src/java.base/share/classes/java/lang/Math.java

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rev 13339 : Move sun.misc math support classes to jdk.internal.math


   9  * by Oracle in the LICENSE file that accompanied this code.
  10  *
  11  * This code is distributed in the hope that it will be useful, but WITHOUT
  12  * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
  13  * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
  14  * version 2 for more details (a copy is included in the LICENSE file that
  15  * accompanied this code).
  16  *
  17  * You should have received a copy of the GNU General Public License version
  18  * 2 along with this work; if not, write to the Free Software Foundation,
  19  * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
  20  *
  21  * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
  22  * or visit www.oracle.com if you need additional information or have any
  23  * questions.
  24  */
  25 
  26 package java.lang;
  27 
  28 import java.util.Random;
  29 import sun.misc.FloatConsts;
  30 import sun.misc.DoubleConsts;
  31 import jdk.internal.HotSpotIntrinsicCandidate;
  32 
  33 /**
  34  * The class {@code Math} contains methods for performing basic
  35  * numeric operations such as the elementary exponential, logarithm,
  36  * square root, and trigonometric functions.
  37  *
  38  * <p>Unlike some of the numeric methods of class
  39  * {@code StrictMath}, all implementations of the equivalent
  40  * functions of class {@code Math} are not defined to return the
  41  * bit-for-bit same results.  This relaxation permits
  42  * better-performing implementations where strict reproducibility is
  43  * not required.
  44  *
  45  * <p>By default many of the {@code Math} methods simply call
  46  * the equivalent method in {@code StrictMath} for their
  47  * implementation.  Code generators are encouraged to use
  48  * platform-specific native libraries or microprocessor instructions,
  49  * where available, to provide higher-performance implementations of
  50  * {@code Math} methods.  Such higher-performance




   9  * by Oracle in the LICENSE file that accompanied this code.
  10  *
  11  * This code is distributed in the hope that it will be useful, but WITHOUT
  12  * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
  13  * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
  14  * version 2 for more details (a copy is included in the LICENSE file that
  15  * accompanied this code).
  16  *
  17  * You should have received a copy of the GNU General Public License version
  18  * 2 along with this work; if not, write to the Free Software Foundation,
  19  * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
  20  *
  21  * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
  22  * or visit www.oracle.com if you need additional information or have any
  23  * questions.
  24  */
  25 
  26 package java.lang;
  27 
  28 import java.util.Random;
  29 import jdk.internal.math.FloatConsts;
  30 import jdk.internal.math.DoubleConsts;
  31 import jdk.internal.HotSpotIntrinsicCandidate;
  32 
  33 /**
  34  * The class {@code Math} contains methods for performing basic
  35  * numeric operations such as the elementary exponential, logarithm,
  36  * square root, and trigonometric functions.
  37  *
  38  * <p>Unlike some of the numeric methods of class
  39  * {@code StrictMath}, all implementations of the equivalent
  40  * functions of class {@code Math} are not defined to return the
  41  * bit-for-bit same results.  This relaxation permits
  42  * better-performing implementations where strict reproducibility is
  43  * not required.
  44  *
  45  * <p>By default many of the {@code Math} methods simply call
  46  * the equivalent method in {@code StrictMath} for their
  47  * implementation.  Code generators are encouraged to use
  48  * platform-specific native libraries or microprocessor instructions,
  49  * where available, to provide higher-performance implementations of
  50  * {@code Math} methods.  Such higher-performance