8302191: Performance degradation for float/double modulo on Linux
Reviewed-by: dholmes, sviswanathan
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760c0128a4
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37774556da
@ -24,6 +24,7 @@
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#include "precompiled.hpp"
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#include "asm/macroAssembler.hpp"
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#include "runtime/interfaceSupport.inline.hpp"
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#include "runtime/sharedRuntime.hpp"
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#include "vmreg_x86.inline.hpp"
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#ifdef COMPILER1
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@ -83,3 +84,34 @@ void SharedRuntime::inline_check_hashcode_from_object_header(MacroAssembler* mas
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}
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#endif //COMPILER1
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#if defined(TARGET_COMPILER_gcc) && !defined(_WIN64)
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JRT_LEAF(jfloat, SharedRuntime::frem(jfloat x, jfloat y))
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jfloat retval;
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asm ("\
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1: \n\
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fprem \n\
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fnstsw %%ax \n\
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test $0x4,%%ah \n\
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jne 1b \n\
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"
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:"=t"(retval)
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:"0"(x), "u"(y)
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:"cc", "ax");
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return retval;
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JRT_END
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JRT_LEAF(jdouble, SharedRuntime::drem(jdouble x, jdouble y))
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jdouble retval;
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asm ("\
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1: \n\
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fprem \n\
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fnstsw %%ax \n\
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test $0x4,%%ah \n\
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jne 1b \n\
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"
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:"=t"(retval)
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:"0"(x), "u"(y)
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:"cc", "ax");
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return retval;
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JRT_END
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#endif // TARGET_COMPILER_gcc && !_WIN64
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@ -230,12 +230,15 @@ JRT_LEAF(jlong, SharedRuntime::lrem(jlong y, jlong x))
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JRT_END
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#ifdef _WIN64
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const juint float_sign_mask = 0x7FFFFFFF;
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const juint float_infinity = 0x7F800000;
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const julong double_sign_mask = CONST64(0x7FFFFFFFFFFFFFFF);
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const julong double_infinity = CONST64(0x7FF0000000000000);
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#endif
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JRT_LEAF(jfloat, SharedRuntime::frem(jfloat x, jfloat y))
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#if !defined(X86) || !defined(TARGET_COMPILER_gcc) || defined(_WIN64)
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JRT_LEAF(jfloat, SharedRuntime::frem(jfloat x, jfloat y))
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#ifdef _WIN64
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// 64-bit Windows on amd64 returns the wrong values for
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// infinity operands.
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@ -253,7 +256,6 @@ JRT_LEAF(jfloat, SharedRuntime::frem(jfloat x, jfloat y))
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#endif
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JRT_END
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JRT_LEAF(jdouble, SharedRuntime::drem(jdouble x, jdouble y))
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#ifdef _WIN64
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union { jdouble d; julong l; } xbits, ybits;
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@ -269,6 +271,7 @@ JRT_LEAF(jdouble, SharedRuntime::drem(jdouble x, jdouble y))
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return ((jdouble)fmod((double)x,(double)y));
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#endif
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JRT_END
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#endif // !X86 || !TARGET_COMPILER_gcc || _WIN64
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JRT_LEAF(jfloat, SharedRuntime::i2f(jint x))
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return (jfloat)x;
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229
test/micro/org/openjdk/bench/vm/floatingpoint/DremFrem.java
Normal file
229
test/micro/org/openjdk/bench/vm/floatingpoint/DremFrem.java
Normal file
@ -0,0 +1,229 @@
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/*
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* Copyright (c) 2023, Azul Systems, Inc. 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 org.openjdk.bench.vm.floatingpoint;
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import org.openjdk.jmh.annotations.Benchmark;
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import org.openjdk.jmh.annotations.BenchmarkMode;
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import org.openjdk.jmh.annotations.Mode;
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import org.openjdk.jmh.annotations.OperationsPerInvocation;
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import org.openjdk.jmh.annotations.OutputTimeUnit;
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import org.openjdk.jmh.annotations.Scope;
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import org.openjdk.jmh.annotations.Setup;
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import org.openjdk.jmh.annotations.State;
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import org.openjdk.jmh.infra.Blackhole;
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import java.util.Random;
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import java.util.concurrent.TimeUnit;
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/**
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* Tests for float and double modulo.
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* Testcase is based on: https://github.com/cirosantilli/java-cheat/blob/c5ffd8ea19c5620ce752b6c98b2d3579be2bef98/Nan.java
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*/
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@BenchmarkMode(Mode.AverageTime)
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@OutputTimeUnit(TimeUnit.NANOSECONDS)
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@State(Scope.Thread)
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public class DremFrem {
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private static final int DEFAULT_X_RANGE = 1 << 11;
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private static final int DEFAULT_Y_RANGE = 1 << 11;
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private static boolean regressionValue = false;
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@Benchmark
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@OperationsPerInvocation(DEFAULT_X_RANGE * DEFAULT_Y_RANGE)
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public void calcFloatJava(Blackhole bh) {
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for (int i = 0; i < DEFAULT_X_RANGE; i++) {
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for (int j = DEFAULT_Y_RANGE; j > 0; j--) {
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float x = i;
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float y = j;
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boolean result = (13.0F * x * x * x) % y == 1.0F;
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regressionValue = regressionValue & result;
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}
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}
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}
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@Benchmark
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@OperationsPerInvocation(DEFAULT_X_RANGE * DEFAULT_Y_RANGE)
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public void calcDoubleJava(Blackhole bh) {
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for (int i = 0; i < DEFAULT_X_RANGE; i++) {
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for (int j = DEFAULT_Y_RANGE; j > 0; j--) {
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double x = i;
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double y = j;
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boolean result = (13.0D * x * x * x) % y == 1.0D;
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regressionValue = regressionValue & result;
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}
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}
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}
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@SuppressWarnings("divzero")
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public void cornercaseFloatJava_divzero(Blackhole bh) {
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assert Float.isNaN(10 / 0);
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assert Float.isNaN(10 / 0);
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}
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@Benchmark
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@OperationsPerInvocation(DEFAULT_X_RANGE * DEFAULT_Y_RANGE)
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public void cornercaseFloatJava(Blackhole bh) {
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for (int i = 0; i < DEFAULT_X_RANGE * DEFAULT_Y_RANGE; i++) {
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// Generate some NaNs.
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float nan = Float.NaN;
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float zero_div_zero = 0.0f / 0.0f;
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float sqrt_negative = (float)Math.sqrt(-1.0);
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float log_negative = (float)Math.log(-1.0);
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float inf_minus_inf = Float.POSITIVE_INFINITY - Float.POSITIVE_INFINITY;
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float inf_times_zero = Float.POSITIVE_INFINITY * 0.0f;
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float quiet_nan1 = Float.intBitsToFloat(0x7fc00001);
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float quiet_nan2 = Float.intBitsToFloat(0x7fc00002);
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float signaling_nan1 = Float.intBitsToFloat(0x7fa00001);
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float signaling_nan2 = Float.intBitsToFloat(0x7fa00002);
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float nan_minus = -nan;
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// Generate some infinities.
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float positive_inf = Float.POSITIVE_INFINITY;
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float negative_inf = Float.NEGATIVE_INFINITY;
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float one_div_zero = 1.0f / 0.0f;
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float log_zero = (float)Math.log(0.0);
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// Double check that they are actually NaNs.
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assert Float.isNaN(nan);
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assert Float.isNaN(zero_div_zero);
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assert Float.isNaN(sqrt_negative);
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assert Float.isNaN(inf_minus_inf);
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assert Float.isNaN(inf_times_zero);
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assert Float.isNaN(quiet_nan1);
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assert Float.isNaN(quiet_nan2);
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assert Float.isNaN(signaling_nan1);
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assert Float.isNaN(signaling_nan2);
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assert Float.isNaN(nan_minus);
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assert Float.isNaN(log_negative);
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// Double check that they are infinities.
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assert Float.isInfinite(positive_inf);
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assert Float.isInfinite(negative_inf);
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assert !Float.isNaN(positive_inf);
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assert !Float.isNaN(negative_inf);
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assert one_div_zero == positive_inf;
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assert log_zero == negative_inf;
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// Double check infinities.
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assert Float.isNaN(positive_inf / 10);
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assert Float.isNaN(negative_inf / 10);
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cornercaseFloatJava_divzero(bh);
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assert (+10 / positive_inf) == +10;
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assert (+10 / negative_inf) == +10;
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assert (-10 / positive_inf) == -10;
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assert (-10 / negative_inf) == -10;
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// NaN comparisons always fail.
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// Therefore, all tests that we will do afterwards will be just isNaN.
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assert !(1.0f < nan);
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assert !(1.0f == nan);
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assert !(1.0f > nan);
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assert !(nan == nan);
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// NaN propagate through most operations.
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assert Float.isNaN(nan + 1.0f);
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assert Float.isNaN(1.0f + nan);
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assert Float.isNaN(nan + nan);
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assert Float.isNaN(nan / 1.0f);
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assert Float.isNaN(1.0f / nan);
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assert Float.isNaN((float)Math.sqrt((double)nan));
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}
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}
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@SuppressWarnings("divzero")
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public void cornercaseDoubleJava_divzero(Blackhole bh) {
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assert Double.isNaN(10 / 0);
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assert Double.isNaN(10 / 0);
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}
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@Benchmark
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@OperationsPerInvocation(DEFAULT_X_RANGE * DEFAULT_Y_RANGE)
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public void cornercaseDoubleJava(Blackhole bh) {
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for (int i = 0; i < DEFAULT_X_RANGE * DEFAULT_Y_RANGE; i++) {
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// Generate some NaNs.
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double nan = Double.NaN;
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double zero_div_zero = 0.0f / 0.0f;
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double sqrt_negative = (double)Math.sqrt(-1.0);
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double log_negative = (double)Math.log(-1.0);
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double inf_minus_inf = Double.POSITIVE_INFINITY - Double.POSITIVE_INFINITY;
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double inf_times_zero = Double.POSITIVE_INFINITY * 0.0f;
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double quiet_nan1 = Double.longBitsToDouble(0x7ffc000000000001L);
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double quiet_nan2 = Double.longBitsToDouble(0x7ffc000000000002L);
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double signaling_nan1 = Double.longBitsToDouble(0x7ffa000000000001L);
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double signaling_nan2 = Double.longBitsToDouble(0x7ffa000000000002L);
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double nan_minus = -nan;
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// Generate some infinities.
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double positive_inf = Double.POSITIVE_INFINITY;
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double negative_inf = Double.NEGATIVE_INFINITY;
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double one_div_zero = 1.0d / 0.0f;
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double log_zero = (double)Math.log(0.0);
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// Double check that they are actually NaNs.
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assert Double.isNaN(nan);
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assert Double.isNaN(zero_div_zero);
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assert Double.isNaN(sqrt_negative);
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assert Double.isNaN(inf_minus_inf);
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assert Double.isNaN(inf_times_zero);
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assert Double.isNaN(quiet_nan1);
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assert Double.isNaN(quiet_nan2);
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assert Double.isNaN(signaling_nan1);
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assert Double.isNaN(signaling_nan2);
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assert Double.isNaN(nan_minus);
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assert Double.isNaN(log_negative);
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// Double check that they are infinities.
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assert Double.isInfinite(positive_inf);
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assert Double.isInfinite(negative_inf);
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assert !Double.isNaN(positive_inf);
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assert !Double.isNaN(negative_inf);
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assert one_div_zero == positive_inf;
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assert log_zero == negative_inf;
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// Double check infinities.
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assert Double.isNaN(positive_inf / 10);
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assert Double.isNaN(negative_inf / 10);
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cornercaseDoubleJava_divzero(bh);
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assert (+10 / positive_inf) == +10;
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assert (+10 / negative_inf) == +10;
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assert (-10 / positive_inf) == -10;
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assert (-10 / negative_inf) == -10;
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// NaN comparisons always fail.
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// Therefore, all tests that we will do afterwards will be just isNaN.
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assert !(1.0d < nan);
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assert !(1.0d == nan);
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assert !(1.0d > nan);
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assert !(nan == nan);
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// NaN propagate through most operations.
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assert Double.isNaN(nan + 1.0d);
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assert Double.isNaN(1.0d + nan);
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assert Double.isNaN(nan + nan);
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assert Double.isNaN(nan / 1.0d);
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assert Double.isNaN(1.0d / nan);
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assert Double.isNaN((double)Math.sqrt((double)nan));
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}
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}
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}
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