/* * Copyright (c) 2022, 2023, 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. */ /* * @test * @summary Vectorization test on basic float operations * @library /test/lib / * * @build jdk.test.whitebox.WhiteBox * compiler.vectorization.runner.VectorizationTestRunner * * @run driver jdk.test.lib.helpers.ClassFileInstaller jdk.test.whitebox.WhiteBox * @run main/othervm -Xbootclasspath/a:. * -XX:+UnlockDiagnosticVMOptions * -XX:+WhiteBoxAPI * compiler.vectorization.runner.BasicFloatOpTest * * @requires (os.simpleArch == "x64") | (os.simpleArch == "aarch64") * @requires vm.compiler2.enabled */ package compiler.vectorization.runner; import compiler.lib.ir_framework.*; import java.util.Random; public class BasicFloatOpTest extends VectorizationTestRunner { private static final int SIZE = 543; private float[] a; private float[] b; private float[] c; private float[] d; private float[] e; public BasicFloatOpTest() { // Positive test values sign | exponent | mantisa float smallPositive = Float.intBitsToFloat(0<<31 | 0x3f << 23 | 0x30000f); float positive = Float.intBitsToFloat(0<<31 | 0x7f << 23 | 0x30000f); float bigPositive = Float.intBitsToFloat(0<<31 | 0x7f << 23 | 0x30100f); float biggerPositive = Float.intBitsToFloat(0<<31 | 0xfe << 23 | 0x30000f); float maxPositive = Float.MAX_VALUE; // Special positive float nan1 = Float.intBitsToFloat(0<<31 | 0xff << 23 | 0x7fffff); float nan2 = Float.intBitsToFloat(0<<31 | 0xff << 23 | 0x30000f); float inf = Float.intBitsToFloat(0<<31 | 0xff << 23); float zero = 0.0f; // Negative test values sign | exponent | mantisa float smallNegative = Float.intBitsToFloat(1<<31 | 0x03 << 23 | 0x30000f); float negative = Float.intBitsToFloat(1<<31 | 0x83 << 23 | 0x30100f); float bigNegative = Float.intBitsToFloat(1<<31 | 0x83 << 23 | 0x30000f); float biggerNegative = Float.intBitsToFloat(1<<31 | 0x86 << 23 | 0x30000f); float maxNegative = Float.intBitsToFloat(1<<31 | 0xfe << 23 | 0x7fffff); // Special negative float nNan1 = Float.intBitsToFloat(1<<31 | 0xff << 23 | 0x7fffff); float nNan2 = Float.intBitsToFloat(1<<31 | 0xff << 23 | 0x30000f); float nInf = Float.intBitsToFloat(1<<31 | 0xff << 23); float nZero = -0.0f; float[] orderedList = new float[] { nInf, maxNegative, biggerNegative, bigNegative, negative, smallNegative, nZero, zero, smallPositive, positive, bigPositive, biggerPositive, maxPositive, inf }; float[] NaNs = new float[] { nan1, nan2, nNan1, nNan2 }; float[] numberList = new float[] { nInf, maxNegative, biggerNegative, bigNegative, negative, smallNegative, nZero, zero, smallPositive, positive, bigPositive, biggerPositive, maxPositive, inf, nan1, nan2, nNan1, nNan2 }; Random rnd = new Random(11); a = new float[SIZE]; b = new float[SIZE]; c = new float[SIZE]; d = new float[SIZE]; e = new float[SIZE]; for (int i = 0; i < SIZE;) { for (int j = 0; j < numberList.length && i < SIZE; j++, i++) { for (int k = j; k < numberList.length && i < SIZE; k++, i++) { if (rnd.nextBoolean()) { d[i] = numberList[j]; e[i] = numberList[k]; } else { d[i] = numberList[k]; e[i] = numberList[j]; } } } } for (int i = 0; i < SIZE; i++) { a[i] = 850.0f * i + 22222.22f; b[i] = -12345.678f; c[i] = -1.23456e7f; } } // ---------------- Arithmetic ---------------- @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "sse", "true"}, counts = {IRNode.NEG_VF, ">0"}) public float[] vectorNeg() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = -a[i]; } return res; } @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "sse", "true"}, counts = {IRNode.ABS_VF, ">0"}) public float[] vectorAbs() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.abs(a[i]); } return res; } @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "avx", "true"}, counts = {IRNode.SQRT_VF, ">0"}) public float[] vectorSqrt() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = (float) Math.sqrt(a[i]); } return res; } @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "sse2", "true"}, counts = {IRNode.ADD_VF, ">0"}) public float[] vectorAdd() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = a[i] + b[i]; } return res; } @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "sse2", "true"}, counts = {IRNode.SUB_VF, ">0"}) public float[] vectorSub() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = a[i] - b[i]; } return res; } @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "sse2", "true"}, counts = {IRNode.MUL_VF, ">0"}) public float[] vectorMul() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = a[i] * b[i]; } return res; } @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "sse2", "true"}, counts = {IRNode.DIV_VF, ">0"}) public float[] vectorDiv() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = a[i] / b[i]; } return res; } @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "avx", "true"}, counts = {IRNode.MAX_VF, ">0"}) public float[] vectorMax() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.max(d[i], e[i]); } return res; } @Test @IR(applyIfCPUFeatureOr = {"asimd", "true", "avx", "true"}, counts = {IRNode.MIN_VF, ">0"}) public float[] vectorMin() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.min(d[i], e[i]); } return res; } @Test @IR(applyIfCPUFeature = {"asimd", "true"}, counts = {IRNode.FMA_VF, ">0", IRNode.VFMLA, ">0"}) @IR(applyIfCPUFeatureAnd = {"fma", "true", "avx", "true"}, counts = {IRNode.FMA_VF, ">0"}) public float[] vectorMulAdd() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.fma(a[i], b[i], c[i]); } return res; } @Test @IR(applyIfCPUFeature = {"asimd", "true"}, counts = {IRNode.FMA_VF, ">0", IRNode.VFMLS, ">0"}) @IR(applyIfCPUFeatureAnd = {"fma", "true", "avx", "true"}, counts = {IRNode.FMA_VF, ">0"}) public float[] vectorMulSub1() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.fma(-a[i], b[i], c[i]); } return res; } @Test @IR(applyIfCPUFeature = {"asimd", "true"}, counts = {IRNode.FMA_VF, ">0", IRNode.VFMLS, ">0"}) @IR(applyIfCPUFeatureAnd = {"fma", "true", "avx", "true"}, counts = {IRNode.FMA_VF, ">0"}) public float[] vectorMulSub2() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.fma(a[i], -b[i], c[i]); } return res; } @Test @IR(applyIfCPUFeature = {"asimd", "true"}, counts = {IRNode.FMA_VF, ">0"}) @IR(applyIfCPUFeature = {"sve", "true"}, counts = {IRNode.VFNMLA, ">0"}) @IR(applyIfCPUFeatureAnd = {"fma", "true", "avx", "true"}, counts = {IRNode.FMA_VF, ">0"}) public float[] vectorNegateMulAdd1() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.fma(-a[i], b[i], -c[i]); } return res; } @Test @IR(applyIfCPUFeature = {"asimd", "true"}, counts = {IRNode.FMA_VF, ">0"}) @IR(applyIfCPUFeature = {"sve", "true"}, counts = {IRNode.VFNMLA, ">0"}) @IR(applyIfCPUFeatureAnd = {"fma", "true", "avx", "true"}, counts = {IRNode.FMA_VF, ">0"}) public float[] vectorNegateMulAdd2() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.fma(a[i], -b[i], -c[i]); } return res; } @Test @IR(applyIfCPUFeature = {"asimd", "true"}, counts = {IRNode.FMA_VF, ">0"}) @IR(applyIfCPUFeatureAnd = {"fma", "true", "avx", "true"}, counts = {IRNode.FMA_VF, ">0"}) public float[] vectorNegateMulSub() { float[] res = new float[SIZE]; for (int i = 0; i < SIZE; i++) { res[i] = Math.fma(a[i], b[i], -c[i]); } return res; } // ---------------- Reduction ---------------- @Test public float reductionAdd() { float res = 0.0f; for (int i = 0; i < SIZE; i++) { res += a[i]; } return res; } @Test public float reductionMax() { float res = Float.MIN_VALUE; for (int i = 0; i < SIZE; i++) { res = Math.max(res, a[i]); } return res; } @Test public float reductionMin() { float res = Float.MAX_VALUE; for (int i = 0; i < SIZE; i++) { res = Math.min(res, a[i]); } return res; } }