simplify preconditioning the system matrix, bugfix
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@ -64,15 +64,9 @@ private:
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// Compute the constraint projection matrix S.
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void Compute_S(b3Mat33* S);
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// Solve Ax = b using the Modified Conjugate Gradient (MCG).
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// Output x and the residual error f.
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void Solve_MCG(b3DenseVec3& x0, b3DenseVec3& f, u32& iterations, const b3SparseMat33& A, const b3DenseVec3& b, const b3Mat33* S) const;
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// Solve Ax = b using MCG with Jacobi preconditioning.
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// Output x and the residual error f.
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// This method is slower than MCG because we have to compute the preconditioning
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// matrix P, but it can improve convergence.
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void Solve_MPCG(b3DenseVec3& x0, b3DenseVec3& f, u32& iterations, const b3SparseMat33& A, const b3DenseVec3& b, const b3Mat33* S) const;
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// Solve Ax = b.
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// Output x and the residual error f = Ax - b ~ 0.
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void Solve(b3DenseVec3& x0, b3DenseVec3& f, u32& iterations, const b3SparseMat33& A, const b3DenseVec3& b, const b3Mat33* S) const;
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b3SpringCloth * m_cloth;
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float32 m_h;
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@ -26,9 +26,7 @@
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// Here, we solve Ax = b using the Modified Conjugate Gradient method.
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// This work is based on the paper "Large Steps in Cloth Simulation - David Baraff, Andrew Witkin".
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// Enable preconditioning. It can be slow, depending on
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// how the preconditioning matrix is computed, but it can help
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// to increase convergence.
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// Enable preconditioning.
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bool b3_enablePrecontitioning = false;
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b3SpringSolver::b3SpringSolver(const b3SpringSolverDef& def)
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@ -103,14 +101,7 @@ void b3SpringSolver::Solve(b3DenseVec3& f)
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b3Mat33* S = (b3Mat33*)m_allocator->Allocate(m_massCount * sizeof(b3Mat33));
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Compute_S(S);
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if (b3_enablePrecontitioning)
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{
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Solve_MPCG(x, f, m_iterations, A, b, S);
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}
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else
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{
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Solve_MCG(x, f, m_iterations, A, b, S);
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}
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Solve(x, f, m_iterations, A, b, S);
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// Update state
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for (u32 i = 0; i < m_massCount; ++i)
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@ -314,17 +305,6 @@ void b3SpringSolver::Compute_A_b(b3SparseMat33& SA, b3DenseVec3& b) const
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// Assembly sparsity
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u32 nzCount = 0;
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#if 0
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for (u32 i = 0; i < m_massCount * m_massCount; ++i)
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{
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b3Mat33 a = A[i];
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if (b3IsZero(a) == false)
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{
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++nzCount;
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}
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}
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#endif
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SA.row_ptrs[0] = 0;
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for (u32 i = 0; i < m_massCount; ++i)
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@ -410,7 +390,7 @@ void b3SpringSolver::Compute_S(b3Mat33* out)
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{
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if (m_contacts[i].lockT1 == true)
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{
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b3Vec3 t1 = m_contacts[i].t2;
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b3Vec3 t1 = m_contacts[i].t1;
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S -= b3Outer(t1, t1);
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}
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@ -439,7 +419,7 @@ void b3SpringSolver::Compute_S(b3Mat33* out)
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}
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}
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// Maintains invariants inside the MCG solver.
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// S * v
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static void b3Filter(b3DenseVec3& out,
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const b3DenseVec3& v, const b3Mat33* S, u32 massCount)
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{
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@ -449,66 +429,6 @@ static void b3Filter(b3DenseVec3& out,
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}
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}
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void b3SpringSolver::Solve_MCG(b3DenseVec3& dv, b3DenseVec3& e, u32& iterations, const b3SparseMat33& A, const b3DenseVec3& b, const b3Mat33* S) const
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{
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// r = filter(b - Adv)
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b3DenseVec3 r = b - A * dv;
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b3Filter(r, r, S, m_massCount);
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// c = r
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b3DenseVec3 c = r;
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// eps0 = dot(r, r)
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float32 eps0 = b3Dot(r, r);
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// epsNew = dot(r, r)
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float32 epsNew = eps0;
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// [0, 1]
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const float32 kTol = 0.02f;
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// Limit number of iterations to prevent cycling.
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const u32 kMaxIters = 200;
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// Main iteration loop.
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u32 iter = 0;
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while (iter < kMaxIters && epsNew > kTol * kTol * eps0)
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{
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// q = filter(A * c)
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b3DenseVec3 q = A * c;
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b3Filter(q, q, S, m_massCount);
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// alpha = epsNew / dot(c, q)
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float32 alpha = epsNew / b3Dot(c, q);
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// dv = dv + alpha * c
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dv = dv + alpha * c;
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// r = r - alpha * q
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r = r - alpha * q;
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// epsOld = epsNew
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float32 epsOld = epsNew;
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// epsNew = dot(r, r)
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epsNew = b3Dot(r, r);
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float32 beta = epsNew / epsOld;
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// c = filter(r + beta * c)
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c = r + beta * c;
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b3Filter(c, c, S, m_massCount);
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++iter;
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}
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iterations = iter;
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// Residual error
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// f = A * x - b
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e = A * dv - b;
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}
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// Sylvester's Criterion
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static bool b3IsPD(const b3Mat33* diagA, u32 n)
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{
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@ -528,40 +448,51 @@ static bool b3IsPD(const b3Mat33* diagA, u32 n)
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return true;
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}
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void b3SpringSolver::Solve_MPCG(b3DenseVec3& dv, b3DenseVec3& e, u32& iterations, const b3SparseMat33& A, const b3DenseVec3& b, const b3Mat33* S) const
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void b3SpringSolver::Solve(b3DenseVec3& dv, b3DenseVec3& e, u32& iterations, const b3SparseMat33& A, const b3DenseVec3& b, const b3Mat33* S) const
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{
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// P = diag(A)^-1
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b3DenseVec3 P(m_massCount);
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b3DenseVec3 inv_P(m_massCount);
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// diag(A)
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b3Mat33* diagA = (b3Mat33*)m_allocator->Allocate(m_massCount * sizeof(b3Mat33));
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A.AssembleDiagonal(diagA);
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// Compute P, P^-1
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bool isPD = true;
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for (u32 i = 0; i < m_massCount; ++i)
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if (b3_enablePrecontitioning)
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{
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b3Mat33 D = diagA[i];
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// P = diag(A)^-1
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if (b3Det(D.x, D.y, D.z) <= B3_EPSILON)
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// diag(A)
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b3Mat33* diagA = (b3Mat33*)m_allocator->Allocate(m_massCount * sizeof(b3Mat33));
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A.AssembleDiagonal(diagA);
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for (u32 i = 0; i < m_massCount; ++i)
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{
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isPD = false;
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b3Mat33 D = diagA[i];
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// Sylvester's Criterion
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B3_ASSERT(b3Det(D.x, D.y, D.z) <= B3_EPSILON);
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B3_ASSERT(D[0][0] != 0.0f);
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B3_ASSERT(D[1][1] != 0.0f);
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B3_ASSERT(D[2][2] != 0.0f);
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P[i] = b3Vec3(1.0f / D[0][0], 1.0f / D[1][1], 1.0f / D[2][2]);
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inv_P[i] = b3Vec3(D[0][0], D[1][1], D[2][2]);
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}
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B3_ASSERT(D[0][0] != 0.0f);
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B3_ASSERT(D[1][1] != 0.0f);
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B3_ASSERT(D[2][2] != 0.0f);
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P[i] = b3Vec3(1.0f / D[0][0], 1.0f / D[1][1], 1.0f / D[2][2]);
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inv_P[i] = b3Vec3(D[0][0], D[1][1], D[2][2]);
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m_allocator->Free(diagA);
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}
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else
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{
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// P = I
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for (u32 i = 0; i < m_massCount; ++i)
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{
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P[i].Set(1.0f, 1.0f, 1.0f);
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}
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B3_ASSERT(isPD == true);
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m_allocator->Free(diagA);
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for (u32 i = 0; i < m_massCount; ++i)
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{
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inv_P[i].Set(1.0f, 1.0f, 1.0f);
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}
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}
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// eps0 = dot( filter(b), P * filter(b) )
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b3DenseVec3 filtered_b(m_massCount);
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@ -595,10 +526,10 @@ void b3SpringSolver::Solve_MPCG(b3DenseVec3& dv, b3DenseVec3& e, u32& iterations
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float32 epsNew = b3Dot(r, c);
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// [0, 1]
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const float32 kTol = 0.02f;
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const float32 kTol = 1000.0f * B3_EPSILON;
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// Limit number of iterations to prevent cycling.
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const u32 kMaxIters = 200;
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const u32 kMaxIters = 1000;
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// Main iteration loop.
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u32 iter = 0;
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