Centre Blaise Pascal » Bench4GPU

import numpy as np

import pyopencl as cl

import pyopencl.array as cl_array

from numpy.random import randint as nprnd

deviceID = 0

platformID = 0

workGroup=(1,1)

N = 10

MyData = np.zeros(N, dtype=cl_array.vec.float4)

dev = cl.get_platforms()[platformID].get_devices()[deviceID]

ctx = cl.Context([dev])

queue = cl.CommandQueue(ctx)

mf = cl.mem_flags

clData = cl.Buffer(ctx, mf.READ_WRITE, MyData.nbytes)

prg = cl.Program(ctx, """

#define znew  ((z=36969*(z&65535)+(z>>16))<<16)

#define wnew  ((w=18000*(w&65535)+(w>>16))&65535)

#define MWC   (znew+wnew)

#define SHR3  (jsr=(jsr=(jsr=jsr^(jsr<<17))^(jsr>>13))^(jsr<<5))

#define CONG  (jcong=69069*jcong+1234567)

#define KISS  ((MWC^CONG)+SHR3)

#define MWCfp MWC * 2.328306435454494e-10f

#define KISSfp KISS * 2.328306435454494e-10f

#define SHR3fp SHR3 * 2.328306435454494e-10f

#define CONGfp CONG * 2.328306435454494e-10f

__kernel void SplutterSpace(__global float4* clData, 

                               uint seed_z,uint seed_w)

{

   int gid = get_global_id(0);

   uint z=seed_z+(uint)gid;

   uint w=seed_w-(uint)gid;

  clData[gid].xyzw = (float4) (MWCfp,MWCfp,MWCfp,0.);

}

 """).build()

#prg.Pack_Cmplx(queue, (N,1), workGroup, Data_In, np.int32(N))

prg.SplutterSpace(queue, (N,1), None, clData, 

                   numpy.uint32(nprnd(2**32)),numpy.uint32(nprnd(2**32)))

cl.enqueue_copy(queue, MyData, clData)

print MyData

import numpy as np

import pyopencl as cl

import pyopencl.array as cl_array

from numpy.random import randint as nprnd

deviceID = 0

platformID = 0

workGroup=(1,1)

N = 10

MyData = np.zeros(N, dtype=cl_array.vec.float4)

dev = cl.get_platforms()[platformID].get_devices()[deviceID]

ctx = cl.Context([dev])

queue = cl.CommandQueue(ctx)

mf = cl.mem_flags

clData = cl.Buffer(ctx, mf.READ_WRITE, MyData.nbytes)

prg = cl.Program(ctx, """

#define znew  ((z=36969*(z&65535)+(z>>16))<<16)

#define wnew  ((w=18000*(w&65535)+(w>>16))&65535)

#define MWC   (znew+wnew)

#define SHR3  (jsr=(jsr=(jsr=jsr^(jsr<<17))^(jsr>>13))^(jsr<<5))

#define CONG  (jcong=69069*jcong+1234567)

#define KISS  ((MWC^CONG)+SHR3)

#define MWCfp MWC * 2.328306435454494e-10f

#define KISSfp KISS * 2.328306435454494e-10f

#define SHR3fp SHR3 * 2.328306435454494e-10f

#define CONGfp CONG * 2.328306435454494e-10f

__kernel void SplutterSpace(__global float4* clData, 

                               uint seed_z,uint seed_w)

{

   int gid = get_global_id(0);

   uint z=seed_z+(uint)gid;

   uint w=seed_w-(uint)gid;

  clData[gid].xyzw = (float4) (MWCfp,MWCfp,MWCfp,0.);

}

 """).build()

#prg.Pack_Cmplx(queue, (N,1), workGroup, Data_In, np.int32(N))

prg.SplutterSpace(queue, (N,1), None, clData, 

                   numpy.uint32(nprnd(2**32)),numpy.uint32(nprnd(2**32)))

cl.enqueue_copy(queue, MyData, clData)

print MyData

import numpy as np

import pyopencl as cl

import pyopencl.array as cl_array

deviceID = 0

platformID = 0

workGroup=(1,1)

N = 10

testData = np.zeros(N, dtype=cl_array.vec.float4)

dev = cl.get_platforms()[platformID].get_devices()[deviceID]

ctx = cl.Context([dev])

queue = cl.CommandQueue(ctx)

mf = cl.mem_flags

Data_In = cl.Buffer(ctx, mf.READ_WRITE, testData.nbytes)

prg = cl.Program(ctx, """

__kernel void   Pack_Cmplx( __global float4* Data_In, int  N)

{

  int gid = get_global_id(0);

  Data_In[gid] = 1;

}

 """).build()

prg.Pack_Cmplx(queue, (N,1), workGroup, Data_In, np.int32(N))

cl.enqueue_copy(queue, testData, Data_In)

print testData