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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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NBody Demonstrator implemented in OpenCL, rendering OpenGL
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CC BY-NC-SA 2011 : Emmanuel QUEMENER <emmanuel.quemener@gmail.com>
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Cecill v2 : Emmanuel QUEMENER <emmanuel.quemener@gmail.com>
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Thanks to Andreas Klockner for PyOpenCL:
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http://mathema.tician.de/software/pyopencl
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"""
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import getopt |
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import sys |
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import time |
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import numpy as np |
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import pyopencl as cl |
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import pyopencl.array as cl_array |
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from numpy.random import randint as nprnd |
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import string, sys |
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from OpenGL.GL import * |
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from OpenGL.GLUT import * |
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def DictionariesAPI(): |
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Marsaglia={'CONG':0,'SHR3':1,'MWC':2,'KISS':3} |
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Computing={'FP32':0,'FP64':1} |
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Interaction={'Force':0,'Potential':1} |
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Artevasion={'None':0,'NegExp':1,'CorRad':2} |
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return(Marsaglia,Computing,Interaction,Artevasion)
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BlobOpenCL= """
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#define TFP32 0
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#define TFP64 1
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#define TFORCE 0
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#define TPOTENTIAL 1
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#define NONE 0
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#define NEGEXP 1
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#define CORRAD 2
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#if TYPE == TFP32
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#define MYFLOAT4 float4
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#define MYFLOAT8 float8
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#define MYFLOAT float
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#define DISTANCE fast_distance
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#else
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#define MYFLOAT4 double4
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#define MYFLOAT8 double8
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#define MYFLOAT double
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#define DISTANCE distance
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#if defined(cl_khr_fp64) // Khronos extension available?
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#pragma OPENCL EXTENSION cl_khr_fp64 : enable
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#endif
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#endif
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#define znew ((zmwc=36969*(zmwc&65535)+(zmwc>>16))<<16)
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#define wnew ((wmwc=18000*(wmwc&65535)+(wmwc>>16))&65535)
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#define MWC (znew+wnew)
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#define SHR3 (jsr=(jsr=(jsr=jsr^(jsr<<17))^(jsr>>13))^(jsr<<5))
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#define CONG (jcong=69069*jcong+1234567)
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#define KISS ((MWC^CONG)+SHR3)
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#define MWCfp (MYFLOAT)(MWC * 2.3283064365386963e-10f)
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#define KISSfp (MYFLOAT)(KISS * 2.3283064365386963e-10f)
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#define SHR3fp (MYFLOAT)(SHR3 * 2.3283064365386963e-10f)
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#define CONGfp (MYFLOAT)(CONG * 2.3283064365386963e-10f)
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#define PI (MYFLOAT)3.141592653589793238e0f
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#define SMALL_NUM (MYFLOAT)1.e-9f
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#define CoreRadius (MYFLOAT)(1.e0f)
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// Create my own Distance implementation: distance buggy on Oland AMD chipset
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MYFLOAT MyDistance(MYFLOAT4 n,MYFLOAT4 m)
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{
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private MYFLOAT x2,y2,z2;
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x2=n.s0-m.s0;
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x2*=x2;
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y2=n.s1-m.s1;
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y2*=y2;
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z2=n.s2-m.s2;
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z2*=z2;
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return(sqrt(x2+y2+z2));
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}
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// Potential between 2 m,n bodies
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MYFLOAT PairPotential(MYFLOAT4 m,MYFLOAT4 n)
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#if ARTEVASION == NEGEXP
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// Add exp(-r) to numerator to avoid divergence for low distances
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{
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MYFLOAT r=DISTANCE(n,m);
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return((-1.e0f+exp(-r))/r);
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}
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#elif ARTEVASION == CORRAD
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// Add Core Radius to avoid divergence for low distances
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{
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MYFLOAT r=DISTANCE(n,m);
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return(-1.e0f/sqrt(r*r+CoreRadius*CoreRadius));
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}
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#else
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// Classical potential in 1/r
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{
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// return((MYFLOAT)(-1.e0f)/(MyDistance(m,n)));
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return((MYFLOAT)(-1.e0f)/(DISTANCE(n,m)));
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}
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#endif
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// Interaction based of Force as gradient of Potential
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MYFLOAT4 Interaction(MYFLOAT4 m,MYFLOAT4 n)
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#if INTERACTION == TFORCE
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#if ARTEVASION == NEGEXP
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// Force gradient of potential, set as (1-exp(-r))/r
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{
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private MYFLOAT r=MyDistance(n,m);
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private MYFLOAT num=1.e0f+exp(-r)*(r-1.e0f);
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return((n-m)*num/(MYFLOAT)(r*r*r));
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}
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#elif ARTEVASION == CORRAD
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// Force gradient of potential, (Core Radius) set as 1/sqrt(r**2+CoreRadius**2)
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{
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private MYFLOAT r=MyDistance(n,m);
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private MYFLOAT den=sqrt(r*r+CoreRadius*CoreRadius);
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return((n-m)/(MYFLOAT)(den*den*den));
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}
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#else
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// Simplest implementation of force (equals to acceleration)
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// seems to bo bad (numerous artevasions)
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// MYFLOAT4 InteractionForce(MYFLOAT4 m,MYFLOAT4 n)
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{
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private MYFLOAT r=MyDistance(n,m);
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return((n-m)/(MYFLOAT)(r*r*r));
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}
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#endif
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#else
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// Force definited as gradient of potential
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// Estimate potential and proximate potential to estimate force
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{
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// 1/1024 seems to be a good factor: larger one provides bad results
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private MYFLOAT epsilon=(MYFLOAT)(1.e0f/1024);
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private MYFLOAT4 er=normalize(n-m);
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private MYFLOAT4 dr=er*(MYFLOAT)epsilon;
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return(er/epsilon*(PairPotential(m,n)-PairPotential(m+dr,n)));
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}
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#endif
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MYFLOAT AtomicPotential(__global MYFLOAT4* clDataX,int gid)
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{
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private MYFLOAT potential=(MYFLOAT)0.e0f;
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private MYFLOAT4 x=clDataX[gid];
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for (int i=0;i<get_global_size(0);i++)
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{
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if (gid != i)
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potential+=PairPotential(x,clDataX[i]);
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}
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barrier(CLK_GLOBAL_MEM_FENCE);
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return(potential);
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}
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MYFLOAT AtomicPotentialCoM(__global MYFLOAT4* clDataX,__global MYFLOAT4* clCoM,int gid)
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{
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return(PairPotential(clDataX[gid],clCoM[0]));
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}
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// Elements from : http://doswa.com/2009/01/02/fourth-order-runge-kutta-numerical-integration.html
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MYFLOAT8 AtomicRungeKutta(__global MYFLOAT4* clDataInX,__global MYFLOAT4* clDataInV,int gid,MYFLOAT dt)
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{
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private MYFLOAT4 a0,v0,x0,a1,v1,x1,a2,v2,x2,a3,v3,x3,a4,v4,x4,xf,vf;
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MYFLOAT4 DT=dt*(MYFLOAT4)(1.e0f,1.e0f,1.e0f,1.e0f);
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a0=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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v0=(MYFLOAT4)clDataInV[gid];
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x0=(MYFLOAT4)clDataInX[gid];
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int N = get_global_size(0);
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for (private int i=0;i<N;i++)
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{
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if (gid != i)
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a0+=Interaction(x0,clDataInX[i]);
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}
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a1=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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v1=a0*dt+v0;
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x1=v0*dt+x0;
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for (private int j=0;j<N;j++)
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{
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if (gid != j)
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a1+=Interaction(x1,clDataInX[j]);
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}
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a2=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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v2=a1*(MYFLOAT)(dt/2.e0f)+v0;
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x2=v1*(MYFLOAT)(dt/2.e0f)+x0;
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for (private int k=0;k<N;k++)
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{
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if (gid != k)
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a2+=Interaction(x2,clDataInX[k]);
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}
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a3=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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v3=a2*(MYFLOAT)(dt/2.e0f)+v0;
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x3=v2*(MYFLOAT)(dt/2.e0f)+x0;
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for (private int l=0;l<N;l++)
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{
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if (gid != l)
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a3+=Interaction(x3,clDataInX[l]);
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}
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a4=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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v4=a3*dt+v0;
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x4=v3*dt+x0;
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for (private int m=0;m<N;m++)
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{
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if (gid != m)
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a4+=Interaction(x4,clDataInX[m]);
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}
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xf=x0+dt*(v1+(MYFLOAT)2.e0f*(v2+v3)+v4)/(MYFLOAT)6.e0f;
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vf=v0+dt*(a1+(MYFLOAT)2.e0f*(a2+a3)+a4)/(MYFLOAT)6.e0f;
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return((MYFLOAT8)(xf.s0,xf.s1,xf.s2,0.e0f,vf.s0,vf.s1,vf.s2,0.e0f));
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}
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MYFLOAT8 AtomicHeun(__global MYFLOAT4* clDataInX,__global MYFLOAT4* clDataInV,int gid,MYFLOAT dt)
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{
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private MYFLOAT4 x0,v0,a0,x1,v1,a1,xf,vf;
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MYFLOAT4 Dt=dt*(MYFLOAT4)(1.e0f,1.e0f,1.e0f,1.e0f);
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x0=(MYFLOAT4)clDataInX[gid];
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v0=(MYFLOAT4)clDataInV[gid];
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a0=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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for (private int i=0;i<get_global_size(0);i++)
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{
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if (gid != i)
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a0+=Interaction(x0,clDataInX[i]);
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}
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a1=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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//v1=v0+dt*a0;
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//x1=x0+dt*v0;
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v1=dt*a0+v0;
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x1=dt*v0+x0;
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for (private int j=0;j<get_global_size(0);j++)
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{
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if (gid != j)
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a1+=Interaction(x1,clDataInX[j]);
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}
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vf=v0+dt*(a0+a1)/(MYFLOAT)2.e0f;
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xf=x0+dt*(v0+v1)/(MYFLOAT)2.e0f;
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return((MYFLOAT8)(xf.s0,xf.s1,xf.s2,0.e0f,vf.s0,vf.s1,vf.s2,0.e0f));
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}
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MYFLOAT8 AtomicImplicitEuler(__global MYFLOAT4* clDataInX,__global MYFLOAT4* clDataInV,int gid,MYFLOAT dt)
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{
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MYFLOAT4 x0,v0,a,xf,vf;
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x0=(MYFLOAT4)clDataInX[gid];
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v0=(MYFLOAT4)clDataInV[gid];
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a=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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for (private int i=0;i<get_global_size(0);i++)
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{
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if (gid != i)
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a+=Interaction(x0,clDataInX[i]);
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}
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vf=v0+dt*a;
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xf=x0+dt*vf;
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return((MYFLOAT8)(xf.s0,xf.s1,xf.s2,0.e0f,vf.s0,vf.s1,vf.s2,0.e0f));
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}
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MYFLOAT8 AtomicExplicitEuler(__global MYFLOAT4* clDataInX,__global MYFLOAT4* clDataInV,int gid,MYFLOAT dt)
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{
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MYFLOAT4 x0,v0,a,xf,vf;
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x0=(MYFLOAT4)clDataInX[gid];
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v0=(MYFLOAT4)clDataInV[gid];
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a=(MYFLOAT4)(0.e0f,0.e0f,0.e0f,0.e0f);
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for (private int i=0;i<get_global_size(0);i++)
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{
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if (gid != i)
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a+=Interaction(x0,clDataInX[i]);
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}
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vf=v0+dt*a;
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xf=x0+dt*v0;
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return((MYFLOAT8)(xf.s0,xf.s1,xf.s2,0.e0f,vf.s0,vf.s1,vf.s2,0.e0f));
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}
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__kernel void InBallSplutterPoints(__global MYFLOAT4* clDataX,
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MYFLOAT diameter,uint seed_z,uint seed_w)
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{
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private int gid=get_global_id(0);
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private uint zmwc=seed_z+gid;
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private uint wmwc=seed_w+(gid+1)%2;
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private MYFLOAT Heat;
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for (int i=0;i<gid;i++)
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{
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Heat=MWCfp;
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}
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// More accurate distribution based on spherical coordonates
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// Disactivated because of AMD Oland GPU crash on launch
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// private MYFLOAT Radius,Theta,Phi,PosX,PosY,PosZ,SinTheta;
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// Radius=MWCfp*diameter/2.e0f;
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// Theta=(MYFLOAT)acos((float)(-2.e0f*MWCfp+1.0e0f));
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// Phi=(MYFLOAT)(2.e0f*PI*MWCfp);
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// SinTheta=sin((float)Theta);
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// PosX=cos((float)Phi)*Radius*SinTheta;
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// PosY=sin((float)Phi)*Radius*SinTheta;
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// PosZ=cos((float)Theta)*Radius;
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// clDataX[gid]=(MYFLOAT4)(PosX,PosY,PosZ,0.e0f);
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private MYFLOAT Radius=diameter/2.e0f;
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private MYFLOAT Length=diameter;
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private MYFLOAT4 Position;
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while (Length>Radius) {
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Position=(MYFLOAT4)((MWCfp-0.5e0f)*diameter,(MWCfp-0.5e0f)*diameter,(MWCfp-0.5e0f)*diameter,0.e0f);
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Length=(MYFLOAT)length((MYFLOAT4)Position);
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}
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clDataX[gid]=Position;
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barrier(CLK_GLOBAL_MEM_FENCE);
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}
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__kernel void InBoxSplutterPoints(__global MYFLOAT4* clDataX, MYFLOAT box,
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uint seed_z,uint seed_w)
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{
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int gid=get_global_id(0);
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uint zmwc=seed_z+gid;
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uint wmwc=seed_w-gid;
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private MYFLOAT Heat;
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for (int i=0;i<gid;i++)
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{
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Heat=MWCfp;
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}
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clDataX[gid]=(MYFLOAT4)((MWCfp-0.5e0f)*box,(MWCfp-0.5e0f)*box,(MWCfp-0.5e0f)*box,0.e0f);
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barrier(CLK_GLOBAL_MEM_FENCE);
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}
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__kernel void SplutterStress(__global MYFLOAT4* clDataX,__global MYFLOAT4* clDataV,__global MYFLOAT4* clCoM, MYFLOAT velocity,uint seed_z,uint seed_w)
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{
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int gid = get_global_id(0);
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MYFLOAT N = (MYFLOAT)get_global_size(0);
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uint zmwc=seed_z+(uint)gid;
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uint wmwc=seed_w-(uint)gid;
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MYFLOAT4 CrossVector,SpeedVector,FromCoM;
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MYFLOAT Heat,ThetaA,PhiA,ThetaB,PhiB,Length,tA,tB,Polar;
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for (int i=0;i<gid;i++)
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{
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Heat=MWCfp;
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}
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// cast to float for sin,cos are NEEDED by Mesa FP64 implementation!
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// Implemention on AMD Oland are probably broken in float
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FromCoM=(MYFLOAT4)(clDataX[gid]-clCoM[0]);
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Length=length(FromCoM);
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//Theta=acos(FromCoM.z/Length);
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//Phi=atan(FromCoM.y/FromCoM.x);
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// First tangential vector to sphere of length radius
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ThetaA=acos(FromCoM.x/Length)+5.e-1f*PI;
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PhiA=atan(FromCoM.y/FromCoM.z);
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// Second tangential vector to sphere of length radius
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ThetaB=acos((float)(FromCoM.x/Length));
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PhiB=atan((float)(FromCoM.y/FromCoM.z))+5.e-1f*PI;
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// (x,y) random coordonates to plane tangential to sphere
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Polar=MWCfp*2.e0f*PI;
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tA=cos((float)Polar);
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tB=sin((float)Polar);
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// Exception for 2 particules to ovoid shifting
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if (get_global_size(0)==2) {
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CrossVector=(MYFLOAT4)(1.e0f,1.e0f,1.e0f,0.e0f);
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} else {
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CrossVector.s0=tA*cos((float)ThetaA)+tB*cos((float)ThetaB);
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CrossVector.s1=tA*sin((float)ThetaA)*sin((float)PhiA)+tB*sin((float)ThetaB)*sin((float)PhiB);
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CrossVector.s2=tA*sin((float)ThetaA)*cos((float)PhiA)+tB*sin((float)ThetaB)*cos((float)PhiB);
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CrossVector.s3=0.e0f;
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}
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if (velocity<SMALL_NUM) {
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SpeedVector=(MYFLOAT4)normalize(cross(FromCoM,CrossVector))*sqrt((-AtomicPotential(clDataX,gid)/(MYFLOAT)2.e0f));
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}
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else
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{
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SpeedVector=(MYFLOAT4)((MWCfp-5e-1f)*velocity,(MWCfp-5e-1f)*velocity,
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(MWCfp-5e-1f)*velocity,0.e0f);
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}
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clDataV[gid]=SpeedVector;
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barrier(CLK_GLOBAL_MEM_FENCE);
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}
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__kernel void RungeKutta(__global MYFLOAT4* clDataX,__global MYFLOAT4* clDataV,MYFLOAT h)
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{
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private int gid = get_global_id(0);
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private MYFLOAT8 clDataGid;
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419 |
clDataGid=AtomicRungeKutta(clDataX,clDataV,gid,h);
|
420 |
barrier(CLK_GLOBAL_MEM_FENCE);
|
421 |
clDataX[gid]=clDataGid.s0123;
|
422 |
clDataV[gid]=clDataGid.s4567;
|
423 |
}
|
424 |
|
425 |
__kernel void Heun(__global MYFLOAT4* clDataX,__global MYFLOAT4* clDataV,MYFLOAT h)
|
426 |
{
|
427 |
private int gid = get_global_id(0);
|
428 |
private MYFLOAT8 clDataGid;
|
429 |
|
430 |
clDataGid=AtomicHeun(clDataX,clDataV,gid,h);
|
431 |
barrier(CLK_GLOBAL_MEM_FENCE);
|
432 |
clDataX[gid]=clDataGid.s0123;
|
433 |
clDataV[gid]=clDataGid.s4567;
|
434 |
}
|
435 |
|
436 |
__kernel void ImplicitEuler(__global MYFLOAT4* clDataX,__global MYFLOAT4* clDataV,MYFLOAT h)
|
437 |
{
|
438 |
private int gid = get_global_id(0);
|
439 |
private MYFLOAT8 clDataGid;
|
440 |
|
441 |
clDataGid=AtomicImplicitEuler(clDataX,clDataV,gid,h);
|
442 |
barrier(CLK_GLOBAL_MEM_FENCE);
|
443 |
clDataX[gid]=clDataGid.s0123;
|
444 |
clDataV[gid]=clDataGid.s4567;
|
445 |
}
|
446 |
|
447 |
__kernel void ExplicitEuler(__global MYFLOAT4* clDataX,__global MYFLOAT4* clDataV,MYFLOAT h)
|
448 |
{
|
449 |
private int gid = get_global_id(0);
|
450 |
private MYFLOAT8 clDataGid;
|
451 |
|
452 |
clDataGid=AtomicExplicitEuler(clDataX,clDataV,gid,h);
|
453 |
barrier(CLK_GLOBAL_MEM_FENCE);
|
454 |
clDataX[gid]=clDataGid.s0123;
|
455 |
clDataV[gid]=clDataGid.s4567;
|
456 |
}
|
457 |
|
458 |
__kernel void CoMPotential(__global MYFLOAT4* clDataX,__global MYFLOAT4* clCoM,__global MYFLOAT* clPotential)
|
459 |
{
|
460 |
int gid = get_global_id(0);
|
461 |
|
462 |
clPotential[gid]=PairPotential(clDataX[gid],clCoM[0]);
|
463 |
}
|
464 |
|
465 |
__kernel void Potential(__global MYFLOAT4* clDataX,__global MYFLOAT* clPotential)
|
466 |
{
|
467 |
int gid = get_global_id(0);
|
468 |
|
469 |
MYFLOAT potential=(MYFLOAT)0.e0f;
|
470 |
MYFLOAT4 x=clDataX[gid];
|
471 |
|
472 |
for (int i=0;i<get_global_size(0);i++)
|
473 |
{
|
474 |
if (gid != i)
|
475 |
potential+=PairPotential(x,clDataX[i]);
|
476 |
}
|
477 |
|
478 |
barrier(CLK_GLOBAL_MEM_FENCE);
|
479 |
clPotential[gid]=potential*(MYFLOAT)5.e-1f;
|
480 |
}
|
481 |
|
482 |
__kernel void CenterOfMass(__global MYFLOAT4* clDataX,__global MYFLOAT4* clCoM,int Size)
|
483 |
{
|
484 |
MYFLOAT4 CoM=clDataX[0];
|
485 |
|
486 |
for (int i=1;i<Size;i++)
|
487 |
{
|
488 |
CoM+=clDataX[i];
|
489 |
}
|
490 |
|
491 |
barrier(CLK_GLOBAL_MEM_FENCE);
|
492 |
clCoM[0]=(MYFLOAT4)(CoM.s0,CoM.s1,CoM.s2,0.e0f)/(MYFLOAT)Size;
|
493 |
}
|
494 |
|
495 |
__kernel void Kinetic(__global MYFLOAT4* clDataV,__global MYFLOAT* clKinetic)
|
496 |
{
|
497 |
int gid = get_global_id(0);
|
498 |
|
499 |
barrier(CLK_GLOBAL_MEM_FENCE);
|
500 |
MYFLOAT d=(MYFLOAT)length(clDataV[gid]);
|
501 |
clKinetic[gid]=(MYFLOAT)5.e-1f*(MYFLOAT)(d*d);
|
502 |
}
|
503 |
|
504 |
"""
|
505 |
|
506 |
def MainOpenCL(clDataX,clDataV,Step,Method): |
507 |
time_start=time.time() |
508 |
if Method=="RungeKutta": |
509 |
CLLaunch=MyRoutines.RungeKutta(queue,(Number,1),None,clDataX,clDataV,Step) |
510 |
elif Method=="ExplicitEuler": |
511 |
CLLaunch=MyRoutines.ExplicitEuler(queue,(Number,1),None,clDataX,clDataV,Step) |
512 |
elif Method=="Heun": |
513 |
CLLaunch=MyRoutines.Heun(queue,(Number,1),None,clDataX,clDataV,Step) |
514 |
else:
|
515 |
CLLaunch=MyRoutines.ImplicitEuler(queue,(Number,1),None,clDataX,clDataV,Step) |
516 |
CLLaunch.wait() |
517 |
Elapsed=time.time()-time_start |
518 |
return(Elapsed)
|
519 |
|
520 |
def display(*args): |
521 |
|
522 |
global MyDataX,MyDataV,clDataX,clDataV,Step,Method,Number,Iterations,Durations,Verbose,SpeedRendering
|
523 |
|
524 |
glClearColor(0.0, 0.0, 0.0, 0.0) |
525 |
glClear(GL_COLOR_BUFFER_BIT) |
526 |
glColor3f(1.0,1.0,1.0) |
527 |
|
528 |
Elapsed=MainOpenCL(clDataX,clDataV,Step,Method) |
529 |
if SpeedRendering:
|
530 |
cl.enqueue_copy(queue, MyDataV, clDataV) |
531 |
MyDataV.reshape(Number,4)[:,3]=1 |
532 |
glVertexPointerf(MyDataV.reshape(Number,4))
|
533 |
else:
|
534 |
cl.enqueue_copy(queue, MyDataX, clDataX) |
535 |
MyDataX.reshape(Number,4)[:,3]=1 |
536 |
glVertexPointerf(MyDataX.reshape(Number,4))
|
537 |
|
538 |
if Verbose:
|
539 |
print("Positions for #%s iteration: %s" % (Iterations,MyDataX))
|
540 |
else:
|
541 |
sys.stdout.write('.')
|
542 |
sys.stdout.flush() |
543 |
Durations=np.append(Durations,MainOpenCL(clDataX,clDataV,Step,Method)) |
544 |
glEnableClientState(GL_VERTEX_ARRAY) |
545 |
glDrawArrays(GL_POINTS, 0, Number)
|
546 |
glDisableClientState(GL_VERTEX_ARRAY) |
547 |
glFlush() |
548 |
Iterations+=1
|
549 |
glutSwapBuffers() |
550 |
|
551 |
def halt(): |
552 |
pass
|
553 |
|
554 |
def keyboard(k,x,y): |
555 |
global ViewRZ,SpeedRendering
|
556 |
LC_Z = as_8_bit( 'z' )
|
557 |
UC_Z = as_8_bit( 'Z' )
|
558 |
Plus = as_8_bit( '+' )
|
559 |
Minus = as_8_bit( '-' )
|
560 |
Switch = as_8_bit( 's' )
|
561 |
|
562 |
Zoom=1
|
563 |
if k == LC_Z:
|
564 |
ViewRZ += 1.0
|
565 |
elif k == UC_Z:
|
566 |
ViewRZ -= 1.0
|
567 |
elif k == Plus:
|
568 |
Zoom *= 2.0
|
569 |
elif k == Minus:
|
570 |
Zoom /= 2.0
|
571 |
elif k == Switch:
|
572 |
if SpeedRendering:
|
573 |
SpeedRendering=False
|
574 |
else:
|
575 |
SpeedRendering=True
|
576 |
elif ord(k) == 27: # Escape |
577 |
glutLeaveMainLoop() |
578 |
return(False) |
579 |
else:
|
580 |
return
|
581 |
glRotatef(ViewRZ, 0.0, 0.0, 1.0) |
582 |
glScalef(Zoom,Zoom,Zoom) |
583 |
glutPostRedisplay() |
584 |
|
585 |
def special(k,x,y): |
586 |
global ViewRX, ViewRY
|
587 |
|
588 |
Step=1.
|
589 |
if k == GLUT_KEY_UP:
|
590 |
ViewRX += Step |
591 |
elif k == GLUT_KEY_DOWN:
|
592 |
ViewRX -= Step |
593 |
elif k == GLUT_KEY_LEFT:
|
594 |
ViewRY += Step |
595 |
elif k == GLUT_KEY_RIGHT:
|
596 |
ViewRY -= Step |
597 |
else:
|
598 |
return
|
599 |
glRotatef(ViewRX, 1.0, 0.0, 0.0) |
600 |
glRotatef(ViewRY, 0.0, 1.0, 0.0) |
601 |
glutPostRedisplay() |
602 |
|
603 |
def setup_viewport(): |
604 |
global SizeOfBox
|
605 |
glMatrixMode(GL_PROJECTION) |
606 |
glLoadIdentity() |
607 |
glOrtho(-SizeOfBox, SizeOfBox, -SizeOfBox, SizeOfBox, -SizeOfBox, SizeOfBox) |
608 |
glutPostRedisplay() |
609 |
|
610 |
def reshape(w, h): |
611 |
glViewport(0, 0, w, h) |
612 |
setup_viewport() |
613 |
|
614 |
if __name__=='__main__': |
615 |
|
616 |
global Number,Step,clDataX,clDataV,MyDataX,MyDataV,Method,SizeOfBox,Iterations,Verbose,Durations
|
617 |
|
618 |
# ValueType
|
619 |
ValueType='FP32'
|
620 |
class MyFloat(np.float32):pass |
621 |
# clType8=cl_array.vec.float8
|
622 |
# Set defaults values
|
623 |
np.set_printoptions(precision=2)
|
624 |
# Id of Device : 1 is for first find !
|
625 |
Device=0
|
626 |
# Number of bodies is integer
|
627 |
Number=2
|
628 |
# Number of iterations (for standalone execution)
|
629 |
Iterations=10
|
630 |
# Size of shape
|
631 |
SizeOfShape=MyFloat(1.)
|
632 |
# Initial velocity of particules
|
633 |
Velocity=MyFloat(1.)
|
634 |
# Step
|
635 |
Step=MyFloat(1./32) |
636 |
# Method of integration
|
637 |
Method='ImplicitEuler'
|
638 |
# InitialRandom
|
639 |
InitialRandom=False
|
640 |
# RNG Marsaglia Method
|
641 |
RNG='MWC'
|
642 |
# Viriel Distribution of stress
|
643 |
VirielStress=True
|
644 |
# Verbose
|
645 |
Verbose=False
|
646 |
# OpenGL real time rendering
|
647 |
OpenGL=False
|
648 |
# Speed rendering
|
649 |
SpeedRendering=False
|
650 |
# Counter ArtEvasions Measures (artefact evasion)
|
651 |
CoArEv='None'
|
652 |
# Shape to distribute
|
653 |
Shape='Ball'
|
654 |
# Type of Interaction
|
655 |
InterType='Force'
|
656 |
|
657 |
HowToUse='%s -h [Help] -r [InitialRandom] -g [OpenGL] -e [VirielStress] -o [Verbose] -p [Potential] -x <None|NegExp|CorRad> -d <DeviceId> -n <NumberOfParticules> -i <Iterations> -z <SizeOfBoxOrBall> -v <Velocity> -s <Step> -b <Ball|Box> -m <ImplicitEuler|RungeKutta|ExplicitEuler|Heun> -t <FP32|FP64>'
|
658 |
|
659 |
try:
|
660 |
opts, args = getopt.getopt(sys.argv[1:],"rpgehod:n:i:z:v:s:m:t:b:x:",["random","potential","coarev","opengl","viriel","verbose","device=","number=","iterations=","size=","velocity=","step=","method=","valuetype=","shape="]) |
661 |
except getopt.GetoptError:
|
662 |
print(HowToUse % sys.argv[0])
|
663 |
sys.exit(2)
|
664 |
|
665 |
for opt, arg in opts: |
666 |
if opt == '-h': |
667 |
print(HowToUse % sys.argv[0])
|
668 |
|
669 |
print("\nInformations about devices detected under OpenCL:")
|
670 |
try:
|
671 |
Id=0
|
672 |
for platform in cl.get_platforms(): |
673 |
for device in platform.get_devices(): |
674 |
# Failed now because of POCL implementation
|
675 |
#deviceType=cl.device_type.to_string(device.type)
|
676 |
deviceType="xPU"
|
677 |
print("Device #%i from %s of type %s : %s" % (Id,platform.vendor.lstrip(),deviceType,device.name.lstrip()))
|
678 |
Id=Id+1
|
679 |
sys.exit() |
680 |
except ImportError: |
681 |
print("Your platform does not seem to support OpenCL")
|
682 |
sys.exit() |
683 |
|
684 |
elif opt in ("-t", "--valuetype"): |
685 |
if arg=='FP64': |
686 |
class MyFloat(np.float64): pass |
687 |
else:
|
688 |
class MyFloat(np.float32):pass |
689 |
ValueType = arg |
690 |
elif opt in ("-d", "--device"): |
691 |
Device=int(arg)
|
692 |
elif opt in ("-m", "--method"): |
693 |
Method=arg |
694 |
elif opt in ("-b", "--shape"): |
695 |
Shape=arg |
696 |
if Shape!='Ball' or Shape!='Box': |
697 |
print('Wrong argument: set to Ball')
|
698 |
elif opt in ("-n", "--number"): |
699 |
Number=int(arg)
|
700 |
elif opt in ("-i", "--iterations"): |
701 |
Iterations=int(arg)
|
702 |
elif opt in ("-z", "--size"): |
703 |
SizeOfShape=MyFloat(arg) |
704 |
elif opt in ("-v", "--velocity"): |
705 |
Velocity=MyFloat(arg) |
706 |
VirielStress=False
|
707 |
elif opt in ("-s", "--step"): |
708 |
Step=MyFloat(arg) |
709 |
elif opt in ("-r", "--random"): |
710 |
InitialRandom=True
|
711 |
elif opt in ("-c", "--check"): |
712 |
CheckEnergies=True
|
713 |
elif opt in ("-e", "--viriel"): |
714 |
VirielStress=True
|
715 |
elif opt in ("-g", "--opengl"): |
716 |
OpenGL=True
|
717 |
elif opt in ("-p", "--potential"): |
718 |
InterType='Potential'
|
719 |
elif opt in ("-x", "--coarev"): |
720 |
CoArEv=arg |
721 |
elif opt in ("-o", "--verbose"): |
722 |
Verbose=True
|
723 |
|
724 |
SizeOfShape=np.sqrt(MyFloat(SizeOfShape*Number)) |
725 |
Velocity=MyFloat(Velocity) |
726 |
Step=MyFloat(Step) |
727 |
|
728 |
print("Device choosed : %s" % Device)
|
729 |
print("Number of particules : %s" % Number)
|
730 |
print("Size of Shape : %s" % SizeOfShape)
|
731 |
print("Initial velocity : %s" % Velocity)
|
732 |
print("Step of iteration : %s" % Step)
|
733 |
print("Number of iterations : %s" % Iterations)
|
734 |
print("Method of resolution : %s" % Method)
|
735 |
print("Initial Random for RNG Seed : %s" % InitialRandom)
|
736 |
print("ValueType is : %s" % ValueType)
|
737 |
print("Viriel distribution of stress : %s" % VirielStress)
|
738 |
print("OpenGL real time rendering : %s" % OpenGL)
|
739 |
print("Speed rendering : %s" % SpeedRendering)
|
740 |
print("Interaction type : %s" % InterType)
|
741 |
print("Counter Artevasion type : %s" % CoArEv)
|
742 |
|
743 |
# Create Numpy array of CL vector with 8 FP32
|
744 |
MyCoM = np.zeros(4,dtype=MyFloat)
|
745 |
MyDataX = np.zeros(Number*4, dtype=MyFloat)
|
746 |
MyDataV = np.zeros(Number*4, dtype=MyFloat)
|
747 |
MyPotential = np.zeros(Number, dtype=MyFloat) |
748 |
MyKinetic = np.zeros(Number, dtype=MyFloat) |
749 |
|
750 |
Marsaglia,Computing,Interaction,Artevasion=DictionariesAPI() |
751 |
|
752 |
# Scan the OpenCL arrays
|
753 |
Id=0
|
754 |
HasXPU=False
|
755 |
for platform in cl.get_platforms(): |
756 |
for device in platform.get_devices(): |
757 |
if Id==Device:
|
758 |
PlatForm=platform |
759 |
XPU=device |
760 |
print("CPU/GPU selected: ",device.name.lstrip())
|
761 |
print("Platform selected: ",platform.name)
|
762 |
HasXPU=True
|
763 |
Id+=1
|
764 |
|
765 |
if HasXPU==False: |
766 |
print("No XPU #%i found in all of %i devices, sorry..." % (Device,Id-1)) |
767 |
sys.exit() |
768 |
|
769 |
# Create Context
|
770 |
try:
|
771 |
ctx = cl.Context([XPU]) |
772 |
queue = cl.CommandQueue(ctx,properties=cl.command_queue_properties.PROFILING_ENABLE) |
773 |
except:
|
774 |
print("Crash during context creation")
|
775 |
|
776 |
# Build all routines used for the computing
|
777 |
|
778 |
#BuildOptions="-cl-mad-enable -cl-kernel-arg-info -cl-fast-relaxed-math -cl-std=CL1.2 -DTRNG=%i -DTYPE=%i" % (Marsaglia[RNG],Computing[ValueType])
|
779 |
BuildOptions="-cl-mad-enable -cl-fast-relaxed-math -DTRNG=%i -DTYPE=%i -DINTERACTION=%i -DARTEVASION=%i" % (Marsaglia[RNG],Computing[ValueType],Interaction[InterType],Artevasion[CoArEv])
|
780 |
|
781 |
if 'Intel' in PlatForm.name or 'Experimental' in PlatForm.name or 'Clover' in PlatForm.name or 'Portable' in PlatForm.name : |
782 |
MyRoutines = cl.Program(ctx, BlobOpenCL).build(options = BuildOptions) |
783 |
else:
|
784 |
MyRoutines = cl.Program(ctx, BlobOpenCL).build(options = BuildOptions+" -cl-strict-aliasing")
|
785 |
|
786 |
mf = cl.mem_flags |
787 |
# Read/Write approach for buffering
|
788 |
clDataX = cl.Buffer(ctx, mf.READ_WRITE, MyDataX.nbytes) |
789 |
clDataV = cl.Buffer(ctx, mf.READ_WRITE, MyDataV.nbytes) |
790 |
clPotential = cl.Buffer(ctx, mf.READ_WRITE, MyPotential.nbytes) |
791 |
clKinetic = cl.Buffer(ctx, mf.READ_WRITE, MyKinetic.nbytes) |
792 |
clCoM = cl.Buffer(ctx, mf.READ_WRITE, MyCoM.nbytes) |
793 |
|
794 |
# Write/HostPointer approach for buffering
|
795 |
# clDataX = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyDataX)
|
796 |
# clDataV = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyDataV)
|
797 |
# clPotential = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyPotential)
|
798 |
# clKinetic = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyKinetic)
|
799 |
# clCoM = cl.Buffer(ctx, mf.WRITE_ONLY|mf.COPY_HOST_PTR,hostbuf=MyCoM)
|
800 |
|
801 |
print('All particles superimposed.')
|
802 |
|
803 |
# Set particles to RNG points
|
804 |
if InitialRandom:
|
805 |
seed_w=np.uint32(nprnd(2**32)) |
806 |
seed_z=np.uint32(nprnd(2**32)) |
807 |
else:
|
808 |
seed_w=np.uint32(19710211)
|
809 |
seed_z=np.uint32(20081010)
|
810 |
|
811 |
if Shape=='Ball': |
812 |
MyRoutines.InBallSplutterPoints(queue,(Number,1),None,clDataX,SizeOfShape,seed_w,seed_z) |
813 |
else:
|
814 |
MyRoutines.InBoxSplutterPoints(queue,(Number,1),None,clDataX,SizeOfShape,seed_w,seed_z) |
815 |
|
816 |
print('All particules distributed')
|
817 |
|
818 |
CLLaunch=MyRoutines.CenterOfMass(queue,(1,1),None,clDataX,clCoM,np.int32(Number)) |
819 |
CLLaunch.wait() |
820 |
cl.enqueue_copy(queue,MyCoM,clCoM) |
821 |
print('Center Of Mass estimated: (%s,%s,%s)' % (MyCoM[0],MyCoM[1],MyCoM[2])) |
822 |
|
823 |
if VirielStress:
|
824 |
CLLaunch=MyRoutines.SplutterStress(queue,(Number,1),None,clDataX,clDataV,clCoM,MyFloat(0.),np.uint32(110271),np.uint32(250173)) |
825 |
else:
|
826 |
CLLaunch=MyRoutines.SplutterStress(queue,(Number,1),None,clDataX,clDataV,clCoM,Velocity,np.uint32(110271),np.uint32(250173)) |
827 |
CLLaunch.wait() |
828 |
|
829 |
print('All particules stressed')
|
830 |
|
831 |
CLLaunch=MyRoutines.Potential(queue,(Number,1),None,clDataX,clPotential) |
832 |
CLLaunch=MyRoutines.Kinetic(queue,(Number,1),None,clDataV,clKinetic) |
833 |
CLLaunch.wait() |
834 |
cl.enqueue_copy(queue,MyPotential,clPotential) |
835 |
cl.enqueue_copy(queue,MyKinetic,clKinetic) |
836 |
print('Energy estimated: Viriel=%s Potential=%s Kinetic=%s\n'% (np.sum(MyPotential)+2*np.sum(MyKinetic),np.sum(MyPotential),np.sum(MyKinetic))) |
837 |
|
838 |
if SpeedRendering:
|
839 |
SizeOfBox=max(2*MyKinetic) |
840 |
else:
|
841 |
SizeOfBox=SizeOfShape |
842 |
|
843 |
if OpenGL:
|
844 |
print('\tTiny documentation to interact OpenGL rendering:\n')
|
845 |
print('\t<Left|Right> Rotate around X axis')
|
846 |
print('\t <Up|Down> Rotate around Y axis')
|
847 |
print('\t <z|Z> Rotate around Z axis')
|
848 |
print('\t <-|+> Unzoom/Zoom')
|
849 |
print('\t <s> Toggle to display Positions or Velocities')
|
850 |
print('\t <Esc> Quit\n')
|
851 |
|
852 |
wall_time_start=time.time() |
853 |
|
854 |
Durations=np.array([],dtype=MyFloat) |
855 |
print('Starting!')
|
856 |
if OpenGL:
|
857 |
global ViewRX,ViewRY,ViewRZ
|
858 |
Iterations=0
|
859 |
ViewRX,ViewRY,ViewRZ = 0.,0.,0. |
860 |
# Launch OpenGL Loop
|
861 |
glutInit(sys.argv) |
862 |
glutInitDisplayMode(GLUT_DOUBLE | GLUT_RGB) |
863 |
glutSetOption(GLUT_ACTION_ON_WINDOW_CLOSE,GLUT_ACTION_CONTINUE_EXECUTION) |
864 |
glutInitWindowSize(512,512) |
865 |
glutCreateWindow(b'NBodyGL')
|
866 |
setup_viewport() |
867 |
glutReshapeFunc(reshape) |
868 |
glutDisplayFunc(display) |
869 |
glutIdleFunc(display) |
870 |
# glutMouseFunc(mouse)
|
871 |
glutSpecialFunc(special) |
872 |
glutKeyboardFunc(keyboard) |
873 |
glutMainLoop() |
874 |
else:
|
875 |
for iteration in range(Iterations): |
876 |
Elapsed=MainOpenCL(clDataX,clDataV,Step,Method) |
877 |
if Verbose:
|
878 |
# print("Duration of #%s iteration: %s" % (iteration,Elapsed))
|
879 |
cl.enqueue_copy(queue, MyDataX, clDataX) |
880 |
print("Positions for #%s iteration: %s" % (iteration,MyDataX))
|
881 |
else:
|
882 |
sys.stdout.write('.')
|
883 |
sys.stdout.flush() |
884 |
Durations=np.append(Durations,Elapsed) |
885 |
|
886 |
print('\nEnding!')
|
887 |
|
888 |
MyRoutines.CenterOfMass(queue,(1,1),None,clDataX,clCoM,np.int32(Number)) |
889 |
CLLaunch=MyRoutines.Potential(queue,(Number,1),None,clDataX,clPotential) |
890 |
CLLaunch=MyRoutines.Kinetic(queue,(Number,1),None,clDataV,clKinetic) |
891 |
CLLaunch.wait() |
892 |
cl.enqueue_copy(queue,MyCoM,clCoM) |
893 |
cl.enqueue_copy(queue,MyPotential,clPotential) |
894 |
cl.enqueue_copy(queue,MyKinetic,clKinetic) |
895 |
print('\nCenter Of Mass estimated: (%s,%s,%s)' % (MyCoM[0],MyCoM[1],MyCoM[2])) |
896 |
print('Energy estimated: Viriel=%s Potential=%s Kinetic=%s\n'% (np.sum(MyPotential)+2.*np.sum(MyKinetic),np.sum(MyPotential),np.sum(MyKinetic))) |
897 |
|
898 |
print("Duration stats on device %s with %s iterations :\n\tMean:\t%s\n\tMedian:\t%s\n\tStddev:\t%s\n\tMin:\t%s\n\tMax:\t%s\n\n\tVariability:\t%s\n" % (Device,Iterations,np.mean(Durations),np.median(Durations),np.std(Durations),np.min(Durations),np.max(Durations),np.std(Durations)/np.median(Durations)))
|
899 |
|
900 |
# FPS: 1/Elapsed
|
901 |
FPS=np.ones(len(Durations))
|
902 |
FPS/=Durations |
903 |
|
904 |
print("FPS stats on device %s with %s iterations :\n\tMean:\t%s\n\tMedian:\t%s\n\tStddev:\t%s\n\tMin:\t%s\n\tMax:\t%s\n" % (Device,Iterations,np.mean(FPS),np.median(FPS),np.std(FPS),np.min(FPS),np.max(FPS)))
|
905 |
|
906 |
# Contraction of Square*Size*Hertz: Size*Size/Elapsed
|
907 |
Squertz=np.ones(len(Durations))
|
908 |
Squertz*=Number*Number |
909 |
Squertz/=Durations |
910 |
|
911 |
print("Squertz in log10 & complete stats on device %s with %s iterations :\n\tMean:\t%s\t%s\n\tMedian:\t%s\t%s\n\tStddev:\t%s\t%s\n\tMin:\t%s\t%s\n\tMax:\t%s\t%s\n" % (Device,Iterations,np.log10(np.mean(Squertz)),np.mean(Squertz),np.log10(np.median(Squertz)),np.median(Squertz),np.log10(np.std(Squertz)),np.std(Squertz),np.log10(np.min(Squertz)),np.min(Squertz),np.log10(np.max(Squertz)),np.max(Squertz)))
|
912 |
|
913 |
clDataX.release() |
914 |
clDataV.release() |
915 |
clKinetic.release() |
916 |
clPotential.release() |
917 |
|