268 lines
8.9 KiB
Java
268 lines
8.9 KiB
Java
/*
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* Copyright (c) 2022, 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.ShortVector;
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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.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 8275275
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* @key randomness
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* @library /test/lib /
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* @requires os.arch=="aarch64"
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* @summary AArch64: Fix performance regression after auto-vectorization on NEON
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* @modules jdk.incubator.vector
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*
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* @run driver compiler.vectorapi.TestVectorMulAddSub
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*/
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public class TestVectorMulAddSub {
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private static final VectorSpecies<Byte> B_SPECIES = ByteVector.SPECIES_MAX;
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private static final VectorSpecies<Short> S_SPECIES = ShortVector.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 int LENGTH = 1024;
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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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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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for (int i = 0; i < LENGTH; i++) {
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ba[i] = (byte) RD.nextInt();
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bb[i] = (byte) RD.nextInt();
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bc[i] = (byte) RD.nextInt();
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sa[i] = (short) RD.nextInt();
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sb[i] = (short) RD.nextInt();
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sc[i] = (short) RD.nextInt();
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ia[i] = RD.nextInt();
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ib[i] = RD.nextInt();
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ic[i] = RD.nextInt();
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la[i] = RD.nextLong();
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lb[i] = RD.nextLong();
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lc[i] = RD.nextLong();
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}
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}
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@Test
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@IR(counts = {IRNode.VMLA, "> 0"})
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public static void testByteMulAdd() {
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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)).intoArray(br, i);
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}
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}
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@Run(test = "testByteMulAdd")
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public static void testByteMulAdd_runner() {
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testByteMulAdd();
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for (int i = 0; i < LENGTH; i++) {
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Asserts.assertEquals((byte) (ba[i] + bb[i] * bc[i]), br[i]);
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}
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}
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@Test
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@IR(counts = {IRNode.VMLA, "> 0"})
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public static void testShortMulAdd() {
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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)).intoArray(sr, i);
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}
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}
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@Run(test = "testShortMulAdd")
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public static void testShortMulAdd_runner() {
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testShortMulAdd();
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for (int i = 0; i < LENGTH; i++) {
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Asserts.assertEquals((short) (sa[i] + sb[i] * sc[i]), sr[i]);
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}
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}
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@Test
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@IR(counts = {IRNode.VMLA, "> 0"})
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public static void testIntMulAdd() {
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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)).intoArray(ir, i);
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}
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}
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@Run(test = "testIntMulAdd")
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public static void testIntMulAdd_runner() {
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testIntMulAdd();
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for (int i = 0; i < LENGTH; i++) {
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Asserts.assertEquals((ia[i] + ib[i] * ic[i]), ir[i]);
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}
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}
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@Test
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@IR(applyIf = {"UseSVE", " > 0"}, counts = {IRNode.VMLA, "> 0"})
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public static void testLongMulAdd() {
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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)).intoArray(lr, i);
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}
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}
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@Run(test = "testLongMulAdd")
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public static void testLongMulAdd_runner() {
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testLongMulAdd();
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for (int i = 0; i < LENGTH; i++) {
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Asserts.assertEquals((la[i] + lb[i] * lc[i]), lr[i]);
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}
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}
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@Test
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@IR(counts = {IRNode.VMLS, "> 0"})
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public static void testByteMulSub() {
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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)).intoArray(br, i);
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}
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}
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@Run(test = "testByteMulSub")
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public static void testByteMulSub_runner() {
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testByteMulSub();
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for (int i = 0; i < LENGTH; i++) {
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Asserts.assertEquals((byte) (ba[i] - bb[i] * bc[i]), br[i]);
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}
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}
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@Test
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@IR(counts = {IRNode.VMLS, "> 0"})
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public static void testShortMulSub() {
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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)).intoArray(sr, i);
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}
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}
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@Run(test = "testShortMulSub")
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public static void testShortMulSub_runner() {
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testShortMulSub();
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for (int i = 0; i < LENGTH; i++) {
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Asserts.assertEquals((short) (sa[i] - sb[i] * sc[i]), sr[i]);
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}
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}
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@Test
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@IR(counts = {IRNode.VMLS, "> 0"})
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public static void testIntMulSub() {
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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)).intoArray(ir, i);
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}
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}
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@Run(test = "testIntMulSub")
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public static void testIntMulSub_runner() {
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testIntMulSub();
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for (int i = 0; i < LENGTH; i++) {
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Asserts.assertEquals((ia[i] - ib[i] * ic[i]), ir[i]);
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}
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}
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@Test
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@IR(applyIf = {"UseSVE", " > 0"}, counts = {IRNode.VMLS, "> 0"})
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public static void testLongMulSub() {
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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)).intoArray(lr, i);
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}
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}
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@Run(test = "testLongMulSub")
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public static void testLongMulSub_runner() {
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testLongMulSub();
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for (int i = 0; i < LENGTH; i++) {
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Asserts.assertEquals((la[i] - lb[i] * lc[i]), lr[i]);
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}
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}
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public static void main(String[] args) {
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TestFramework.runWithFlags("--add-modules=jdk.incubator.vector");
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}
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}
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