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EiffL 2024-07-09 18:02:57 -04:00
parent 6408aff1de
commit 319942a6bc
5 changed files with 113 additions and 96 deletions
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57
dev/jaxdecomp.py
View file

@ -1,4 +1,5 @@
import argparse
import jax
import numpy as np
@ -9,15 +10,17 @@ size = jax.process_count()
import jax.numpy as jnp
import jax_cosmo as jc
from jaxpm.pm import linear_field, lpt
from jaxpm.painting import cic_paint
from jax.experimental import mesh_utils
from jax.sharding import Mesh
mesh_shape= [256, 256, 256]
box_size = [256.,256.,256.]
from jaxpm.painting import cic_paint
from jaxpm.pm import linear_field, lpt
mesh_shape = [256, 256, 256]
box_size = [256., 256., 256.]
snapshots = jnp.linspace(0.1, 1., 2)
@jax.jit
def run_simulation(omega_c, sigma8, seed):
# Create a cosmology
@ -25,38 +28,42 @@ def run_simulation(omega_c, sigma8, seed):
# Create a small function to generate the matter power spectrum
k = jnp.logspace(-4, 1, 128)
pk = jc.power.linear_matter_power(jc.Planck15(Omega_c=omega_c, sigma8=sigma8), k)
pk_fn = lambda x: jc.scipy.interpolate.interp(x.reshape([-1]), k, pk).reshape(x.shape)
pk = jc.power.linear_matter_power(
jc.Planck15(Omega_c=omega_c, sigma8=sigma8), k)
pk_fn = lambda x: jc.scipy.interpolate.interp(x.reshape([-1]), k, pk
).reshape(x.shape)
# Create initial conditions
initial_conditions = linear_field(mesh_shape, box_size, pk_fn, seed=seed)
# Initialize particle displacements
# Initialize particle displacements
dx, p, f = lpt(cosmo, initial_conditions, 1.0)
field = cic_paint(jnp.zeros_like(initial_conditions), dx)
return field
def main(args):
# Setting up distributed random numbers
master_key = jax.random.PRNGKey(42)
key = jax.random.split(master_key, size)[rank]
# Setting up distributed random numbers
master_key = jax.random.PRNGKey(42)
key = jax.random.split(master_key, size)[rank]
# Create computing mesh and sharding information
devices = mesh_utils.create_device_mesh((2,2))
mesh = Mesh(devices.T, axis_names=('x', 'y'))
# Create computing mesh and sharding information
devices = mesh_utils.create_device_mesh((2, 2))
mesh = Mesh(devices.T, axis_names=('x', 'y'))
# Run the simulation on the compute mesh
with mesh:
field = run_simulation(0.32, 0.8, key)
# Run the simulation on the compute mesh
with mesh:
field = run_simulation(0.32, 0.8, key)
print('done')
np.save(f'field_{rank}.npy', field.addressable_data(0))
# Closing distributed jax
jax.distributed.shutdown()
print('done')
np.save(f'field_{rank}.npy', field.addressable_data(0))
# Closing distributed jax
jax.distributed.shutdown()
if __name__ == '__main__':
parser = argparse.ArgumentParser("Distributed LPT N-body simulation.")
args = parser.parse_args()
main(args)
parser = argparse.ArgumentParser("Distributed LPT N-body simulation.")
args = parser.parse_args()
main(args)

31
jaxpm/distributed.py
View file

@ -16,11 +16,11 @@ from jax.experimental.shard_map import shard_map
def autoshmap(f: Callable,
in_specs: Specs,
out_specs: Specs,
check_rep: bool = True,
auto: frozenset[AxisName] = frozenset()):
"""Helper function to wrap the provided function in a shard map if
in_specs: Specs,
out_specs: Specs,
check_rep: bool = True,
auto: frozenset[AxisName] = frozenset()):
"""Helper function to wrap the provided function in a shard map if
the code is being executed in a mesh context."""
mesh = mesh_lib.thread_resources.env.physical_mesh
if mesh.empty:
@ -28,23 +28,28 @@ def autoshmap(f: Callable,
else:
return shard_map(f, mesh, in_specs, out_specs, check_rep, auto)
def fft3d(x):
if distributed and not(mesh_lib.thread_resources.env.physical_mesh.empty):
if distributed and not (mesh_lib.thread_resources.env.physical_mesh.empty):
return jaxdecomp.pfft3d(x.astype(jnp.complex64))
else:
return jnp.fft.rfftn(x)
def ifft3d(x):
if distributed and not(mesh_lib.thread_resources.env.physical_mesh.empty):
if distributed and not (mesh_lib.thread_resources.env.physical_mesh.empty):
return jaxdecomp.pifft3d(x).real
else:
return jnp.fft.irfftn(x)
def get_local_shape(mesh_shape):
""" Helper function to get the local size of a mesh given the global size.
""" Helper function to get the local size of a mesh given the global size.
"""
if mesh_lib.thread_resources.env.physical_mesh.empty:
return mesh_shape
else:
pdims = mesh_lib.thread_resources.env.physical_mesh.devices.shape
return [mesh_shape[0] // pdims[0], mesh_shape[1] // pdims[1], mesh_shape[2]]
if mesh_lib.thread_resources.env.physical_mesh.empty:
return mesh_shape
else:
pdims = mesh_lib.thread_resources.env.physical_mesh.devices.shape
return [
mesh_shape[0] // pdims[0], mesh_shape[1] // pdims[1], mesh_shape[2]
]

33
jaxpm/kernels.py
View file

@ -1,12 +1,14 @@
from jaxpm.distributed import autoshmap
from jax.sharding import PartitionSpec as P
from functools import partial
import jax.numpy as jnp
import numpy as np
from jax.sharding import PartitionSpec as P
from jaxpm.distributed import autoshmap
def fftk(shape, dtype=np.float32):
"""
"""
Generate Fourier transform wave numbers for a given mesh.
Args:
@ -16,18 +18,19 @@ def fftk(shape, dtype=np.float32):
list: List of wave number arrays for each dimension in
the order [kx, ky, kz].
"""
kx, ky, kz = [jnp.fft.fftfreq(s, dtype=dtype) * 2 * np.pi for s in shape]
@partial(
autoshmap,
in_specs=(P('x'), P('y'), P(None)),
out_specs=(P('x'), P(None, 'y'), P(None)))
def get_kvec(ky, kz, kx):
return (ky.reshape([-1, 1, 1]),
kz.reshape([1, -1, 1]),
kx.reshape([1, 1, -1])) # yapf: disable
ky, kz, kx = get_kvec(ky, kz, kx) # The order corresponds
# to the order of dimensions in the transposed FFT
return kx, ky, kz
kx, ky, kz = [jnp.fft.fftfreq(s, dtype=dtype) * 2 * np.pi for s in shape]
@partial(autoshmap,
in_specs=(P('x'), P('y'), P(None)),
out_specs=(P('x'), P(None, 'y'), P(None)))
def get_kvec(ky, kz, kx):
return (ky.reshape([-1, 1, 1]),
kz.reshape([1, -1, 1]),
kx.reshape([1, 1, -1])) # yapf: disable
ky, kz, kx = get_kvec(ky, kz, kx) # The order corresponds
# to the order of dimensions in the transposed FFT
return kx, ky, kz
def gradient_kernel(kvec, direction, order=1):
"""

43
jaxpm/painting.py
View file

@ -1,26 +1,28 @@
from functools import partial
import jax
import jax.lax as lax
import jax.numpy as jnp
from jaxpm.kernels import cic_compensation, fftk
from jax.sharding import PartitionSpec as P
from functools import partial
from jaxpm.distributed import autoshmap
@partial(autoshmap,
in_specs=(P('x', 'y'), P('x','y'), P('x','y')),
out_specs=P('x', 'y'))
from jaxpm.distributed import autoshmap
from jaxpm.kernels import cic_compensation, fftk
@partial(autoshmap,
in_specs=(P('x', 'y'), P('x', 'y'), P('x', 'y')),
out_specs=P('x', 'y'))
def cic_paint(mesh, displacement, weight=None):
""" Paints positions onto mesh
mesh: [nx, ny, nz]
displacement field: [nx, ny, nz, 3]
"""
part_shape = displacement.shape
positions = jnp.stack(jnp.meshgrid(
jnp.arange(part_shape[0]),
jnp.arange(part_shape[1]),
jnp.arange(part_shape[2]),
indexing='ij'), axis=-1) + displacement
positions = jnp.stack(jnp.meshgrid(jnp.arange(part_shape[0]),
jnp.arange(part_shape[1]),
jnp.arange(part_shape[2]),
indexing='ij'),
axis=-1) + displacement
positions = positions.reshape([-1, 3])
positions = jnp.expand_dims(positions, 1)
floor = jnp.floor(positions)
@ -46,9 +48,7 @@ def cic_paint(mesh, displacement, weight=None):
return mesh
@partial(autoshmap,
in_specs=(P('x', 'y'), P('x','y')),
out_specs=P('x', 'y'))
@partial(autoshmap, in_specs=(P('x', 'y'), P('x', 'y')), out_specs=P('x', 'y'))
def cic_read(mesh, displacement):
""" Paints positions onto mesh
mesh: [nx, ny, nz]
@ -56,11 +56,11 @@ def cic_read(mesh, displacement):
"""
# Compute the position of the particles on a regular grid
part_shape = displacement.shape
positions = jnp.stack(jnp.meshgrid(
jnp.arange(part_shape[0]),
jnp.arange(part_shape[1]),
jnp.arange(part_shape[2]),
indexing='ij'), axis=-1) + displacement
positions = jnp.stack(jnp.meshgrid(jnp.arange(part_shape[0]),
jnp.arange(part_shape[1]),
jnp.arange(part_shape[2]),
indexing='ij'),
axis=-1) + displacement
positions = positions.reshape([-1, 3])
positions = jnp.expand_dims(positions, 1)
floor = jnp.floor(positions)
@ -75,7 +75,8 @@ def cic_read(mesh, displacement):
jnp.array(mesh.shape))
return (mesh[neighboor_coords[..., 0], neighboor_coords[..., 1],
neighboor_coords[..., 3]] * kernel).sum(axis=-1).reshape(displacement.shape[:-1])
neighboor_coords[..., 3]] * kernel).sum(axis=-1).reshape(
displacement.shape[:-1])
def cic_paint_2d(mesh, positions, weight):

45
jaxpm/pm.py
View file

@ -1,15 +1,16 @@
from functools import partial
import jax
import jax.numpy as jnp
import jax_cosmo as jc
from jax.sharding import PartitionSpec as P
from jaxpm.distributed import autoshmap, fft3d, get_local_shape, ifft3d
from jaxpm.growth import dGfa, growth_factor, growth_rate
from jaxpm.kernels import (PGD_kernel, fftk, gradient_kernel, laplace_kernel,
longrange_kernel)
from jaxpm.painting import cic_paint, cic_read
from jaxpm.distributed import fft3d, ifft3d, autoshmap, get_local_shape
from functools import partial
def pm_forces(positions, mesh_shape=None, delta=None, r_split=0):
"""
@ -100,28 +101,28 @@ def make_ode_fn(mesh_shape):
return nbody_ode
def pgd_correction(pos, params):
"""
improve the short-range interactions of PM-Nbody simulations with potential gradient descent method, based on https://arxiv.org/abs/1804.00671
args:
pos: particle positions [npart, 3]
params: [alpha, kl, ks] pgd parameters
"""
kvec = fftk(mesh_shape)
def pgd_correction(pos, params):
"""
improve the short-range interactions of PM-Nbody simulations with potential gradient descent method, based on https://arxiv.org/abs/1804.00671
args:
pos: particle positions [npart, 3]
params: [alpha, kl, ks] pgd parameters
"""
kvec = fftk(mesh_shape)
delta = cic_paint(jnp.zeros(mesh_shape), pos)
alpha, kl, ks = params
delta_k = jnp.fft.rfftn(delta)
PGD_range = PGD_kernel(kvec, kl, ks)
delta = cic_paint(jnp.zeros(mesh_shape), pos)
alpha, kl, ks = params
delta_k = jnp.fft.rfftn(delta)
PGD_range = PGD_kernel(kvec, kl, ks)
pot_k_pgd = (delta_k * laplace_kernel(kvec)) * PGD_range
pot_k_pgd = (delta_k * laplace_kernel(kvec)) * PGD_range
forces_pgd = jnp.stack([
cic_read(jnp.fft.irfftn(gradient_kernel(kvec, i) * pot_k_pgd), pos)
for i in range(3)
],
axis=-1)
forces_pgd = jnp.stack([
cic_read(jnp.fft.irfftn(gradient_kernel(kvec, i) * pot_k_pgd), pos)
for i in range(3)
],
axis=-1)
dpos_pgd = forces_pgd * alpha
dpos_pgd = forces_pgd * alpha
return dpos_pgd
return dpos_pgd