Classy: \Omega_\lambda nan crash

Use of Cobaya. camb, CLASS, cosmomc, compilers, etc.
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Brandon Stevenson
Posts: 2
Joined: July 15 2020
Affiliation: SMU

Classy: \Omega_\lambda nan crash

Post by Brandon Stevenson » August 18 2021

I am trying to get cobaya (v3.1.1) running on a mainframe using the basic cosmo run(https://cobaya.readthedocs.io/en/latest/cosmo_basic_runs.html) with classy (v3.0.1) and mpi. However, I keep getting crash after around 20 plus hours that I have tracked down to \omega_\lambda being set to nan. I was wondering if anyone else has experienced this issue and has any idea how to fix it.

Also, I have noticed classy is running quite slow. ~0.16 runs/sec and was wondering if anyone has been able to speed this up?

Thanks,

yaml input file wrote: theory:
classy:
extra_args:
non linear: hmcode
hmcode_min_k_max: 20
N_ncdm: 1
N_ur: 2.0328
input_verbose: 2
background_verbose: 2
thermodynamics_verbose: 1
perturbations_verbose: 1
transfer_verbose: 1
primordial_verbose: 1
harmonic_verbose: 1
fourier_verbose: 1
lensing_verbose: 1
distortions_verbose: 1
output_verbose: 1
likelihood:
planck_2018_lowl.TT: null
planck_2018_lowl.EE: null
planck_2018_highl_plik.TTTEEE: null
planck_2018_lensing.clik: null
params:
logA:
prior:
min: 1.61
max: 3.91
ref:
dist: norm
loc: 3.05
scale: 0.001
proposal: 0.001
latex: \log(10^{10} A_\mathrm{s})
drop: true
A_s:
value: 'lambda logA: 1e-10*np.exp(logA)'
latex: A_\mathrm{s}
n_s:
prior:
min: 0.8
max: 1.2
ref:
dist: norm
loc: 0.965
scale: 0.004
proposal: 0.002
latex: n_\mathrm{s}
theta_s_1e2:
prior:
min: 0.5
max: 10
ref:
dist: norm
loc: 1.0416
scale: 0.0004
proposal: 0.0002
latex: 100\theta_\mathrm{s}
drop: true
100*theta_s:
value: 'lambda theta_s_1e2: theta_s_1e2'
derived: false
H0:
latex: H_0
omega_b:
prior:
min: 0.005
max: 0.1
ref:
dist: norm
loc: 0.0224
scale: 0.0001
proposal: 0.0001
latex: \Omega_\mathrm{b} h^2
omega_cdm:
prior:
min: 0.001
max: 0.99
ref:
dist: norm
loc: 0.12
scale: 0.001
proposal: 0.0005
latex: \Omega_\mathrm{c} h^2
Omega_m:
latex: \Omega_\mathrm{m}
omegamh2:
derived: 'lambda Omega_m, H0: Omega_m*(H0/100)**2'
latex: \Omega_\mathrm{m} h^2
m_ncdm:
value: 0.06
renames: mnu
Omega_Lambda:
latex: \Omega_\Lambda
YHe:
latex: Y_\mathrm{P}
tau_reio:
prior:
min: 0.01
max: 0.8
ref:
dist: norm
loc: 0.055
scale: 0.006
proposal: 0.003
latex: \tau_\mathrm{reio}
z_reio:
latex: z_\mathrm{re}
sigma8:
latex: \sigma_8
s8h5:
derived: 'lambda sigma8, H0: sigma8*(H0*1e-2)**(-0.5)'
latex: \sigma_8/h^{0.5}
s8omegamp5:
derived: 'lambda sigma8, Omega_m: sigma8*Omega_m**0.5'
latex: \sigma_8 \Omega_\mathrm{m}^{0.5}
s8omegamp25:
derived: 'lambda sigma8, Omega_m: sigma8*Omega_m**0.25'
latex: \sigma_8 \Omega_\mathrm{m}^{0.25}
A:
derived: 'lambda A_s: 1e9*A_s'
latex: 10^9 A_\mathrm{s}
clamp:
derived: 'lambda A_s, tau_reio: 1e9*A_s*np.exp(-2*tau_reio)'
latex: 10^9 A_\mathrm{s} e^{-2\tau}
age:
latex: '{\rm{Age}}/\mathrm{Gyr}'
rs_drag:
latex: r_\mathrm{drag}
sampler:
mcmc:
drag: true
oversample_power: 0.4
proposal_scale: 1.9
covmat: auto
Rminus1_stop: 0.05
Rminus1_cl_stop: 0.2
measure_speeds: 10
# learn_every: 1d
# output_every: 3600s #60s
# learn_every: 100d #40d
max_samples: 10000 #.inf

output: chains/lambda-verbose/20400868/lambda-verbose
packages_path: '/users/stevensonb/Research/Hubble/packages/'
error stacktrace wrote: Computing thermodynamics using HyRec 2020
-> with primordial helium mass fraction Y_He = 0.2454
-> recombination (maximum of visibility function) at z = 1088.868926
corresponding to conformal time = 280.583883 Mpc
with comoving sound horizon = 144.523105 Mpc
angular diameter distance = 12.726766 Mpc
sound horizon angle 100*theta_s = 1.041945
Thomson optical depth crosses one at z_* = 1085.035015
giving an angle 100*theta_* = 1.044415
-> baryon drag stops at z = 1059.767482
corresponding to conformal time = 286.297563 Mpc
with comoving sound horizon rs = 147.107476 Mpc
-> reionization at z = 7.929764
corresponding to conformal time = 5041.255667 Mpc
Computing sources
Computing primordial spectra (analytic spectrum)
Computing linear Fourier spectra.
-> sigma8=0.810524 for total matter (computed till k = 1.70725 h/Mpc)
-> sigma8=0.813994 for baryons+cdm (computed till k = 1.70725 h/Mpc)
Computing non-linear matter power spectrum with HMcode
-> [WARNING:] Non-linear corrections could not be computed at redshift z= 1.39 and higher.
This is because k_max is too small for the algorithm (Halofit or HMcode) to be able to compute the scale k_NL at this redshift.
If non-linear corrections at such high redshift really matter for you,
just try to increase one of the parameters P_k_max_h/Mpc or P_k_max_1/Mpc or halofit_min_k_max (the code will take the max of these parameters) until reaching desired z.
Computing transfers
Computing unlensed harmonic spectra
Computing lensed spectra (fast mode)
No distortions requested. Distortions module skipped.
Reading input parameters
Computing unknown input parameter 'h' using input parameter '100*theta_s'
-> matched budget equations by adjusting Omega_Lambda = 0.691038
-> matched budget equations by adjusting Omega_Lambda = 0.715441
-> matched budget equations by adjusting Omega_Lambda = 0.691244
-> matched budget equations by adjusting Omega_Lambda = 0.663824
-> matched budget equations by adjusting Omega_Lambda = 0.677972
-> matched budget equations by adjusting Omega_Lambda = 0.686797
-> matched budget equations by adjusting Omega_Lambda = 0.689032
-> matched budget equations by adjusting Omega_Lambda = nan
[b172:36525:0:36525] Caught signal 11 (Segmentation fault: Sent by the kernel at address (nil))
==== backtrace (tid: 36525) ====
0 0x000000000004cb95 ucs_debug_print_backtrace() ???:0
1 0x000000000013da83 numjac() /users/stevensonb/Research/Hubble/packages/code/classy/build/../tools/evolver_ndf15.c:1355
2 0x000000000013f9fc evolver_ndf15() /users/stevensonb/Research/Hubble/packages/code/classy/build/../tools/evolver_ndf15.c:240
3 0x00000000000c8cf3 background_solve() /users/stevensonb/Research/Hubble/packages/code/classy/build/../source/background.c:1876
4 0x00000000000c99d1 background_init() /users/stevensonb/Research/Hubble/packages/code/classy/build/../source/background.c:782
5 0x00000000000c0253 input_try_unknown_parameters() /users/stevensonb/Research/Hubble/packages/code/classy/build/../source/input.c:1275
6 0x00000000000c0cb9 input_fzerofun_1d() /users/stevensonb/Research/Hubble/packages/code/classy/build/../source/input.c:906
7 0x000000000009f5ed input_fzero_ridder() /users/stevensonb/Research/Hubble/packages/code/classy/build/../source/input.c:991
8 0x00000000000c0f0c input_find_root() /users/stevensonb/Research/Hubble/packages/code/classy/build/../source/input.c:872
9 0x00000000000c184f input_shooting() /users/stevensonb/Research/Hubble/packages/code/classy/build/../source/input.c:654
10 0x00000000000c1cd8 input_read_from_file() /users/stevensonb/Research/Hubble/packages/code/classy/build/../source/input.c:419
11 0x0000000000094a17 __pyx_pf_6classy_5Class_18compute() /users/stevensonb/Research/Hubble/packages/code/classy/python/../python/classy.c:6843
12 0x000000000009708f __pyx_pw_6classy_5Class_19compute() /users/stevensonb/Research/Hubble/packages/code/classy/python/../python/classy.c:6607
13 0x0000000000180804 _PyMethodDef_RawFastCallKeywords() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:693
14 0x0000000000187c9d _PyMethodDescr_FastCallKeywords() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/descrobject.c:288
15 0x00000000001ebc1b call_function() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4594
16 0x00000000001ebc1b _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3111
17 0x000000000012be88 _PyEval_EvalCodeWithName() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3931
18 0x000000000012c9e3 _PyFunction_FastCallDict() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:376
19 0x000000000014cf31 _PyObject_Call_Prepend() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:906
20 0x000000000013e445 PyObject_Call() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:245
21 0x00000000001e8c09 do_call_core() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4646
22 0x00000000001e8c09 _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3192
23 0x000000000012b628 _PyEval_EvalCodeWithName() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3931
24 0x000000000017ff36 _PyFunction_FastCallKeywords() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:433
25 0x00000000001e8388 call_function() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4617
26 0x00000000001e8388 _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3140
27 0x000000000012be88 _PyEval_EvalCodeWithName() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3931
28 0x000000000017ff36 _PyFunction_FastCallKeywords() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:433
29 0x00000000001e8388 call_function() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4617
30 0x00000000001e8388 _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3140
31 0x000000000012b628 _PyEval_EvalCodeWithName() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3931
32 0x000000000017ff36 _PyFunction_FastCallKeywords() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:433
33 0x00000000001e8388 call_function() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4617
34 0x00000000001e8388 _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3140
35 0x000000000012b628 _PyEval_EvalCodeWithName() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3931
36 0x000000000017fed4 _PyFunction_FastCallKeywords() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:433
37 0x00000000001e75df call_function() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4617
38 0x00000000001e75df _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3111
39 0x000000000017fc9a function_code_fastcall() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:283
40 0x000000000017fc9a _PyFunction_FastCallKeywords() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:408
41 0x00000000001ebb08 call_function() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4617
42 0x00000000001ebb08 _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3094
43 0x000000000017fc9a function_code_fastcall() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:283
44 0x000000000017fc9a _PyFunction_FastCallKeywords() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:408
45 0x00000000001e75df call_function() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4617
46 0x00000000001e75df _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3111
47 0x000000000012b628 _PyEval_EvalCodeWithName() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3931
48 0x000000000012c9e3 _PyFunction_FastCallDict() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:376
49 0x00000000001e8c09 do_call_core() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4646
50 0x00000000001e8c09 _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3192
51 0x000000000017fada function_code_fastcall() /home/sat_bot/base/conda-bld/python_1604523054000/work/Objects/call.c:283
52 0x00000000001e73d5 call_function() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:4617
53 0x00000000001e73d5 _PyEval_EvalFrameDefault() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3125
54 0x000000000012b628 _PyEval_EvalCodeWithName() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3931
55 0x000000000012c563 PyEval_EvalCodeEx() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:3960
56 0x000000000012c5bb PyEval_EvalCode() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/ceval.c:524
57 0x0000000000254476 run_mod() /home/sat_bot/base/conda-bld/python_1604523054000/work/Python/pythonrun.c:1035
=================================
srun: error: b172: task 0: Segmentation fault
Last edited by Brandon Stevenson on August 19 2021, edited 1 time in total.

Antony Lewis
Posts: 1720
Joined: September 23 2004
Affiliation: University of Sussex
Contact:

Re: Cobaya: \Omega_\lambda nan crash

Post by Antony Lewis » August 19 2021

Title should be "Classy: \Omega_\lambda nan crash" as not specific to Cobaya?

Brandon Stevenson
Posts: 2
Joined: July 15 2020
Affiliation: SMU

Re: Cobaya: \Omega_\lambda nan crash

Post by Brandon Stevenson » August 19 2021

Antony Lewis wrote:
August 19 2021
Title should be "Classy: \Omega_\lambda nan crash" as not specific to Cobaya?
Thanks, changed the title.

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