/* * Copyright (c) 2022, Arm Limited. All rights reserved. * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. * * This code is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 2 only, as * published by the Free Software Foundation. * * This code is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * version 2 for more details (a copy is included in the LICENSE file that * accompanied this code). * * You should have received a copy of the GNU General Public License version * 2 along with this work; if not, write to the Free Software Foundation, * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. * * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA * or visit www.oracle.com if you need additional information or have any * questions. */ package compiler.vectorapi; import compiler.lib.ir_framework.*; import java.util.Random; import jdk.incubator.vector.ByteVector; import jdk.incubator.vector.ShortVector; import jdk.incubator.vector.IntVector; import jdk.incubator.vector.LongVector; import jdk.incubator.vector.VectorSpecies; import jdk.test.lib.Asserts; import jdk.test.lib.Utils; /** * @test * @bug 8275275 * @key randomness * @library /test/lib / * @requires os.arch=="aarch64" * @summary AArch64: Fix performance regression after auto-vectorization on NEON * @modules jdk.incubator.vector * * @run driver compiler.vectorapi.TestVectorMulAddSub */ public class TestVectorMulAddSub { private static final VectorSpecies B_SPECIES = ByteVector.SPECIES_MAX; private static final VectorSpecies S_SPECIES = ShortVector.SPECIES_MAX; private static final VectorSpecies I_SPECIES = IntVector.SPECIES_MAX; private static final VectorSpecies L_SPECIES = LongVector.SPECIES_MAX; private static int LENGTH = 1024; private static final Random RD = Utils.getRandomInstance(); private static byte[] ba; private static byte[] bb; private static byte[] bc; private static byte[] br; private static short[] sa; private static short[] sb; private static short[] sc; private static short[] sr; private static int[] ia; private static int[] ib; private static int[] ic; private static int[] ir; private static long[] la; private static long[] lb; private static long[] lc; private static long[] lr; static { ba = new byte[LENGTH]; bb = new byte[LENGTH]; bc = new byte[LENGTH]; br = new byte[LENGTH]; sa = new short[LENGTH]; sb = new short[LENGTH]; sc = new short[LENGTH]; sr = new short[LENGTH]; ia = new int[LENGTH]; ib = new int[LENGTH]; ic = new int[LENGTH]; ir = new int[LENGTH]; la = new long[LENGTH]; lb = new long[LENGTH]; lc = new long[LENGTH]; lr = new long[LENGTH]; for (int i = 0; i < LENGTH; i++) { ba[i] = (byte) RD.nextInt(); bb[i] = (byte) RD.nextInt(); bc[i] = (byte) RD.nextInt(); sa[i] = (short) RD.nextInt(); sb[i] = (short) RD.nextInt(); sc[i] = (short) RD.nextInt(); ia[i] = RD.nextInt(); ib[i] = RD.nextInt(); ic[i] = RD.nextInt(); la[i] = RD.nextLong(); lb[i] = RD.nextLong(); lc[i] = RD.nextLong(); } } @Test @IR(counts = {IRNode.VMLA, "> 0"}) public static void testByteMulAdd() { for (int i = 0; i < LENGTH; i += B_SPECIES.length()) { ByteVector av = ByteVector.fromArray(B_SPECIES, ba, i); ByteVector bv = ByteVector.fromArray(B_SPECIES, bb, i); ByteVector cv = ByteVector.fromArray(B_SPECIES, bc, i); av.add(bv.mul(cv)).intoArray(br, i); } } @Run(test = "testByteMulAdd") public static void testByteMulAdd_runner() { testByteMulAdd(); for (int i = 0; i < LENGTH; i++) { Asserts.assertEquals((byte) (ba[i] + bb[i] * bc[i]), br[i]); } } @Test @IR(counts = {IRNode.VMLA, "> 0"}) public static void testShortMulAdd() { for (int i = 0; i < LENGTH; i += S_SPECIES.length()) { ShortVector av = ShortVector.fromArray(S_SPECIES, sa, i); ShortVector bv = ShortVector.fromArray(S_SPECIES, sb, i); ShortVector cv = ShortVector.fromArray(S_SPECIES, sc, i); av.add(bv.mul(cv)).intoArray(sr, i); } } @Run(test = "testShortMulAdd") public static void testShortMulAdd_runner() { testShortMulAdd(); for (int i = 0; i < LENGTH; i++) { Asserts.assertEquals((short) (sa[i] + sb[i] * sc[i]), sr[i]); } } @Test @IR(counts = {IRNode.VMLA, "> 0"}) public static void testIntMulAdd() { for (int i = 0; i < LENGTH; i += I_SPECIES.length()) { IntVector av = IntVector.fromArray(I_SPECIES, ia, i); IntVector bv = IntVector.fromArray(I_SPECIES, ib, i); IntVector cv = IntVector.fromArray(I_SPECIES, ic, i); av.add(bv.mul(cv)).intoArray(ir, i); } } @Run(test = "testIntMulAdd") public static void testIntMulAdd_runner() { testIntMulAdd(); for (int i = 0; i < LENGTH; i++) { Asserts.assertEquals((ia[i] + ib[i] * ic[i]), ir[i]); } } @Test @IR(applyIf = {"UseSVE", " > 0"}, counts = {IRNode.VMLA, "> 0"}) public static void testLongMulAdd() { for (int i = 0; i < LENGTH; i += L_SPECIES.length()) { LongVector av = LongVector.fromArray(L_SPECIES, la, i); LongVector bv = LongVector.fromArray(L_SPECIES, lb, i); LongVector cv = LongVector.fromArray(L_SPECIES, lc, i); av.add(bv.mul(cv)).intoArray(lr, i); } } @Run(test = "testLongMulAdd") public static void testLongMulAdd_runner() { testLongMulAdd(); for (int i = 0; i < LENGTH; i++) { Asserts.assertEquals((la[i] + lb[i] * lc[i]), lr[i]); } } @Test @IR(counts = {IRNode.VMLS, "> 0"}) public static void testByteMulSub() { for (int i = 0; i < LENGTH; i += B_SPECIES.length()) { ByteVector av = ByteVector.fromArray(B_SPECIES, ba, i); ByteVector bv = ByteVector.fromArray(B_SPECIES, bb, i); ByteVector cv = ByteVector.fromArray(B_SPECIES, bc, i); av.sub(bv.mul(cv)).intoArray(br, i); } } @Run(test = "testByteMulSub") public static void testByteMulSub_runner() { testByteMulSub(); for (int i = 0; i < LENGTH; i++) { Asserts.assertEquals((byte) (ba[i] - bb[i] * bc[i]), br[i]); } } @Test @IR(counts = {IRNode.VMLS, "> 0"}) public static void testShortMulSub() { for (int i = 0; i < LENGTH; i += S_SPECIES.length()) { ShortVector av = ShortVector.fromArray(S_SPECIES, sa, i); ShortVector bv = ShortVector.fromArray(S_SPECIES, sb, i); ShortVector cv = ShortVector.fromArray(S_SPECIES, sc, i); av.sub(bv.mul(cv)).intoArray(sr, i); } } @Run(test = "testShortMulSub") public static void testShortMulSub_runner() { testShortMulSub(); for (int i = 0; i < LENGTH; i++) { Asserts.assertEquals((short) (sa[i] - sb[i] * sc[i]), sr[i]); } } @Test @IR(counts = {IRNode.VMLS, "> 0"}) public static void testIntMulSub() { for (int i = 0; i < LENGTH; i += I_SPECIES.length()) { IntVector av = IntVector.fromArray(I_SPECIES, ia, i); IntVector bv = IntVector.fromArray(I_SPECIES, ib, i); IntVector cv = IntVector.fromArray(I_SPECIES, ic, i); av.sub(bv.mul(cv)).intoArray(ir, i); } } @Run(test = "testIntMulSub") public static void testIntMulSub_runner() { testIntMulSub(); for (int i = 0; i < LENGTH; i++) { Asserts.assertEquals((ia[i] - ib[i] * ic[i]), ir[i]); } } @Test @IR(applyIf = {"UseSVE", " > 0"}, counts = {IRNode.VMLS, "> 0"}) public static void testLongMulSub() { for (int i = 0; i < LENGTH; i += L_SPECIES.length()) { LongVector av = LongVector.fromArray(L_SPECIES, la, i); LongVector bv = LongVector.fromArray(L_SPECIES, lb, i); LongVector cv = LongVector.fromArray(L_SPECIES, lc, i); av.sub(bv.mul(cv)).intoArray(lr, i); } } @Run(test = "testLongMulSub") public static void testLongMulSub_runner() { testLongMulSub(); for (int i = 0; i < LENGTH; i++) { Asserts.assertEquals((la[i] - lb[i] * lc[i]), lr[i]); } } public static void main(String[] args) { TestFramework.runWithFlags("--add-modules=jdk.incubator.vector"); } }