python – 使用PyCuda的遗传细胞自动机,如何有效地将每个细胞的大量数据传递给CUDA内核？

我正在使用PyCuda开发一种遗传细胞自动机.每个细胞都会有大量的基因组数据以及细胞参数.我想知道什么是最有效的方法1)将单元数据传递给CUDA内核,然后2)处理这些数据.

我从一个特别糟糕的(imo)开始,但仍在使用解决方案.它将每个参数传递到一个单独的数组中,然后使用switch-case和大量重复代码处理它们.

然后,意识到每个内核函数可以快速结束相当多的参数,并决定重写它.

第二种解决方案是将所有单元格的参数存储在具有额外维度的单个数组中.这在代码中更优雅,但令人惊讶的是代码运行速度慢了10倍！

为了更清楚,我需要为每个单元格存储完整的数据列表：

>(Fc,Mc,Tc)：3x(int) – 细胞的当前“味道”,质量和温度
>(Rfc,Rmc,Rtc)：3x(int) – 单元的当前寄存器
>(Fi,Mi,Ti)每个邻居：8 * 3x(int) – 传入值
>(Rfi,Rmi,Rti)每个邻居：8 * 3x(int) – 传入值
>门方向：1x(uchar)
>执行指针：1x(uchar)
>目前的微操作内存：32x(uchar)
>最后一步的微操作记忆：32x(uchar)

我分两个阶段分裂自动化步骤.首先(发射阶段)计算每个小区邻居的(Fi,Mi,Ti).第二(吸收阶段)是将8x(Fi,Mi,Ti)值与当前单元的状态混合.尚未实施基因组或寄存器,但我需要将其数据传递给未来.

所以,我的第一个解决方案的代码是：

Mk = 64
Tk = 1000

emit_gpu = ElementwiseKernel("int3 *cells, int3 *dcells0, int3 *dcells1, int3 *dcells2, int3 *dcells3, int3 *dcells4, int3 *dcells5, int3 *dcells6, int3 *dcells7, int w, int h", """
    int x = i / h;
    int y = i % h;

    int3 cell = cells[i];
    float M = (float) cell.y;
    float T = (float) cell.z;
    int Mi = (int) (fmin(1, T / Tk) * M);
    cells[i].y -= Mi;
    cells[i].z -= (int) (T * fmin(1, T / Tk) / 1);

    int Fi = cell.x;
    int Mbase = Mi / 8;
    int Mpart = Mi % 8;
    int Madd;
    int Ti = cell.z;
    int ii, xo, yo;

    for (int cc = 0; cc < 9; cc++) {
      int c = (cc + Fi) % 9;
      if (c == 4) continue;
      xo = x + c%3 - 1;
      if (xo < 0) xo = w + xo;
      if (xo >= w) xo = xo - w;
      yo = y + c/3 - 1;
      if (yo < 0) yo = h + yo;
      if (xo >= w) yo = yo - h;
      ii = xo * h + yo;
      if (Mpart > 0) { Madd = 1; Mpart--;} else Madd = 0;
      switch(c) {
        case 0: dcells0[ii] = make_int3(Fi, Mbase + Madd, Ti); break;
        case 1: dcells1[ii] = make_int3(Fi, Mbase + Madd, Ti); break;
        case 2: dcells2[ii] = make_int3(Fi, Mbase + Madd, Ti); break;
        case 3: dcells3[ii] = make_int3(Fi, Mbase + Madd, Ti); break;
        case 5: dcells4[ii] = make_int3(Fi, Mbase + Madd, Ti); break;
        case 6: dcells5[ii] = make_int3(Fi, Mbase + Madd, Ti); break;
        case 7: dcells6[ii] = make_int3(Fi, Mbase + Madd, Ti); break;
        case 8: dcells7[ii] = make_int3(Fi, Mbase + Madd, Ti); break;
        default: break;
      }

    } 
""", "ca_prepare", preamble="""
#define Tk %s
""" % Tk)

absorb_gpu = ElementwiseKernel("int3 *cells, int3 *dcells0, int3 *dcells1, int3 *dcells2, int3 *dcells3, int3 *dcells4, int3 *dcells5, int3 *dcells6, int3 *dcells7, int *img, int w, int h", """
    int3 cell = cells[i];

    int3 dcell = dcells0[i];
    cell = cell + calc_d(cell.x, cell.y, cell.z, dcell.x, dcell.y, dcell.z);
    cell.x = cell.x % 360;
    if (cell.x < 0) cell.x += 360;

    dcell = dcells1[i];
    cell = cell + calc_d(cell.x, cell.y, cell.z, dcell.x, dcell.y, dcell.z);
    cell.x = cell.x % 360;
    if (cell.x < 0) cell.x += 360;
    if (cell.z > Tk) cell.z = Tk;

    dcell = dcells2[i];
    cell = cell + calc_d(cell.x, cell.y, cell.z, dcell.x, dcell.y, dcell.z);
    cell.x = cell.x % 360;
    if (cell.x < 0) cell.x += 360;
    if (cell.z > Tk) cell.z = Tk;

    dcell = dcells3[i];
    cell = cell + calc_d(cell.x, cell.y, cell.z, dcell.x, dcell.y, dcell.z);
    cell.x = cell.x % 360;
    if (cell.x < 0) cell.x += 360;
    if (cell.z > Tk) cell.z = Tk;

    dcell = dcells4[i];
    cell = cell + calc_d(cell.x, cell.y, cell.z, dcell.x, dcell.y, dcell.z);
    cell.x = cell.x % 360;
    if (cell.x < 0) cell.x += 360;
    if (cell.z > Tk) cell.z = Tk;

    dcell = dcells5[i];
    cell = cell + calc_d(cell.x, cell.y, cell.z, dcell.x, dcell.y, dcell.z);
    cell.x = cell.x % 360;
    if (cell.x < 0) cell.x += 360;
    if (cell.z > Tk) cell.z = Tk;

    dcell = dcells6[i];
    cell = cell + calc_d(cell.x, cell.y, cell.z, dcell.x, dcell.y, dcell.z);
    cell.x = cell.x % 360;
    if (cell.x < 0) cell.x += 360;
    if (cell.z > Tk) cell.z = Tk;

    dcell = dcells7[i];
    cell = cell + calc_d(cell.x, cell.y, cell.z, dcell.x, dcell.y, dcell.z);
    cell.x = cell.x % 360;
    if (cell.x < 0) cell.x += 360;
    if (cell.z > Tk) cell.z = Tk;

    cells[i] = cell;
    img[i] = hsv2rgb(cell);

""", "ca_calc", preamble="""
#include <math.h>
#define Mk %s
#define Tk %s

__device__ int3 operator+(const int3 &a, const int3 &b) {
    return make_int3(a.x+b.x, a.y+b.y, a.z+b.z);
}

__device__ int3 calc_d(int Fc, int Mc, int Tc, int Fi, int Mi, int Ti) {
    int dF = Fi - Fc;
    if (dF > 180) Fc += 360;
    if (dF < -180) Fc -= 360;
    float sM = Mi + Mc;
    if (sM != 0) sM = Mi / sM; else sM = 0;
    dF = (int) (Fi - Fc) * sM;
    int dM = Mi;
    int dT = fabs((float) (Fi - Fc)) * fmin((float) Mc, (float) Mi) / Mk + (Ti - Tc) * sM;
    return make_int3(dF, dM, dT);
}

__device__ uint hsv2rgb(int3 pixel) {
    // skipped for brevity
}
""" % (Mk, Tk, RAM))

第二个和当前的解决方案：

Mk = 64
Tk = 1000
CELL_LEN = 120 # number of parameters per cell

emit_gpu = ElementwiseKernel("int *cells, int w, int h", """
    int x = i / h;
    int y = i % h;
    int ii = i * CN;

    int Fc = cells[ii];
    int Mc = cells[ii+1];
    int Tc = cells[ii+2];
    float M = (float) Mc;
    float T = (float) Tc;
    int Mi = (int) (fmin(1, T / Tk) * M);
    cells[ii+1] = Mc - Mi;
    cells[ii+2] = Tc - (int) (T * fmin(1, T / Tk));

    int Mbase = Mi / 8;
    int Mpart = Mi % 8;
    int Madd;
    int iii, xo, yo;

    for (int cc = 0; cc < 9; cc++) {
      int c = (cc + Fc) % 9;
      if (c == 4) continue;
      xo = x + c%3 - 1;
      if (xo < 0) xo = w + xo; else if (xo >= w) xo = xo - w;
      yo = y + c/3 - 1;
      if (yo < 0) yo = h + yo; else if (xo >= w) yo = yo - h;
      if (Mpart > 0) { Madd = 1; Mpart--;} else Madd = 0;
      if (c > 4) c--;
      iii = (xo * h + yo) * CN + 6 + c*3;

      cells[iii] = Fc;
      cells[iii+1] = Mbase + Madd;
      cells[iii+2] = Tc;

    } 
""", "ca_emit", preamble="""
#define Tk %s
#define CN %s
""" % (Tk, CELL_LEN))

absorb_gpu = ElementwiseKernel("int *cells, int *img, int w, int h", """
    int ii = i * CN;
    int Fc = cells[ii];
    int Mc = cells[ii+1];
    int Tc = cells[ii+2];

    for (int c=0; c < 8; c++){
      int iii = ii + c * 3 + 6;
      int Fi = cells[iii];
      int Mi = cells[iii+1];
      int Ti = cells[iii+2];

      int dF = Fi - Fc;
      if (dF > 180) Fc += 360;
      if (dF < -180) Fc -= 360;
      float sM = Mi + Mc;
      if (sM != 0) sM = Mi / sM; else sM = 0;
      dF = (int) (Fi - Fc) * sM;
      int dM = Mi;
      int dT = fabs((float) (Fi - Fc)) * fmin((float) Mc, (float) Mi) / Mk + (Ti - Tc) * sM;
      Fc += dF;
      Mc += dM;
      Tc += dT;
      Fc = Fc % 360;
      if (Fc < 0) Fc += 360;
      if (Tc > Tk) Tc = Tk;
    }      

    cells[ii] = Fc;
    cells[ii+1] = Mc;
    cells[ii+2] = Tc;
    cells[ii+18] = (cells[ii+18] + 1) % 8;

    img[i] = hsv2rgb(Fc, Tc, Mc);

""", "ca_absorb", preamble="""
#include <math.h>
#define Mk %s
#define Tk %s
#define CN %s

__device__ uint hsv2rgb(int hue, int sat, int val) {
    // skipped for brevity
}
""" % (Mk, Tk, CELL_LEN))

两种变体都产生完全相同的CA行为,但后者的运行速度要慢得多.

GTX泰坦：

>字段大小：1900×1080个单元格
>解决方案#1：~200步/秒
>解决方案#2：~20步/秒

GT 630M：

>字段大小：1600×900个单元格
>解决方案#1：~7.8步/秒
>解决方案#2：~1.5步/秒

如果您需要,请随意使用这两种解决方案：

Solution #1 full source

Solution #2 full source

欢迎提供任何线索或建议：

>为什么性能会降低？
>是否有可能将解决方案#2的性能至少提升到#1的水平？
>或者另一种解决方案会更好？

解决方法:

好的,我设法如何运行第二个解决方案快了近15倍.进行了以下更改：

>将主参数数组从int转换为int4.这使得它比使用int3的解决方案更快.虽然,额外的空间未使用(.w维度). [3倍加速]
>在WIDTHxHEIGHT组中重新包装相关参数.因此,形状从(WIDTH,HEIGHT,N)变为(N,WIDTH,HEIGHT).这使得内存访问更有效,因为组内的元素往往被一起处理. [5倍加速]

优化的代码如下所示：

Mk = 64
Tk = 1000

emit_gpu = ElementwiseKernel("int4 *cells, int w, int h, int cn", """
    int x = i / h;
    int y = i % h;

    int4 cell = cells[i];
    int Fc = cell.x;
    int Mc = cell.y;
    int Tc = cell.z;
    float M = (float) Mc;
    float T = (float) Tc;
    int Mi = (int) (fmin(1, T / Tk) * M);
    cells[i] = make_int4(Fc, Mc - Mi, Tc - (int) (T * fmin(1, T / Tk)), 0);

    int Mbase = Mi / 8;
    int Mpart = Mi % 8;
    int Madd;
    int ii;
    int xo, yo;

    int cnn = 0;
    for (int dx = -1; dx < 2; dx++) {
      xo = x + dx;
      if (xo < 0) xo = w + xo; else if (xo >= w) xo = xo - w;
      for (int dy = -1; dy < 2; dy++) {
        if (dx == 0 && dy == 0) continue;
        cnn += cn;
        yo = y + dy;
        if (yo < 0) yo = h + yo; else if (yo >= h) yo = yo - h;
        if (Mpart > 0) { Madd = 1; Mpart--;} else Madd = 0;
        ii = (xo * h + yo) + cnn;
        cells[ii] = make_int4(Fc, Mbase + Madd, Tc, 0);
      }
    } 
""", "ca_emit", preamble="""
#define Tk %s
#define CN %s
""" % (Tk, CELL_LEN))

absorb_gpu = ElementwiseKernel("int4 *cells, int *img, int w, int h, int cn", """
    int ii = i;
    int4 cell = cells[i];
    int Fc = cell.x;
    int Mc = cell.y;
    int Tc = cell.z;

    for (int c=0; c < 8; c++){
      ii += cn;
      cell = cells[ii];
      int Fi = cell.x;
      int Mi = cell.y;
      int Ti = cell.z;

      int dF = Fi - Fc;
      if (dF > 180) Fc += 360;
      if (dF < -180) Fc -= 360;
      float sM = Mi + Mc;
      if (sM != 0) sM = Mi / sM; else sM = 0;
      dF = (int) (Fi - Fc) * sM;
      int dM = Mi;
      int dT = fabs((float) (Fi - Fc)) * fmin((float) Mc, (float) Mi) / Mk + (Ti - Tc) * sM;
      Fc += dF;
      Mc += dM;
      Tc += dT;
      Fc = Fc % 360;
      if (Fc < 0) Fc += 360;
      if (Tc > Tk) Tc = Tk;
    }      

    cells[i] = make_int4(Fc, Mc, Tc, 0);
    img[i] = hsv2rgb(Fc, Tc, Mc);

""", "ca_absorb", preamble="""
#include <math.h>
#define Mk %s
#define Tk %s

__device__ uint hsv2rgb(int hue, int sat, int val) {
    // skipped for brevity
}
""" % (Mk, Tk))

感谢Park Young-Bae提供重新包装的线索以及Alexey Shchepin的一些优化问题.

标签：python,optimization,c-3,cuda,pycuda
来源： https://codeday.me/bug/20190628/1319214.html