def get_target(lang, device=None, compiler=None):
"""
Parameters
----------
lang : str
One of the supported languages, {'c', 'cuda', 'opencl'}
device : :class:`pyopencl.Device`
If supplied, and lang is 'opencl', passed to the
:class:`loopy.PyOpenCLTarget`
compiler: str
If supplied, the C-compiler to use
Returns
-------
The correct loopy target type
"""
utils.check_lang(lang)
# set target
if lang == 'opencl':
return lp.PyOpenCLTarget(device=device)
elif lang == 'c':
return lp.ExecutableCTarget(compiler=compiler)
elif lang == 'cuda':
return lp.CudaTarget()
elif lang == 'ispc':
return lp.ISPCTarget()
def test_cuda_short_vector():
knl = lp.make_kernel("{ [i]: 0<=i<n }",
"out[i] = 2*a[i]",
target=lp.CudaTarget())
knl = lp.set_options(knl, write_code=True)
knl = lp.split_iname(knl, "i", 4, slabs=(0, 1), inner_tag="vec")
knl = lp.split_array_axis(knl, "a,out", axis_nr=0, count=4)
knl = lp.tag_array_axes(knl, "a,out", "C,vec")
knl = lp.set_options(knl, write_wrapper=True)
knl = lp.add_and_infer_dtypes(knl, {"a": np.float32})
print(lp.generate_code_v2(knl).device_code())
import numpy as np
import loopy as lp
target = lp.CudaTarget()
kernel = lp.make_kernel("{ [i_node,j_node]: 0<=i_node,j_node<n_node}",
"""
<float32> coupling_value = params(1)
<float32> speed_value = params(0)
<float32> dt=0.1
<float32> M_PI_F = 2.0
<float32> rec_n = 1.0f / n_node
<float32> rec_speed_dt = 1.0f / speed_value / dt
<float32> omega = 10.0 * 2.0 * M_PI_F / 1e3
<float32> sig = sqrt(dt) * sqrt(2.0 * 1e-5)
<float32> rand = 1.0
for i_node
tavg[i_node]=0.0f {id = clear}
end
for i_node
<float32> theta_i = state[i_node] {id = coupling1, dep=*}
<float32> sum = 0.0 {id = coupling2}
for j_node
<float32> wij = weights[j_node] {id = coupling3, dep=coupling1:coupling2}
if wij != 0.0
<int> dij = lengths[j_node] * rec_speed_dt {id = coupling4, dep=coupling3}
<float32> theta_j = state[j_node]
sum = sum + wij * sin(theta_j - theta_i)