cuda-samples/Samples/eigenvalues/bisect_kernel_large_onei.cuh
2021-10-21 16:34:49 +05:30

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/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
*
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/* Determine eigenvalues for large matrices for intervals that contained after
* the first step one eigenvalue
*/
#ifndef _BISECT_KERNEL_LARGE_ONEI_H_
#define _BISECT_KERNEL_LARGE_ONEI_H_
#include <cooperative_groups.h>
namespace cg = cooperative_groups;
// includes, project
#include "config.h"
#include "util.h"
// additional kernel
#include "bisect_util.cu"
////////////////////////////////////////////////////////////////////////////////
//! Determine eigenvalues for large matrices for intervals that after
//! the first step contained one eigenvalue
//! @param g_d diagonal elements of symmetric, tridiagonal matrix
//! @param g_s superdiagonal elements of symmetric, tridiagonal matrix
//! @param n matrix size
//! @param num_intervals total number of intervals containing one eigenvalue
//! after the first step
//! @param g_left left interval limits
//! @param g_right right interval limits
//! @param g_pos index of interval / number of intervals that are smaller than
//! right interval limit
//! @param precision desired precision of eigenvalues
////////////////////////////////////////////////////////////////////////////////
__global__ void bisectKernelLarge_OneIntervals(
float *g_d, float *g_s, const unsigned int n, unsigned int num_intervals,
float *g_left, float *g_right, unsigned int *g_pos, float precision) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
const unsigned int gtid = (blockDim.x * blockIdx.x) + threadIdx.x;
__shared__ float s_left_scratch[MAX_THREADS_BLOCK];
__shared__ float s_right_scratch[MAX_THREADS_BLOCK];
// active interval of thread
// left and right limit of current interval
float left, right;
// number of threads smaller than the right limit (also corresponds to the
// global index of the eigenvalues contained in the active interval)
unsigned int right_count;
// flag if current thread converged
unsigned int converged = 0;
// midpoint when current interval is subdivided
float mid = 0.0f;
// number of eigenvalues less than mid
unsigned int mid_count = 0;
// read data from global memory
if (gtid < num_intervals) {
left = g_left[gtid];
right = g_right[gtid];
right_count = g_pos[gtid];
}
// flag to determine if all threads converged to eigenvalue
__shared__ unsigned int converged_all_threads;
// initialized shared flag
if (0 == threadIdx.x) {
converged_all_threads = 0;
}
cg::sync(cta);
// process until all threads converged to an eigenvalue
// while( 0 == converged_all_threads) {
while (true) {
atomicExch(&converged_all_threads, 1);
// update midpoint for all active threads
if ((gtid < num_intervals) && (0 == converged)) {
mid = computeMidpoint(left, right);
}
// find number of eigenvalues that are smaller than midpoint
mid_count = computeNumSmallerEigenvalsLarge(
g_d, g_s, n, mid, gtid, num_intervals, s_left_scratch, s_right_scratch,
converged, cta);
cg::sync(cta);
// for all active threads
if ((gtid < num_intervals) && (0 == converged)) {
// udpate intervals -- always one child interval survives
if (right_count == mid_count) {
right = mid;
} else {
left = mid;
}
// check for convergence
float t0 = right - left;
float t1 = max(abs(right), abs(left)) * precision;
if (t0 < min(precision, t1)) {
float lambda = computeMidpoint(left, right);
left = lambda;
right = lambda;
converged = 1;
} else {
atomicExch(&converged_all_threads, 0);
}
}
cg::sync(cta);
if (1 == converged_all_threads) {
break;
}
cg::sync(cta);
}
// write data back to global memory
cg::sync(cta);
if (gtid < num_intervals) {
// intervals converged so left and right interval limit are both identical
// and identical to the eigenvalue
g_left[gtid] = left;
}
}
#endif // #ifndef _BISECT_KERNEL_LARGE_ONEI_H_