES.length()) {
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|
DoubleVector av = DoubleVector.fromArray(D_SPECIES, da, i);
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DoubleVector bv = DoubleVector.fromArray(D_SPECIES, db, i);
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DoubleVector cv = DoubleVector.fromArray(D_SPECIES, dc, i);
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av.neg().lanewise(VectorOperators.FMA, bv, cv, mask).intoArray(dr, i);
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}
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assertArrayEqualsNeg(dr, da, db, dc, m, (a, b, c) -> (double) Math.fma(-a, b, c));
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}
|
|
|
|
@Test
|
|
@IR(counts = { IRNode.VFNMAD_MASKED, ">= 1" })
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|
public static void testDoubleNegatedMultiplyAddMasked() {
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|
VectorMask<Double> mask = VectorMask.fromArray(D_SPECIES, m, 0);
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|
for (int i = 0; i < LENGTH; i += D_SPECIES.length()) {
|
|
DoubleVector av = DoubleVector.fromArray(D_SPECIES, da, i);
|
|
DoubleVector bv = DoubleVector.fromArray(D_SPECIES, db, i);
|
|
DoubleVector cv = DoubleVector.fromArray(D_SPECIES, dc, i);
|
|
av.lanewise(VectorOperators.FMA, bv.neg(), cv.neg(), mask).intoArray(dr, i);
|
|
}
|
|
assertArrayEquals(dr, da, db, dc, m, (a, b, c) -> (double) Math.fma(a, -b, -c));
|
|
}
|
|
|
|
@Test
|
|
@IR(counts = { IRNode.VFNMSB_MASKED, ">= 1" })
|
|
public static void testDoubleNegatedMultiplyNegAMasked() {
|
|
VectorMask<Double> mask = VectorMask.fromArray(D_SPECIES, m, 0);
|
|
for (int i = 0; i < LENGTH; i += D_SPECIES.length()) {
|
|
DoubleVector av = DoubleVector.fromArray(D_SPECIES, da, i);
|
|
DoubleVector bv = DoubleVector.fromArray(D_SPECIES, db, i);
|
|
DoubleVector cv = DoubleVector.fromArray(D_SPECIES, dc, i);
|
|
av.neg().lanewise(VectorOperators.FMA, bv, cv.neg(), mask).intoArray(dr, i);
|
|
}
|
|
assertArrayEqualsNeg(dr, da, db, dc, m, (a, b, c) -> (double) Math.fma(-a, b, -c));
|
|
}
|
|
|
|
@Test
|
|
@IR(counts = { IRNode.VFNMSB_MASKED, ">= 1" })
|
|
public static void testDoubleNegatedMultiplySubMasked() {
|
|
VectorMask<Double> mask = VectorMask.fromArray(D_SPECIES, m, 0);
|
|
for (int i = 0; i < LENGTH; i += D_SPECIES.length()) {
|
|
DoubleVector av = DoubleVector.fromArray(D_SPECIES, da, i);
|
|
DoubleVector bv = DoubleVector.fromArray(D_SPECIES, db, i);
|
|
DoubleVector cv = DoubleVector.fromArray(D_SPECIES, dc, i);
|
|
av.lanewise(VectorOperators.FMA, bv, cv.neg(), mask).intoArray(dr, i);
|
|
}
|
|
assertArrayEquals(dr, da, db, dc, m, (a, b, c) -> (double) Math.fma(a, b, -c));
|
|
}
|
|
|
|
public static void main(String[] args) {
|
|
TestFramework testFramework = new TestFramework();
|
|
testFramework.setDefaultWarmup(5000)
|
|
.addFlags("--add-modules=jdk.incubator.vector", "-XX:UseSVE=1")
|
|
.start();
|
|
}
|
|
}
|