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161 lines
5.5 KiB
Plaintext
161 lines
5.5 KiB
Plaintext
/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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/* Determine eigenvalues for large matrices for intervals that contained after
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* the first step one eigenvalue
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*/
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#ifndef _BISECT_KERNEL_LARGE_ONEI_H_
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#define _BISECT_KERNEL_LARGE_ONEI_H_
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#include <cooperative_groups.h>
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namespace cg = cooperative_groups;
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// includes, project
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#include "config.h"
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#include "util.h"
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// additional kernel
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#include "bisect_util.cu"
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////////////////////////////////////////////////////////////////////////////////
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//! Determine eigenvalues for large matrices for intervals that after
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//! the first step contained one eigenvalue
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//! @param g_d diagonal elements of symmetric, tridiagonal matrix
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//! @param g_s superdiagonal elements of symmetric, tridiagonal matrix
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//! @param n matrix size
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//! @param num_intervals total number of intervals containing one eigenvalue
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//! after the first step
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//! @param g_left left interval limits
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//! @param g_right right interval limits
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//! @param g_pos index of interval / number of intervals that are smaller than
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//! right interval limit
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//! @param precision desired precision of eigenvalues
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////////////////////////////////////////////////////////////////////////////////
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__global__ void bisectKernelLarge_OneIntervals(
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float *g_d, float *g_s, const unsigned int n, unsigned int num_intervals,
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float *g_left, float *g_right, unsigned int *g_pos, float precision) {
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// Handle to thread block group
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cg::thread_block cta = cg::this_thread_block();
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const unsigned int gtid = (blockDim.x * blockIdx.x) + threadIdx.x;
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__shared__ float s_left_scratch[MAX_THREADS_BLOCK];
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__shared__ float s_right_scratch[MAX_THREADS_BLOCK];
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// active interval of thread
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// left and right limit of current interval
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float left, right;
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// number of threads smaller than the right limit (also corresponds to the
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// global index of the eigenvalues contained in the active interval)
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unsigned int right_count;
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// flag if current thread converged
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unsigned int converged = 0;
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// midpoint when current interval is subdivided
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float mid = 0.0f;
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// number of eigenvalues less than mid
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unsigned int mid_count = 0;
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// read data from global memory
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if (gtid < num_intervals) {
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left = g_left[gtid];
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right = g_right[gtid];
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right_count = g_pos[gtid];
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}
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// flag to determine if all threads converged to eigenvalue
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__shared__ unsigned int converged_all_threads;
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// initialized shared flag
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if (0 == threadIdx.x) {
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converged_all_threads = 0;
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}
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cg::sync(cta);
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// process until all threads converged to an eigenvalue
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// while( 0 == converged_all_threads) {
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while (true) {
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atomicExch(&converged_all_threads, 1);
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// update midpoint for all active threads
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if ((gtid < num_intervals) && (0 == converged)) {
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mid = computeMidpoint(left, right);
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}
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// find number of eigenvalues that are smaller than midpoint
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mid_count = computeNumSmallerEigenvalsLarge(
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g_d, g_s, n, mid, gtid, num_intervals, s_left_scratch, s_right_scratch,
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converged, cta);
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cg::sync(cta);
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// for all active threads
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if ((gtid < num_intervals) && (0 == converged)) {
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// udpate intervals -- always one child interval survives
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if (right_count == mid_count) {
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right = mid;
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} else {
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left = mid;
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}
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// check for convergence
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float t0 = right - left;
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float t1 = max(abs(right), abs(left)) * precision;
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if (t0 < min(precision, t1)) {
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float lambda = computeMidpoint(left, right);
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left = lambda;
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right = lambda;
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converged = 1;
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} else {
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atomicExch(&converged_all_threads, 0);
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}
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}
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cg::sync(cta);
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if (1 == converged_all_threads) {
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break;
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}
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cg::sync(cta);
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}
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// write data back to global memory
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cg::sync(cta);
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if (gtid < num_intervals) {
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// intervals converged so left and right interval limit are both identical
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// and identical to the eigenvalue
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g_left[gtid] = left;
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}
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}
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#endif // #ifndef _BISECT_KERNEL_LARGE_ONEI_H_
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