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Fast number theoretic transform implementation using Aparapi

There is a newer version: 1.14.0

/*
 * MIT License
 *
 * Copyright (c) 2002-2023 Mikko Tommila
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */

/**
Transforms for using a GPU via the aparapi library.

This package contains Number-Theoretic Transform implementations that can use
the GPU (Graphics Processing Unit) for executing the transforms. There is significant
overhead in invoking the GPU, e.g. in transferring the data between the main memory
and the GPU memory, so for small data sets there is usually no performance improvement,
and in many cases performance can be even significantly slower. However for very large
calculations, e.g. one billion digits, using the GPU can improve the performance noticeably,
depending on the hardware used.
*/

package org.apfloat.aparapi;