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Sebastian Bindgen
pystencils
Commits
e20f82a3
Commit
e20f82a3
authored
Dec 09, 2020
by
Markus Holzer
Browse files
Merge branch 'rng' into 'master'
Make the RNG node behave more like a regular node See merge request
!194
parents
cf0dd636
fd7730d0
Changes
4
Hide whitespace changes
Inline
Side-by-side
.gitlab-ci.yml
View file @
e20f82a3
...
@@ -142,7 +142,7 @@ pycodegen-integration:
...
@@ -142,7 +142,7 @@ pycodegen-integration:
-
cd ../pygrandchem
-
cd ../pygrandchem
-
py.test -v -n $NUM_CORES .
-
py.test -v -n $NUM_CORES .
-
cd ../walberla/build/
-
cd ../walberla/build/
-
make CodegenJacobiCPU CodegenJacobiGPU CodegenPoissonCPU CodegenPoissonGPU MicroBenchmarkGpuLbm LbCodeGenerationExample UniformGridBenchmarkGPU_trt UniformGridBenchmarkGPU_entropic_kbc_n4
-
make CodegenJacobiCPU CodegenJacobiGPU CodegenPoissonCPU CodegenPoissonGPU MicroBenchmarkGpuLbm LbCodeGenerationExample UniformGridBenchmarkGPU_trt UniformGridBenchmarkGPU_entropic_kbc_n4
FluctuatingMRT
-
cd apps/benchmarks/UniformGridGPU
-
cd apps/benchmarks/UniformGridGPU
-
make -j $NUM_CORES
-
make -j $NUM_CORES
-
cd ../UniformGridGenerated
-
cd ../UniformGridGenerated
...
...
pystencils/astnodes.py
View file @
e20f82a3
...
@@ -37,8 +37,12 @@ class Node:
...
@@ -37,8 +37,12 @@ class Node:
def
subs
(
self
,
subs_dict
)
->
None
:
def
subs
(
self
,
subs_dict
)
->
None
:
"""Inplace! Substitute, similar to sympy's but modifies the AST inplace."""
"""Inplace! Substitute, similar to sympy's but modifies the AST inplace."""
for
a
in
self
.
args
:
for
i
,
a
in
enumerate
(
self
.
args
):
a
.
subs
(
subs_dict
)
result
=
a
.
subs
(
subs_dict
)
if
isinstance
(
a
,
sp
.
Expr
):
# sympy expressions' subs is out-of-place
self
.
args
[
i
]
=
result
else
:
# all other should be in-place
assert
result
is
None
@
property
@
property
def
func
(
self
):
def
func
(
self
):
...
...
pystencils/rng.py
View file @
e20f82a3
...
@@ -19,11 +19,9 @@ def _get_rng_template(name, data_type, num_vars):
...
@@ -19,11 +19,9 @@ def _get_rng_template(name, data_type, num_vars):
return
template
return
template
def
_get_rng_code
(
template
,
dialect
,
vector_instruction_set
,
time_step
,
coordinates
,
keys
,
dim
,
result_symbols
):
def
_get_rng_code
(
template
,
dialect
,
vector_instruction_set
,
args
,
result_symbols
):
parameters
=
[
time_step
]
+
coordinates
+
[
0
]
*
(
3
-
dim
)
+
list
(
keys
)
if
dialect
==
'cuda'
or
(
dialect
==
'c'
and
vector_instruction_set
is
None
):
if
dialect
==
'cuda'
or
(
dialect
==
'c'
and
vector_instruction_set
is
None
):
return
template
.
format
(
parameters
=
', '
.
join
(
str
(
p
)
for
p
in
p
ar
ameter
s
),
return
template
.
format
(
parameters
=
', '
.
join
(
str
(
a
)
for
a
in
ar
g
s
),
result_symbols
=
result_symbols
)
result_symbols
=
result_symbols
)
else
:
else
:
raise
NotImplementedError
(
"Not yet implemented for this backend"
)
raise
NotImplementedError
(
"Not yet implemented for this backend"
)
...
@@ -31,47 +29,38 @@ def _get_rng_code(template, dialect, vector_instruction_set, time_step, coordina
...
@@ -31,47 +29,38 @@ def _get_rng_code(template, dialect, vector_instruction_set, time_step, coordina
class
RNGBase
(
CustomCodeNode
):
class
RNGBase
(
CustomCodeNode
):
def
__init__
(
self
,
dim
,
time_step
=
TypedSymbol
(
"time_step"
,
np
.
uint32
),
offsets
=
(
0
,
0
,
0
),
keys
=
None
):
id
=
0
def
__init__
(
self
,
dim
,
time_step
=
TypedSymbol
(
"time_step"
,
np
.
uint32
),
offsets
=
None
,
keys
=
None
):
if
keys
is
None
:
if
keys
is
None
:
keys
=
(
0
,)
*
self
.
_num_keys
keys
=
(
0
,)
*
self
.
_num_keys
if
offsets
is
None
:
offsets
=
(
0
,)
*
dim
if
len
(
keys
)
!=
self
.
_num_keys
:
if
len
(
keys
)
!=
self
.
_num_keys
:
raise
ValueError
(
f
"Provided
{
len
(
keys
)
}
keys but need
{
self
.
_num_keys
}
"
)
raise
ValueError
(
f
"Provided
{
len
(
keys
)
}
keys but need
{
self
.
_num_keys
}
"
)
if
len
(
offsets
)
!=
3
:
if
len
(
offsets
)
!=
dim
:
raise
ValueError
(
f
"Provided
{
len
(
offsets
)
}
offsets but need
{
3
}
"
)
raise
ValueError
(
f
"Provided
{
len
(
offsets
)
}
offsets but need
{
dim
}
"
)
self
.
result_symbols
=
tuple
(
TypedSymbol
(
sp
.
Dummy
().
name
,
self
.
_data_type
)
for
_
in
range
(
self
.
_num_vars
))
coordinates
=
[
LoopOverCoordinate
.
get_loop_counter_symbol
(
i
)
+
offsets
[
i
]
for
i
in
range
(
dim
)]
symbols_read
=
[
s
for
s
in
keys
if
isinstance
(
s
,
sp
.
Symbol
)]
if
dim
<
3
:
coordinates
.
append
(
0
)
self
.
_args
=
sp
.
sympify
([
time_step
,
*
coordinates
,
*
keys
])
self
.
result_symbols
=
tuple
(
TypedSymbol
(
f
'random_
{
self
.
id
}
_
{
i
}
'
,
self
.
_data_type
)
for
i
in
range
(
self
.
_num_vars
))
symbols_read
=
set
.
union
(
*
[
s
.
atoms
(
sp
.
Symbol
)
for
s
in
self
.
args
])
super
().
__init__
(
""
,
symbols_read
=
symbols_read
,
symbols_defined
=
self
.
result_symbols
)
super
().
__init__
(
""
,
symbols_read
=
symbols_read
,
symbols_defined
=
self
.
result_symbols
)
self
.
_time_step
=
time_step
self
.
_offsets
=
offsets
self
.
_coordinates
=
[
LoopOverCoordinate
.
get_loop_counter_symbol
(
i
)
+
offsets
[
i
]
for
i
in
range
(
dim
)]
self
.
headers
=
[
f
'"
{
self
.
_name
}
_rand.h"'
]
self
.
headers
=
[
f
'"
{
self
.
_name
}
_rand.h"'
]
self
.
keys
=
tuple
(
keys
)
self
.
_args
=
sp
.
sympify
((
dim
,
time_step
,
keys
))
RNGBase
.
id
+=
1
self
.
_dim
=
dim
@
property
@
property
def
args
(
self
):
def
args
(
self
):
return
self
.
_args
return
self
.
_args
@
property
def
undefined_symbols
(
self
):
result
=
{
a
for
a
in
(
self
.
_time_step
,
*
self
.
_offsets
,
*
self
.
keys
)
if
isinstance
(
a
,
sp
.
Symbol
)}
loop_counters
=
[
LoopOverCoordinate
.
get_loop_counter_symbol
(
i
)
for
i
in
range
(
self
.
_dim
)]
result
.
update
(
loop_counters
)
return
result
def
subs
(
self
,
subs_dict
)
->
None
:
for
i
in
range
(
len
(
self
.
_coordinates
)):
self
.
_coordinates
[
i
]
=
self
.
_coordinates
[
i
].
subs
(
subs_dict
)
def
fast_subs
(
self
,
*
_
):
return
self
# nothing to replace inside this node - would destroy intermediate "dummy" by re-creating them
def
get_code
(
self
,
dialect
,
vector_instruction_set
):
def
get_code
(
self
,
dialect
,
vector_instruction_set
):
template
=
_get_rng_template
(
self
.
_name
,
self
.
_data_type
,
self
.
_num_vars
)
template
=
_get_rng_template
(
self
.
_name
,
self
.
_data_type
,
self
.
_num_vars
)
return
_get_rng_code
(
template
,
dialect
,
vector_instruction_set
,
return
_get_rng_code
(
template
,
dialect
,
vector_instruction_set
,
self
.
args
,
self
.
result_symbols
)
self
.
_time_step
,
self
.
_coordinates
,
self
.
keys
,
self
.
_dim
,
self
.
result_symbols
)
def
__repr__
(
self
):
def
__repr__
(
self
):
return
(
", "
.
join
([
'{}'
]
*
self
.
_num_vars
)
+
"
\\
leftarrow {}RNG"
).
format
(
*
self
.
result_symbols
,
return
(
", "
.
join
([
'{}'
]
*
self
.
_num_vars
)
+
"
\\
leftarrow {}RNG"
).
format
(
*
self
.
result_symbols
,
...
...
pystencils_tests/test_random.py
View file @
e20f82a3
...
@@ -12,58 +12,58 @@ philox_reference = np.array([[[3576608082, 1252663339, 1987745383, 348040302],
...
@@ -12,58 +12,58 @@ philox_reference = np.array([[[3576608082, 1252663339, 1987745383, 348040302],
[[
2958765206
,
3725192638
,
2623672781
,
1373196132
],
[[
2958765206
,
3725192638
,
2623672781
,
1373196132
],
[
850605163
,
1694561295
,
3285694973
,
2799652583
]]])
[
850605163
,
1694561295
,
3285694973
,
2799652583
]]])
def
test_philox_double
():
@
pytest
.
mark
.
parametrize
(
'target'
,
(
'cpu'
,
'gpu'
))
for
target
in
(
'cpu'
,
'gpu'
):
def
test_philox_double
(
target
):
if
target
==
'gpu'
:
if
target
==
'gpu'
:
pytest
.
importorskip
(
'pycuda'
)
pytest
.
importorskip
(
'pycuda'
)
dh
=
ps
.
create_data_handling
((
2
,
2
),
default_ghost_layers
=
0
,
default_target
=
target
)
dh
=
ps
.
create_data_handling
((
2
,
2
),
default_ghost_layers
=
0
,
default_target
=
target
)
f
=
dh
.
add_array
(
"f"
,
values_per_cell
=
2
)
f
=
dh
.
add_array
(
"f"
,
values_per_cell
=
2
)
dh
.
fill
(
'f'
,
42.0
)
dh
.
fill
(
'f'
,
42.0
)
philox_node
=
PhiloxTwoDoubles
(
dh
.
dim
)
philox_node
=
PhiloxTwoDoubles
(
dh
.
dim
)
assignments
=
[
philox_node
,
assignments
=
[
philox_node
,
ps
.
Assignment
(
f
(
0
),
philox_node
.
result_symbols
[
0
]),
ps
.
Assignment
(
f
(
0
),
philox_node
.
result_symbols
[
0
]),
ps
.
Assignment
(
f
(
1
),
philox_node
.
result_symbols
[
1
])]
ps
.
Assignment
(
f
(
1
),
philox_node
.
result_symbols
[
1
])]
kernel
=
ps
.
create_kernel
(
assignments
,
target
=
dh
.
default_target
).
compile
()
kernel
=
ps
.
create_kernel
(
assignments
,
target
=
dh
.
default_target
).
compile
()
dh
.
all_to_gpu
()
dh
.
all_to_gpu
()
dh
.
run_kernel
(
kernel
,
time_step
=
124
)
dh
.
run_kernel
(
kernel
,
time_step
=
124
)
dh
.
all_to_cpu
()
dh
.
all_to_cpu
()
arr
=
dh
.
gather_array
(
'f'
)
arr
=
dh
.
gather_array
(
'f'
)
assert
np
.
logical_and
(
arr
<=
1.0
,
arr
>=
0
).
all
()
assert
np
.
logical_and
(
arr
<=
1.0
,
arr
>=
0
).
all
()
x
=
philox_reference
[:,:,
0
::
2
]
x
=
philox_reference
[:,:,
0
::
2
]
y
=
philox_reference
[:,:,
1
::
2
]
y
=
philox_reference
[:,:,
1
::
2
]
z
=
x
^
y
<<
(
53
-
32
)
z
=
x
^
y
<<
(
53
-
32
)
double_reference
=
z
*
2.
**-
53
+
2.
**-
54
double_reference
=
z
*
2.
**-
53
+
2.
**-
54
assert
(
np
.
allclose
(
arr
,
double_reference
,
rtol
=
0
,
atol
=
np
.
finfo
(
np
.
float64
).
eps
))
assert
(
np
.
allclose
(
arr
,
double_reference
,
rtol
=
0
,
atol
=
np
.
finfo
(
np
.
float64
).
eps
))
def
test_philox_float
():
@
pytest
.
mark
.
parametrize
(
'target'
,
(
'cpu'
,
'gpu'
))
for
target
in
(
'cpu'
,
'gpu'
):
def
test_philox_float
(
target
):
if
target
==
'gpu'
:
if
target
==
'gpu'
:
pytest
.
importorskip
(
'pycuda'
)
pytest
.
importorskip
(
'pycuda'
)
dh
=
ps
.
create_data_handling
((
2
,
2
),
default_ghost_layers
=
0
,
default_target
=
target
)
dh
=
ps
.
create_data_handling
((
2
,
2
),
default_ghost_layers
=
0
,
default_target
=
target
)
f
=
dh
.
add_array
(
"f"
,
values_per_cell
=
4
)
f
=
dh
.
add_array
(
"f"
,
values_per_cell
=
4
)
dh
.
fill
(
'f'
,
42.0
)
dh
.
fill
(
'f'
,
42.0
)
philox_node
=
PhiloxFourFloats
(
dh
.
dim
)
philox_node
=
PhiloxFourFloats
(
dh
.
dim
)
assignments
=
[
philox_node
]
+
[
ps
.
Assignment
(
f
(
i
),
philox_node
.
result_symbols
[
i
])
for
i
in
range
(
4
)]
assignments
=
[
philox_node
]
+
[
ps
.
Assignment
(
f
(
i
),
philox_node
.
result_symbols
[
i
])
for
i
in
range
(
4
)]
kernel
=
ps
.
create_kernel
(
assignments
,
target
=
dh
.
default_target
).
compile
()
kernel
=
ps
.
create_kernel
(
assignments
,
target
=
dh
.
default_target
).
compile
()
dh
.
all_to_gpu
()
dh
.
all_to_gpu
()
dh
.
run_kernel
(
kernel
,
time_step
=
124
)
dh
.
run_kernel
(
kernel
,
time_step
=
124
)
dh
.
all_to_cpu
()
dh
.
all_to_cpu
()
arr
=
dh
.
gather_array
(
'f'
)
arr
=
dh
.
gather_array
(
'f'
)
assert
np
.
logical_and
(
arr
<=
1.0
,
arr
>=
0
).
all
()
assert
np
.
logical_and
(
arr
<=
1.0
,
arr
>=
0
).
all
()
float_reference
=
philox_reference
*
2.
**-
32
+
2.
**-
33
float_reference
=
philox_reference
*
2.
**-
32
+
2.
**-
33
assert
(
np
.
allclose
(
arr
,
float_reference
,
rtol
=
0
,
atol
=
np
.
finfo
(
np
.
float32
).
eps
))
assert
(
np
.
allclose
(
arr
,
float_reference
,
rtol
=
0
,
atol
=
np
.
finfo
(
np
.
float32
).
eps
))
def
test_aesni_double
():
def
test_aesni_double
():
dh
=
ps
.
create_data_handling
((
2
,
2
),
default_ghost_layers
=
0
,
default_target
=
"cpu"
)
dh
=
ps
.
create_data_handling
((
2
,
2
),
default_ghost_layers
=
0
,
default_target
=
"cpu"
)
...
...
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