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remove gpu code #420

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05164e7
remove gpu code
sblunt Aug 4, 2026
b4f14e3
remove cuda import
sblunt Aug 4, 2026
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10 changes: 0 additions & 10 deletions orbitize/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,16 +6,6 @@
orbitize_dir = os.path.dirname(__file__)
DATADIR = os.path.join(orbitize_dir, "example_data/")

# Detect a valid CUDA environment
try:
import pycuda.driver as cuda
import pycuda.autoinit
from pycuda.compiler import SourceModule

cuda_ext = True
except:
cuda_ext = False

try:
from . import _kepler

Expand Down
86 changes: 11 additions & 75 deletions orbitize/kepler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,15 +5,11 @@
import astropy.units as u
import astropy.constants as consts

from orbitize import cuda_ext, cext
from orbitize import cext

if cext:
from . import _kepler

if cuda_ext:
# Configure GPU context for CUDA accelerated compute
from orbitize import gpu_context
kep_gpu_ctx = gpu_context.gpu_context()

def tau_to_manom(date, sma, mtot, tau, tau_ref_epoch):
"""
Expand Down Expand Up @@ -54,7 +50,6 @@ def times2trueanom_and_eccanom(
tolerance=1e-9,
max_iter=100,
use_c=True,
use_gpu=False,
):
"""
Convert times to true anomaly and eccentric anomaly by solving Kepler's Equation.
Expand All @@ -69,7 +64,6 @@ def times2trueanom_and_eccanom(
tolerance (float, optional): absolute tolerance of iterative computation. Defaults to 1e-9.
max_iter (int, optional): maximum number of iterations before switching. Defaults to 100.
use_c (bool, optional): Use the C solver if configured. Defaults to True
use_gpu (bool, optional): Use the GPU solver if configured. Defaults to False

Returns:
2-tuple:
Expand All @@ -91,7 +85,7 @@ def times2trueanom_and_eccanom(
# # compute mean anomaly (size: n_orbs x n_dates)
manom = tau_to_manom(epochs[:, None], sma, mtot, tau, tau_ref_epoch)
# compute eccentric anomalies (size: n_orbs x n_dates)
eanom = _calc_ecc_anom(manom, ecc_arr, tolerance=tolerance, max_iter=max_iter, use_c=use_c, use_gpu=use_gpu)
eanom = _calc_ecc_anom(manom, ecc_arr, tolerance=tolerance, max_iter=max_iter, use_c=use_c)

# compute the true anomalies (size: n_orbs x n_dates)
# Note: matrix multiplication makes the shapes work out here and below
Expand All @@ -103,7 +97,7 @@ def times2trueanom_and_eccanom(

def calc_orbit(
epochs, sma, ecc, inc, aop, pan, tau, plx, mtot, mass_for_Kamp=None, tau_ref_epoch=58849, tolerance=1e-9,
max_iter=100, use_c=True, use_gpu=False
max_iter=100, use_c=True
):

"""
Expand All @@ -130,7 +124,6 @@ def calc_orbit(
tolerance (float, optional): absolute tolerance of iterative computation. Defaults to 1e-9.
max_iter (int, optional): maximum number of iterations before switching. Defaults to 100.
use_c (bool, optional): Use the C solver if configured. Defaults to True
use_gpu (bool, optional): Use the GPU solver if configured. Defaults to False

Return:
3-tuple:
Expand All @@ -151,7 +144,7 @@ def calc_orbit(
mass_for_Kamp = mtot
ecc

tanom, eanom = times2trueanom_and_eccanom(sma, epochs, mtot, ecc, tau, tau_ref_epoch=tau_ref_epoch, tolerance=tolerance, max_iter=max_iter, use_c=use_c, use_gpu=use_gpu)
tanom, eanom = times2trueanom_and_eccanom(sma, epochs, mtot, ecc, tau, tau_ref_epoch=tau_ref_epoch, tolerance=tolerance, max_iter=max_iter, use_c=use_c)

# compute 3-D orbital radius of second body (size: n_orbs x n_dates)
radius = sma * (1.0 - ecc * np.cos(eanom))
Expand Down Expand Up @@ -184,7 +177,7 @@ def calc_orbit(
vz = np.squeeze(vz)[()]
return raoff, deoff, vz

def _calc_ecc_anom(manom, ecc, tolerance=1e-9, max_iter=100, use_c=False, use_gpu=False):
def _calc_ecc_anom(manom, ecc, tolerance=1e-9, max_iter=100, use_c=False):
"""
Computes the eccentric anomaly from the mean anomlay.
Code from Rob De Rosa's orbit solver (e < 0.95 use Newton, e >= 0.95 use Mikkola)
Expand All @@ -195,7 +188,6 @@ def _calc_ecc_anom(manom, ecc, tolerance=1e-9, max_iter=100, use_c=False, use_gp
tolerance (float, optional): absolute tolerance of iterative computation. Defaults to 1e-9.
max_iter (int, optional): maximum number of iterations before switching. Defaults to 100.
use_c (bool, optional): Use the C solver if configured. Defaults to False
use_gpu (bool, optional): Use the GPU solver if configured. Defaults to False

Return:
eanom (float/np.array): eccentric anomalies, same shape as manom
Expand Down Expand Up @@ -231,16 +223,16 @@ def _calc_ecc_anom(manom, ecc, tolerance=1e-9, max_iter=100, use_c=False, use_gp
# Now low eccentricities
ind_low = np.where(~ecc_zero & ecc_low)
if len(ind_low[0]) > 0:
eanom[ind_low] = _newton_solver_wrapper(manom[ind_low], ecc[ind_low], tolerance, max_iter, use_c, use_gpu)
eanom[ind_low] = _newton_solver_wrapper(manom[ind_low], ecc[ind_low], tolerance, max_iter, use_c)

# Now high eccentricities
ind_high = np.where(~ecc_zero & ~ecc_low | (eanom == -1)) # The C and CUDA solvers return the unphysical value -1 if they fail to converge
if len(ind_high[0]) > 0:
eanom[ind_high] = _mikkola_solver_wrapper(manom[ind_high], ecc[ind_high], use_c, use_gpu)
eanom[ind_high] = _mikkola_solver_wrapper(manom[ind_high], ecc[ind_high], use_c)

return np.squeeze(eanom)[()]

def _newton_solver_wrapper(manom, ecc, tolerance, max_iter, use_c=False, use_gpu=False):
def _newton_solver_wrapper(manom, ecc, tolerance, max_iter, use_c=False):
"""
Wrapper for the various (Python, C, CUDA) implementations of the Newton-Raphson solver
for eccentric anomaly.
Expand All @@ -250,18 +242,14 @@ def _newton_solver_wrapper(manom, ecc, tolerance, max_iter, use_c=False, use_gpu
ecc (np.array): array of eccentricities
eanom0 (np.array, optional): array of first guess for eccentric anomaly, same shape as manom (optional)
use_c (bool, optional): Use the C solver if configured. Defaults to False
use_gpu (bool, optional): Use the GPU solver if configured. Defaults to False
Return:
eanom (np.array): array of eccentric anomalies

Written: Devin Cody, 2021
"""
eanom = np.empty_like(manom)

if cuda_ext and use_gpu:
# the CUDA solver returns eanom = -1 if it doesnt converge after max_iter iterations
eanom = _CUDA_newton_solver(manom, ecc, tolerance=tolerance, max_iter=max_iter)
elif cext and use_c:
if cext and use_c:
# the C solver returns eanom = -1 if it doesnt converge after max_iter iterations
eanom = _kepler._c_newton_solver(manom, ecc, tolerance=tolerance, max_iter=max_iter)
else:
Expand Down Expand Up @@ -323,42 +311,15 @@ def _newton_solver(manom, ecc, tolerance=1e-9, max_iter=100, eanom0=None):

return eanom

def _CUDA_newton_solver(manom, ecc, tolerance=1e-9, max_iter=100, eanom0=None):
"""
Helper function for calling the CUDA implementation of the Newton-Raphson solver for eccentric anomaly.

Args:
manom (np.array): array of mean anomalies
ecc (np.array): array of eccentricities
eanom0 (np.array, optional): array of first guess for eccentric anomaly, same shape as manom (optional)
Return:
eanom (np.array): array of eccentric anomalies

Written: Devin Cody, 2021
"""
global kep_gpu_ctx

# Ensure manom and ecc are np.array (might get passed as astropy.Table Columns instead)
manom = np.asarray(manom)
ecc = np.asarray(ecc)
eanom = np.empty_like(manom)
tolerance = np.asarray(tolerance, dtype = np.float64)
max_iter = np.asarray(max_iter)

kep_gpu_ctx.newton(manom, ecc, eanom, eanom0, tolerance, max_iter)

return eanom

def _mikkola_solver_wrapper(manom, ecc, use_c=False, use_gpu=False):
def _mikkola_solver_wrapper(manom, ecc, use_c=False):
"""
Wrapper for the various (Python, C, CUDA) implementations of Analtyical Mikkola solver

Args:
manom (np.array): array of mean anomalies between 0 and 2pi
ecc (np.array): eccentricity
use_c (bool, optional): Use the C solver if configured. Defaults to False
use_gpu (bool, optional): Use the GPU solver if configured. Defaults to False


Return:
eanom (np.array): array of eccentric anomalies
Expand All @@ -368,9 +329,7 @@ def _mikkola_solver_wrapper(manom, ecc, use_c=False, use_gpu=False):

ind_change = np.where(manom > np.pi)
manom[ind_change] = (2.0 * np.pi) - manom[ind_change]
if cuda_ext and use_gpu:
eanom = _CUDA_mikkola_solver(manom, ecc)
elif cext and use_c:
if cext and use_c:
eanom = _kepler._c_mikkola_solver(manom, ecc)
else:
eanom = _mikkola_solver(manom, ecc)
Expand Down Expand Up @@ -417,26 +376,3 @@ def _mikkola_solver(manom, ecc):
u4 = -f/(f1+0.5*f2*u3+(1.0/6.0)*f3*u3*u3+(1.0/24.0)*f4*(u3**3.0))

return (e0 + u4)

def _CUDA_mikkola_solver(manom, ecc):
"""
Helper function for calling the CUDA implementation of the Analtyical Mikkola solver for the eccentric anomaly.

Args:
manom (float or np.array): mean anomaly, must be between 0 and pi.
ecc (float or np.array): eccentricity
Return:
eanom (np.array): array of eccentric anomalies

Written: Devin Cody, 2021
"""
global kep_gpu_ctx

# Ensure manom and ecc are np.array (might get passed as astropy.Table Columns instead)
manom = np.asarray(manom)
ecc = np.asarray(ecc)
eanom = np.empty_like(manom)

kep_gpu_ctx.mikkola(manom, ecc, eanom)

return eanom
45 changes: 0 additions & 45 deletions orbitize/kernels/mikkola.cu
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50 changes: 0 additions & 50 deletions orbitize/kernels/newton.cu
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