def test_vectorize(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(
"{[i]: 0<=i<n}", """
<> temp = 2*b[i]
a[i] = temp
""")
knl = lp.add_and_infer_dtypes(knl, dict(b=np.float32))
knl = lp.set_array_dim_names(knl, "a,b", "i")
knl = lp.split_array_dim(knl, [("a", 0), ("b", 0)],
4,
split_kwargs=dict(slabs=(0, 1)))
knl = lp.tag_data_axes(knl, "a,b", "c,vec")
ref_knl = knl
ref_knl = lp.tag_inames(ref_knl, {"i_inner": "unr"})
knl = lp.tag_inames(knl, {"i_inner": "vec"})
knl = lp.preprocess_kernel(knl)
knl = lp.get_one_scheduled_kernel(knl)
code, inf = lp.generate_code(knl)
lp.auto_test_vs_ref(ref_knl, ctx, knl, parameters=dict(n=30))
def test_vectorize(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(
"{[i]: 0<=i<n}",
"""
<> temp = 2*b[i]
a[i] = temp
""")
knl = lp.add_and_infer_dtypes(knl, dict(b=np.float32))
knl = lp.set_array_dim_names(knl, "a,b", "i")
knl = lp.split_array_dim(knl, [("a", 0), ("b", 0)], 4,
split_kwargs=dict(slabs=(0, 1)))
knl = lp.tag_data_axes(knl, "a,b", "c,vec")
ref_knl = knl
ref_knl = lp.tag_inames(ref_knl, {"i_inner": "unr"})
knl = lp.tag_inames(knl, {"i_inner": "vec"})
knl = lp.preprocess_kernel(knl)
knl = lp.get_one_scheduled_kernel(knl)
code, inf = lp.generate_code(knl)
lp.auto_test_vs_ref(
ref_knl, ctx, knl,
parameters=dict(n=30))
def set_q_storage_format(kernel, name):
kernel = lp.set_array_dim_names(kernel, name, "i,j,k,field,e")
kernel = lp.split_array_dim(kernel, (name, 3, "F"), 4, auto_split_inames=False)
kernel = lp.tag_data_axes(kernel, name, "N0,N1,N2,vec,N4,N3")
return kernel
def set_q_storage_format(kernel, name):
kernel = lp.set_array_dim_names(kernel, name, "i,j,k,field,e")
kernel = lp.split_array_dim(kernel, (name, 3, "F"),
4,
auto_split_inames=False)
kernel = lp.tag_data_axes(kernel, name, "N0,N1,N2,vec,N4,N3")
return kernel
