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bisect_kernel_small.cuh
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/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/* Determine eigenvalues for small symmetric, tridiagonal matrix */
#ifndef _BISECT_KERNEL_SMALL_H_
#define _BISECT_KERNEL_SMALL_H_
#include <cooperative_groups.h>
namespace cg = cooperative_groups;
// includes, project
#include "config.h"
#include "util.h"
// additional kernel
#include "bisect_util.cu"
////////////////////////////////////////////////////////////////////////////////
//! Bisection to find eigenvalues of a real, symmetric, and tridiagonal matrix
//! @param g_d diagonal elements in global memory
//! @param g_s superdiagonal elements in global elements (stored so that the
//! element *(g_s - 1) can be accessed an equals 0
//! @param n size of matrix
//! @param lg lower bound of input interval (e.g. Gerschgorin interval)
//! @param ug upper bound of input interval (e.g. Gerschgorin interval)
//! @param lg_eig_count number of eigenvalues that are smaller than \a lg
//! @param lu_eig_count number of eigenvalues that are smaller than \a lu
//! @param epsilon desired accuracy of eigenvalues to compute
////////////////////////////////////////////////////////////////////////////////
__global__ void bisectKernel(float *g_d, float *g_s, const unsigned int n,
float *g_left, float *g_right,
unsigned int *g_left_count,
unsigned int *g_right_count, const float lg,
const float ug, const unsigned int lg_eig_count,
const unsigned int ug_eig_count, float epsilon) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
// intervals (store left and right because the subdivision tree is in general
// not dense
__shared__ float s_left[MAX_THREADS_BLOCK_SMALL_MATRIX];
__shared__ float s_right[MAX_THREADS_BLOCK_SMALL_MATRIX];
// number of eigenvalues that are smaller than s_left / s_right
// (correspondence is realized via indices)
__shared__ unsigned int s_left_count[MAX_THREADS_BLOCK_SMALL_MATRIX];
__shared__ unsigned int s_right_count[MAX_THREADS_BLOCK_SMALL_MATRIX];
// helper for stream compaction
__shared__ unsigned int s_compaction_list[MAX_THREADS_BLOCK_SMALL_MATRIX + 1];
// state variables for whole block
// if 0 then compaction of second chunk of child intervals is not necessary
// (because all intervals had exactly one non-dead child)
__shared__ unsigned int compact_second_chunk;
__shared__ unsigned int all_threads_converged;
// number of currently active threads
__shared__ unsigned int num_threads_active;
// number of threads to use for stream compaction
__shared__ unsigned int num_threads_compaction;
// helper for exclusive scan
unsigned int *s_compaction_list_exc = s_compaction_list + 1;
// variables for currently processed interval
// left and right limit of active interval
float left = 0.0f;
float right = 0.0f;
unsigned int left_count = 0;
unsigned int right_count = 0;
// midpoint of active interval
float mid = 0.0f;
// number of eigenvalues smaller then mid
unsigned int mid_count = 0;
// affected from compaction
unsigned int is_active_second = 0;
s_compaction_list[threadIdx.x] = 0;
s_left[threadIdx.x] = 0;
s_right[threadIdx.x] = 0;
s_left_count[threadIdx.x] = 0;
s_right_count[threadIdx.x] = 0;
cg::sync(cta);
// set up initial configuration
if (0 == threadIdx.x) {
s_left[0] = lg;
s_right[0] = ug;
s_left_count[0] = lg_eig_count;
s_right_count[0] = ug_eig_count;
compact_second_chunk = 0;
num_threads_active = 1;
num_threads_compaction = 1;
}
// for all active threads read intervals from the last level
// the number of (worst case) active threads per level l is 2^l
while (true) {
all_threads_converged = 1;
cg::sync(cta);
is_active_second = 0;
subdivideActiveInterval(threadIdx.x, s_left, s_right, s_left_count,
s_right_count, num_threads_active, left, right,
left_count, right_count, mid,
all_threads_converged);
cg::sync(cta);
// check if done
if (1 == all_threads_converged) {
break;
}
cg::sync(cta);
// compute number of eigenvalues smaller than mid
// use all threads for reading the necessary matrix data from global
// memory
// use s_left and s_right as scratch space for diagonal and
// superdiagonal of matrix
mid_count = computeNumSmallerEigenvals(g_d, g_s, n, mid, threadIdx.x,
num_threads_active, s_left, s_right,
(left == right), cta);
cg::sync(cta);
// store intervals
// for all threads store the first child interval in a continuous chunk of
// memory, and the second child interval -- if it exists -- in a second
// chunk; it is likely that all threads reach convergence up to
// \a epsilon at the same level; furthermore, for higher level most / all
// threads will have only one child, storing the first child compactly will
// (first) avoid to perform a compaction step on the first chunk, (second)
// make it for higher levels (when all threads / intervals have
// exactly one child) unnecessary to perform a compaction of the second
// chunk
if (threadIdx.x < num_threads_active) {
if (left != right) {
// store intervals
storeNonEmptyIntervals(threadIdx.x, num_threads_active, s_left, s_right,
s_left_count, s_right_count, left, mid, right,
left_count, mid_count, right_count, epsilon,
compact_second_chunk, s_compaction_list_exc,
is_active_second);
} else {
storeIntervalConverged(
s_left, s_right, s_left_count, s_right_count, left, mid, right,
left_count, mid_count, right_count, s_compaction_list_exc,
compact_second_chunk, num_threads_active, is_active_second);
}
}
// necessary so that compact_second_chunk is up-to-date
cg::sync(cta);
// perform compaction of chunk where second children are stored
// scan of (num_threads_active / 2) elements, thus at most
// (num_threads_active / 4) threads are needed
if (compact_second_chunk > 0) {
createIndicesCompaction(s_compaction_list_exc, num_threads_compaction,
cta);
compactIntervals(s_left, s_right, s_left_count, s_right_count, mid, right,
mid_count, right_count, s_compaction_list,
num_threads_active, is_active_second);
}
cg::sync(cta);
if (0 == threadIdx.x) {
// update number of active threads with result of reduction
num_threads_active += s_compaction_list[num_threads_active];
num_threads_compaction = ceilPow2(num_threads_active);
compact_second_chunk = 0;
}
cg::sync(cta);
}
cg::sync(cta);
// write resulting intervals to global mem
// for all threads write if they have been converged to an eigenvalue to
// a separate array
// at most n valid intervals
if (threadIdx.x < n) {
// intervals converged so left and right limit are identical
g_left[threadIdx.x] = s_left[threadIdx.x];
// left count is sufficient to have global order
g_left_count[threadIdx.x] = s_left_count[threadIdx.x];
}
}
#endif // #ifndef _BISECT_KERNEL_SMALL_H_