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