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refactor krylov solver

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This commit is contained in:
Xuchen Han
2020-04-27 15:48:51 -07:00
parent ad6bc07535
commit 5fe898f9f2
4 changed files with 145 additions and 152 deletions
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src/BulletSoftBody/btConjugateGradient.h
+17 -68
View File
@@ -15,24 +15,17 @@
#ifndef BT_CONJUGATE_GRADIENT_H
#define BT_CONJUGATE_GRADIENT_H
#include <iostream>
#include <cmath>
#include <limits>
#include <LinearMath/btAlignedObjectArray.h>
#include <LinearMath/btVector3.h>
#include "LinearMath/btQuickprof.h"
#include "btKrylovSolver.h"
template <class MatrixX>
class btConjugateGradient
class btConjugateGradient : public btKrylovSolver<MatrixX>
{
typedef btAlignedObjectArray<btVector3> TVStack;
typedef btKrylovSolver<MatrixX> Base;
TVStack r,p,z,temp;
int max_iterations;
btScalar tolerance_squared;
public:
btConjugateGradient(const int max_it_in)
: max_iterations(max_it_in)
: btKrylovSolver<MatrixX>(max_it_in, SIMD_EPSILON)
{
tolerance_squared = 1e-5;
}
virtual ~btConjugateGradient(){}
@@ -45,13 +38,13 @@ public:
reinitialize(b);
// r = b - A * x --with assigned dof zeroed out
A.multiply(x, temp);
r = sub(b, temp);
r = this->sub(b, temp);
A.project(r);
// z = M^(-1) * r
A.precondition(r, z);
A.project(z);
btScalar r_dot_z = dot(z,r);
if (r_dot_z <= tolerance_squared) {
btScalar r_dot_z = this->dot(z,r);
if (r_dot_z <= Base::m_tolerance) {
if (verbose)
{
std::cout << "Iteration = 0" << std::endl;
@@ -61,11 +54,11 @@ public:
}
p = z;
btScalar r_dot_z_new = r_dot_z;
for (int k = 1; k <= max_iterations; k++) {
for (int k = 1; k <= Base::m_maxIterations; k++) {
// temp = A*p
A.multiply(p, temp);
A.project(temp);
if (dot(p,temp) < SIMD_EPSILON)
if (this->dot(p,temp) < SIMD_EPSILON)
{
if (verbose)
std::cout << "Encountered negative direction in CG!" << std::endl;
@@ -76,16 +69,16 @@ public:
return k;
}
// alpha = r^T * z / (p^T * A * p)
btScalar alpha = r_dot_z_new / dot(p, temp);
btScalar alpha = r_dot_z_new / this->dot(p, temp);
// x += alpha * p;
multAndAddTo(alpha, p, x);
this->multAndAddTo(alpha, p, x);
// r -= alpha * temp;
multAndAddTo(-alpha, temp, r);
this->multAndAddTo(-alpha, temp, r);
// z = M^(-1) * r
A.precondition(r, z);
r_dot_z = r_dot_z_new;
r_dot_z_new = dot(r,z);
if (r_dot_z_new < tolerance_squared) {
r_dot_z_new = this->dot(r,z);
if (r_dot_z_new < Base::m_tolerance) {
if (verbose)
{
std::cout << "ConjugateGradient iterations " << k << std::endl;
@@ -94,13 +87,13 @@ public:
}
btScalar beta = r_dot_z_new/r_dot_z;
p = multAndAdd(beta, p, z);
p = this->multAndAdd(beta, p, z);
}
if (verbose)
{
std::cout << "ConjugateGradient max iterations reached " << max_iterations << std::endl;
std::cout << "ConjugateGradient max iterations reached " << Base::m_maxIterations << std::endl;
}
return max_iterations;
return Base::m_maxIterations;
}
void reinitialize(const TVStack& b)
@@ -110,49 +103,5 @@ public:
z.resize(b.size());
temp.resize(b.size());
}
TVStack sub(const TVStack& a, const TVStack& b)
{
// c = a-b
btAssert(a.size() == b.size());
TVStack c;
c.resize(a.size());
for (int i = 0; i < a.size(); ++i)
{
c[i] = a[i] - b[i];
}
return c;
}
btScalar squaredNorm(const TVStack& a)
{
return dot(a,a);
}
btScalar dot(const TVStack& a, const TVStack& b)
{
btScalar ans(0);
for (int i = 0; i < a.size(); ++i)
ans += a[i].dot(b[i]);
return ans;
}
void multAndAddTo(btScalar s, const TVStack& a, TVStack& result)
{
// result += s*a
btAssert(a.size() == result.size());
for (int i = 0; i < a.size(); ++i)
result[i] += s * a[i];
}
TVStack multAndAdd(btScalar s, const TVStack& a, const TVStack& b)
{
// result = a*s + b
TVStack result;
result.resize(a.size());
for (int i = 0; i < a.size(); ++i)
result[i] = s * a[i] + b[i];
return result;
}
};
#endif /* btConjugateGradient_h */
src/BulletSoftBody/btConjugateResidual.h
+20 -83
View File
@@ -15,28 +15,22 @@
#ifndef BT_CONJUGATE_RESIDUAL_H
#define BT_CONJUGATE_RESIDUAL_H
#include <iostream>
#include <cmath>
#include <limits>
#include <LinearMath/btAlignedObjectArray.h>
#include <LinearMath/btVector3.h>
#include <LinearMath/btScalar.h>
#include "LinearMath/btQuickprof.h"
#include "btKrylovSolver.h"
template <class MatrixX>
class btConjugateResidual
class btConjugateResidual : public btKrylovSolver<MatrixX>
{
typedef btAlignedObjectArray<btVector3> TVStack;
typedef btKrylovSolver<MatrixX> Base;
TVStack r,p,z,temp_p, temp_r, best_x;
// temp_r = A*r
// temp_p = A*p
// z = M^(-1) * temp_p = M^(-1) * A * p
int max_iterations;
btScalar tolerance_squared, best_r;
btScalar best_r;
public:
btConjugateResidual(const int max_it_in)
: max_iterations(max_it_in)
: Base(max_it_in, 1e-8)
{
tolerance_squared = 1e-5;
}
virtual ~btConjugateResidual(){}
@@ -49,12 +43,12 @@ public:
reinitialize(b);
// r = b - A * x --with assigned dof zeroed out
A.multiply(x, temp_r); // borrow temp_r here to store A*x
r = sub(b, temp_r);
r = this->sub(b, temp_r);
// z = M^(-1) * r
A.precondition(r, z); // borrow z to store preconditioned r
r = z;
btScalar residual_norm = norm(r);
if (residual_norm <= tolerance_squared) {
btScalar residual_norm = this->norm(r);
if (residual_norm <= Base::m_tolerance) {
return 0;
}
p = r;
@@ -63,41 +57,41 @@ public:
A.multiply(p, temp_p);
// temp_r = A*r
temp_r = temp_p;
r_dot_Ar = dot(r, temp_r);
for (int k = 1; k <= max_iterations; k++) {
r_dot_Ar = this->dot(r, temp_r);
for (int k = 1; k <= Base::m_maxIterations; k++) {
// z = M^(-1) * Ap
A.precondition(temp_p, z);
// alpha = r^T * A * r / (Ap)^T * M^-1 * Ap)
btScalar alpha = r_dot_Ar / dot(temp_p, z);
btScalar alpha = r_dot_Ar / this->dot(temp_p, z);
// x += alpha * p;
multAndAddTo(alpha, p, x);
this->multAndAddTo(alpha, p, x);
// r -= alpha * z;
multAndAddTo(-alpha, z, r);
btScalar norm_r = norm(r);
this->multAndAddTo(-alpha, z, r);
btScalar norm_r = this->norm(r);
if (norm_r < best_r)
{
best_x = x;
best_r = norm_r;
if (norm_r < tolerance_squared) {
if (norm_r < Base::m_tolerance) {
return k;
}
}
// temp_r = A * r;
A.multiply(r, temp_r);
r_dot_Ar_new = dot(r, temp_r);
r_dot_Ar_new = this->dot(r, temp_r);
btScalar beta = r_dot_Ar_new/r_dot_Ar;
r_dot_Ar = r_dot_Ar_new;
// p = beta*p + r;
p = multAndAdd(beta, p, r);
p = this->multAndAdd(beta, p, r);
// temp_p = beta*temp_p + temp_r;
temp_p = multAndAdd(beta, temp_p, temp_r);
temp_p = this->multAndAdd(beta, temp_p, temp_r);
}
if (verbose)
{
std::cout << "ConjugateResidual max iterations reached, residual = " << best_r << std::endl;
}
x = best_x;
return max_iterations;
return Base::m_maxIterations;
}
void reinitialize(const TVStack& b)
@@ -110,63 +104,6 @@ public:
best_x.resize(b.size());
best_r = SIMD_INFINITY;
}
TVStack sub(const TVStack& a, const TVStack& b)
{
// c = a-b
btAssert(a.size() == b.size());
TVStack c;
c.resize(a.size());
for (int i = 0; i < a.size(); ++i)
{
c[i] = a[i] - b[i];
}
return c;
}
btScalar squaredNorm(const TVStack& a)
{
return dot(a,a);
}
btScalar norm(const TVStack& a)
{
btScalar ret = 0;
for (int i = 0; i < a.size(); ++i)
{
for (int d = 0; d < 3; ++d)
{
ret = btMax(ret, btFabs(a[i][d]));
}
}
return ret;
}
btScalar dot(const TVStack& a, const TVStack& b)
{
btScalar ans(0);
for (int i = 0; i < a.size(); ++i)
ans += a[i].dot(b[i]);
return ans;
}
void multAndAddTo(btScalar s, const TVStack& a, TVStack& result)
{
// result += s*a
btAssert(a.size() == result.size());
for (int i = 0; i < a.size(); ++i)
result[i] += s * a[i];
}
TVStack multAndAdd(btScalar s, const TVStack& a, const TVStack& b)
{
// result = a*s + b
TVStack result;
result.resize(a.size());
for (int i = 0; i < a.size(); ++i)
result[i] = s * a[i] + b[i];
return result;
}
};
#endif /* btConjugateResidual_h */
src/BulletSoftBody/btDeformableContactConstraint.cpp
-1
View File
@@ -247,7 +247,6 @@ btScalar btDeformableRigidContactConstraint::solveConstraint(const btContactSolv
{
// separating in the normal direction
m_static = false;
// m_total_tangent_dv = btVector3(0,0,0);
impulse_tangent.setZero();
}
else
src/BulletSoftBody/btKrylovSolver.h
+108
View File
@@ -0,0 +1,108 @@
/*
Written by Xuchen Han <xuchenhan2015@u.northwestern.edu>
Bullet Continuous Collision Detection and Physics Library
Copyright (c) 2019 Google Inc. http://bulletphysics.org
This software is provided 'as-is', without any express or implied warranty.
In no event will the authors be held liable for any damages arising from the use of this software.
Permission is granted to anyone to use this software for any purpose,
including commercial applications, and to alter it and redistribute it freely,
subject to the following restrictions:
1. The origin of this software must not be misrepresented; you must not claim that you wrote the original software. If you use this software in a product, an acknowledgment in the product documentation would be appreciated but is not required.
2. Altered source versions must be plainly marked as such, and must not be misrepresented as being the original software.
3. This notice may not be removed or altered from any source distribution.
*/
#ifndef BT_KRYLOV_SOLVER_H
#define BT_KRYLOV_SOLVER_H
#include <iostream>
#include <cmath>
#include <limits>
#include <LinearMath/btAlignedObjectArray.h>
#include <LinearMath/btVector3.h>
#include <LinearMath/btScalar.h>
#include "LinearMath/btQuickprof.h"
template <class MatrixX>
class btKrylovSolver
{
typedef btAlignedObjectArray<btVector3> TVStack;
public:
int m_maxIterations;
btScalar m_tolerance;
btKrylovSolver(int maxIterations, btScalar tolerance)
: m_maxIterations(maxIterations)
, m_tolerance(tolerance)
{
}
virtual ~btKrylovSolver(){}
virtual int solve(MatrixX& A, TVStack& x, const TVStack& b, bool verbose = false) = 0;
virtual void reinitialize(const TVStack& b) = 0;
virtual SIMD_FORCE_INLINE TVStack sub(const TVStack& a, const TVStack& b)
{
// c = a-b
btAssert(a.size() == b.size());
TVStack c;
c.resize(a.size());
for (int i = 0; i < a.size(); ++i)
{
c[i] = a[i] - b[i];
}
return c;
}
virtual SIMD_FORCE_INLINE btScalar squaredNorm(const TVStack& a)
{
return dot(a,a);
}
virtual SIMD_FORCE_INLINE btScalar norm(const TVStack& a)
{
btScalar ret = 0;
for (int i = 0; i < a.size(); ++i)
{
for (int d = 0; d < 3; ++d)
{
ret = btMax(ret, btFabs(a[i][d]));
}
}
return ret;
}
virtual SIMD_FORCE_INLINE btScalar dot(const TVStack& a, const TVStack& b)
{
btScalar ans(0);
for (int i = 0; i < a.size(); ++i)
ans += a[i].dot(b[i]);
return ans;
}
virtual SIMD_FORCE_INLINE void multAndAddTo(btScalar s, const TVStack& a, TVStack& result)
{
// result += s*a
btAssert(a.size() == result.size());
for (int i = 0; i < a.size(); ++i)
result[i] += s * a[i];
}
virtual SIMD_FORCE_INLINE TVStack multAndAdd(btScalar s, const TVStack& a, const TVStack& b)
{
// result = a*s + b
TVStack result;
result.resize(a.size());
for (int i = 0; i < a.size(); ++i)
result[i] = s * a[i] + b[i];
return result;
}
virtual SIMD_FORCE_INLINE void setTolerance(btScalar tolerance)
{
m_tolerance = tolerance;
}
};
#endif /* BT_KRYLOV_SOLVER_H */