jianmu
/
lammps
forked from lijiext/lammps
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
lammps/lib/gpu/gb_gpu_extra.h

332 lines
10 KiB
C++
Raw Blame History

/* ----------------------------------------------------------------------
LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
http://lammps.sandia.gov, Sandia National Laboratories
Steve Plimpton, sjplimp@sandia.gov
Copyright (2003) Sandia Corporation. Under the terms of Contract
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
certain rights in this software. This software is distributed under
the GNU General Public License.
See the README file in the top-level LAMMPS directory.
------------------------------------------------------------------------- */
/* ----------------------------------------------------------------------
Contributing authors: Mike Brown (SNL), wmbrown@sandia.gov
Peng Wang (Nvidia), penwang@nvidia.com
Paul Crozier (SNL), pscrozi@sandia.gov
------------------------------------------------------------------------- */
#ifndef GB_GPU_EXTRA_H
#define GB_GPU_EXTRA_H
#include "math.h"
#include "stdio.h"
#include "string.h"
/* ----------------------------------------------------------------------
Atomic update of global memory
------------------------------------------------------------------------- */
/*
template <class numtyp> __device__
inline void atomicAdd(numtyp *address, numtyp val);
template <>
__device__ inline void atomicAdd<float>(float *address, float val)
{
int i_val = __float_as_int(val);
int tmp0 = 0;
int tmp1;
while( (tmp1 = atomicCAS((int *)address, tmp0, i_val)) != tmp0) {
tmp0 = tmp1;
i_val = __float_as_int(val + __int_as_float(tmp1));
}
}*/
/* ----------------------------------------------------------------------
dot product of 2 vectors
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ numtyp gpu_dot3(const numtyp *v1, const numtyp *v2)
{
return v1[0]*v2[0]+v1[1]*v2[1]+v1[2]*v2[2];
}
/* ----------------------------------------------------------------------
cross product of 2 vectors
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ void gpu_cross3(const numtyp *v1,
const numtyp *v2, numtyp *ans)
{
ans[0] = v1[1]*v2[2]-v1[2]*v2[1];
ans[1] = v1[2]*v2[0]-v1[0]*v2[2];
ans[2] = v1[0]*v2[1]-v1[1]*v2[0];
}
/* ----------------------------------------------------------------------
determinant of a matrix
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ numtyp gpu_det3(const numtyp m[9])
{
numtyp ans = m[0]*m[4]*m[8] - m[0]*m[5]*m[7] -
m[3]*m[1]*m[8] + m[3]*m[2]*m[7] +
m[6]*m[1]*m[5] - m[6]*m[2]*m[4];
return ans;
}
/* ----------------------------------------------------------------------
diagonal matrix times a full matrix
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ void gpu_well_times3(const int i, const numtyp m[9],
numtyp ans[9])
{
ans[0] = _well_<numtyp>(i,0)*m[0];
ans[1] = _well_<numtyp>(i,0)*m[1];
ans[2] = _well_<numtyp>(i,0)*m[2];
ans[3] = _well_<numtyp>(i,1)*m[3];
ans[4] = _well_<numtyp>(i,1)*m[4];
ans[5] = _well_<numtyp>(i,1)*m[5];
ans[6] = _well_<numtyp>(i,2)*m[6];
ans[7] = _well_<numtyp>(i,2)*m[7];
ans[8] = _well_<numtyp>(i,2)*m[8];
}
/* ----------------------------------------------------------------------
diagonal matrix times a full matrix
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ void gpu_shape_times3(const int i, const numtyp m[9],
numtyp ans[9])
{
ans[0] = _shape_<numtyp>(i,0)*m[0];
ans[1] = _shape_<numtyp>(i,0)*m[1];
ans[2] = _shape_<numtyp>(i,0)*m[2];
ans[3] = _shape_<numtyp>(i,1)*m[3];
ans[4] = _shape_<numtyp>(i,1)*m[4];
ans[5] = _shape_<numtyp>(i,1)*m[5];
ans[6] = _shape_<numtyp>(i,2)*m[6];
ans[7] = _shape_<numtyp>(i,2)*m[7];
ans[8] = _shape_<numtyp>(i,2)*m[8];
}
/* ----------------------------------------------------------------------
add two matrices
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ void gpu_plus3(const numtyp m[9],
const numtyp m2[9], numtyp ans[9])
{
ans[0] = m[0]+m2[0];
ans[1] = m[1]+m2[1];
ans[2] = m[2]+m2[2];
ans[3] = m[3]+m2[3];
ans[4] = m[4]+m2[4];
ans[5] = m[5]+m2[5];
ans[6] = m[6]+m2[6];
ans[7] = m[7]+m2[7];
ans[8] = m[8]+m2[8];
}
/* ----------------------------------------------------------------------
multiply the transpose of mat1 times mat2
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ void gpu_transpose_times3(const numtyp m[9],
const numtyp m2[9],
numtyp ans[9])
{
ans[0] = m[0]*m2[0]+m[3]*m2[3]+m[6]*m2[6];
ans[1] = m[0]*m2[1]+m[3]*m2[4]+m[6]*m2[7];
ans[2] = m[0]*m2[2]+m[3]*m2[5]+m[6]*m2[8];
ans[3] = m[1]*m2[0]+m[4]*m2[3]+m[7]*m2[6];
ans[4] = m[1]*m2[1]+m[4]*m2[4]+m[7]*m2[7];
ans[5] = m[1]*m2[2]+m[4]*m2[5]+m[7]*m2[8];
ans[6] = m[2]*m2[0]+m[5]*m2[3]+m[8]*m2[6];
ans[7] = m[2]*m2[1]+m[5]*m2[4]+m[8]*m2[7];
ans[8] = m[2]*m2[2]+m[5]*m2[5]+m[8]*m2[8];
}
/* ----------------------------------------------------------------------
row vector times matrix
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ void gpu_row_times3(const numtyp *v,
const numtyp m[9], numtyp *ans)
{
ans[0] = m[0]*v[0]+v[1]*m[3]+v[2]*m[6];
ans[1] = v[0]*m[1]+m[4]*v[1]+v[2]*m[7];
ans[2] = v[0]*m[2]+v[1]*m[5]+m[8]*v[2];
}
/* ----------------------------------------------------------------------
solve Ax = b or M ans = v
use gaussian elimination & partial pivoting on matrix
error_flag set to 2 if bad matrix inversion attempted
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ void gpu_mldivide3(const numtyp m[9],
const numtyp *v, numtyp *ans,
int *error_flag)
{
// create augmented matrix for pivoting
numtyp aug[12], t;
aug[3] = v[0];
aug[0] = m[0];
aug[1] = m[1];
aug[2] = m[2];
aug[7] = v[1];
aug[4] = m[3];
aug[5] = m[4];
aug[6] = m[5];
aug[11] = v[2];
aug[8] = m[6];
aug[9] = m[7];
aug[10] = m[8];
if (fabs(aug[4]) > fabs(aug[0])) {
numtyp swapt;
swapt=aug[0]; aug[0]=aug[4]; aug[4]=swapt;
swapt=aug[1]; aug[1]=aug[5]; aug[5]=swapt;
swapt=aug[2]; aug[2]=aug[6]; aug[6]=swapt;
swapt=aug[3]; aug[3]=aug[7]; aug[7]=swapt;
}
if (fabs(aug[8]) > fabs(aug[0])) {
numtyp swapt;
swapt=aug[0]; aug[0]=aug[8]; aug[8]=swapt;
swapt=aug[1]; aug[1]=aug[9]; aug[9]=swapt;
swapt=aug[2]; aug[2]=aug[10]; aug[10]=swapt;
swapt=aug[3]; aug[3]=aug[11]; aug[11]=swapt;
}
if (aug[0] != (numtyp)0.0) {
if (0!=0) {
numtyp swapt;
swapt=aug[0]; aug[0]=aug[0]; aug[0]=swapt;
swapt=aug[1]; aug[1]=aug[1]; aug[1]=swapt;
swapt=aug[2]; aug[2]=aug[2]; aug[2]=swapt;
swapt=aug[3]; aug[3]=aug[3]; aug[3]=swapt;
}
} else if (aug[4] != (numtyp)0.0) {
if (1!=0) {
numtyp swapt;
swapt=aug[0]; aug[0]=aug[4]; aug[4]=swapt;
swapt=aug[1]; aug[1]=aug[5]; aug[5]=swapt;
swapt=aug[2]; aug[2]=aug[6]; aug[6]=swapt;
swapt=aug[3]; aug[3]=aug[7]; aug[7]=swapt;
}
} else if (aug[8] != (numtyp)0.0) {
if (2!=0) {
numtyp swapt;
swapt=aug[0]; aug[0]=aug[8]; aug[8]=swapt;
swapt=aug[1]; aug[1]=aug[9]; aug[9]=swapt;
swapt=aug[2]; aug[2]=aug[10]; aug[10]=swapt;
swapt=aug[3]; aug[3]=aug[11]; aug[11]=swapt;
}
} else
*error_flag=2;
t = aug[4]/aug[0];
aug[5]-=t*aug[1];
aug[6]-=t*aug[2];
aug[7]-=t*aug[3];
t = aug[8]/aug[0];
aug[9]-=t*aug[1];
aug[10]-=t*aug[2];
aug[11]-=t*aug[3];
if (fabs(aug[9]) > fabs(aug[5])) {
numtyp swapt;
swapt=aug[4]; aug[4]=aug[8]; aug[8]=swapt;
swapt=aug[5]; aug[5]=aug[9]; aug[9]=swapt;
swapt=aug[6]; aug[6]=aug[10]; aug[10]=swapt;
swapt=aug[7]; aug[7]=aug[11]; aug[11]=swapt;
}
if (aug[5] != (numtyp)0.0) {
if (1!=1) {
numtyp swapt;
swapt=aug[4]; aug[4]=aug[4]; aug[4]=swapt;
swapt=aug[5]; aug[5]=aug[5]; aug[5]=swapt;
swapt=aug[6]; aug[6]=aug[6]; aug[6]=swapt;
swapt=aug[7]; aug[7]=aug[7]; aug[7]=swapt;
}
} else if (aug[9] != (numtyp)0.0) {
if (2!=1) {
numtyp swapt;
swapt=aug[4]; aug[4]=aug[8]; aug[8]=swapt;
swapt=aug[5]; aug[5]=aug[9]; aug[9]=swapt;
swapt=aug[6]; aug[6]=aug[10]; aug[10]=swapt;
swapt=aug[7]; aug[7]=aug[11]; aug[11]=swapt;
}
}
t = aug[9]/aug[5];
aug[10]-=t*aug[6];
aug[11]-=t*aug[7];
if (aug[10] == (numtyp)0.0)
*error_flag=2;
ans[2] = aug[11]/aug[10];
t = (numtyp)0.0;
t += aug[6]*ans[2];
ans[1] = (aug[7]-t) / aug[5];
t = (numtyp)0.0;
t += aug[1]*ans[1];
t += aug[2]*ans[2];
ans[0] = (aug[3]-t) / aug[0];
}
/* ----------------------------------------------------------------------
compute rotation matrix from quaternion conjugate
quat = [w i j k]
------------------------------------------------------------------------- */
template <class numtyp>
static __inline__ __device__ void gpu_quat_to_mat_trans(const vec4 *qif,
const int qi,
numtyp mat[9])
{
vec4 q=qif[qi];
numtyp w2 = q.x*q.x;
numtyp i2 = q.y*q.y;
numtyp j2 = q.z*q.z;
numtyp k2 = q.w*q.w;
numtyp twoij = (numtyp)2.0*q.y*q.z;
numtyp twoik = (numtyp)2.0*q.y*q.w;
numtyp twojk = (numtyp)2.0*q.z*q.w;
numtyp twoiw = (numtyp)2.0*q.y*q.x;
numtyp twojw = (numtyp)2.0*q.z*q.x;
numtyp twokw = (numtyp)2.0*q.w*q.x;
mat[0] = w2+i2-j2-k2;
mat[3] = twoij-twokw;
mat[6] = twojw+twoik;
mat[1] = twoij+twokw;
mat[4] = w2-i2+j2-k2;
mat[7] = twojk-twoiw;
mat[2] = twoik-twojw;
mat[5] = twojk+twoiw;
mat[8] = w2-i2-j2+k2;
}
#endif
Reference in New Issue View Git Blame Copy Permalink