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Recover numba #108

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merged 5 commits into from
Mar 29, 2022
Merged

Recover numba #108

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8fd88b2
Remove all numba signatures
felixhekhorn Mar 18, 2022
e18e72b
Adding n_core_parallel option
giacomomagni Mar 28, 2022
8008269
remove parallel computation in tests
giacomomagni Mar 28, 2022
5986134
restore benchmarks
giacomomagni Mar 28, 2022
d5f8bba
minor fixes on data db
giacomomagni Mar 29, 2022
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1 change: 1 addition & 0 deletions benchmarks/eko/benchmark_evol_to_unity.py
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Expand Up @@ -49,6 +49,7 @@ class BenchmarkBackwardForward:
"ev_op_max_order": 1,
"ev_op_iterations": 1,
"backward_inversion": "exact",
"n_integration_cores": 1,
}
g = OperatorGrid.from_dict(
theory_card,
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14 changes: 7 additions & 7 deletions benchmarks/lha_paper_bench.py
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Expand Up @@ -222,14 +222,14 @@ def benchmark_sv(self, pto):

# Benchmark to LHA
# obj = BenchmarkVFNS()
# obj = BenchmarkFFNS()
obj = BenchmarkFFNS()

# obj.benchmark_plain(2)
obj.benchmark_plain(0)
# obj.benchmark_sv(2)

# # VFNS benchmarks with LHA settings
programs = ["LHA", "pegasus", "apfel"]
for p in programs:
obj = BenchmarkRunner(p)
# obj.benchmark_plain(2)
obj.benchmark_sv(2)
# programs = ["LHA", "pegasus", "apfel"]
# for p in programs:
# obj = BenchmarkRunner(p)
# # obj.benchmark_plain(2)
# obj.benchmark_sv(2)
1 change: 1 addition & 0 deletions pyproject.toml
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Expand Up @@ -84,6 +84,7 @@ bench-run.env.NUMBA_DISABLE_JIT.default = "0"
lint = "pylint src/**/*.py -E"
lint-warnings = "pylint src/**/*.py --exit-zero"
sandbox = "python benchmarks/sandbox.py"
lha = "python benchmarks/lha_paper_bench.py"
nav = "ekonav --config benchmarks/banana.yaml"
navigator = "ekonav --config benchmarks/banana.yaml"
docs = { "shell" = "cd doc; make html" }
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6 changes: 3 additions & 3 deletions src/eko/anomalous_dimensions/__init__.py
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Expand Up @@ -23,7 +23,7 @@
from . import as1, as2, as3, harmonics


@nb.njit("Tuple((c16[:,:],c16,c16,c16[:,:],c16[:,:]))(c16[:,:])", cache=True)
@nb.njit(cache=True)
def exp_singlet(gamma_S):
r"""
Computes the exponential and the eigensystem of the singlet anomalous dimension matrix
Expand Down Expand Up @@ -71,7 +71,7 @@ def exp_singlet(gamma_S):
return exp, lambda_p, lambda_m, e_p, e_m


@nb.njit("c16[:](u1,u2,c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_ns(order, mode, n, nf):
r"""
Computes the tower of the non-singlet anomalous dimensions
Expand Down Expand Up @@ -131,7 +131,7 @@ def gamma_ns(order, mode, n, nf):
return gamma_ns


@nb.njit("c16[:,:,:](u1,c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_singlet(order, n, nf):
r"""
Computes the tower of the singlet anomalous dimensions matrices
Expand Down
8 changes: 4 additions & 4 deletions src/eko/anomalous_dimensions/aem1.py
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Expand Up @@ -5,7 +5,7 @@
from . import as1


@nb.njit("c16(c16)", cache=True)
@nb.njit(cache=True)
def gamma_phq(N):
"""
Computes the leading-order photon-quark anomalous dimension
Expand All @@ -26,7 +26,7 @@ def gamma_phq(N):
return as1.gamma_gq(N) / constants.CF


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_qph(N, nf):
"""
Computes the leading-order quark-photon anomalous dimension
Expand All @@ -50,7 +50,7 @@ def gamma_qph(N, nf):
return as1.gamma_qg(N, nf) / constants.TR * constants.NC


@nb.njit("c16(u1)", cache=True)
@nb.njit(cache=True)
def gamma_phph(nf):
"""
Computes the leading-order photon-photon anomalous dimension
Expand All @@ -71,7 +71,7 @@ def gamma_phph(nf):
return 2 / 3 * constants.NC * 2 * nf


@nb.njit("c16(c16,c16)", cache=True)
@nb.njit(cache=True)
def gamma_ns(N, s1):
"""
Computes the leading-order non-singlet QED anomalous dimension.
Expand Down
10 changes: 5 additions & 5 deletions src/eko/anomalous_dimensions/as1.py
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Expand Up @@ -7,7 +7,7 @@
from .. import constants


@nb.njit("c16(c16,c16)", cache=True)
@nb.njit(cache=True)
def gamma_ns(N, s1):
"""
Computes the leading-order non-singlet anomalous dimension.
Expand All @@ -31,7 +31,7 @@ def gamma_ns(N, s1):
return result


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_qg(N, nf):
"""
Computes the leading-order quark-gluon anomalous dimension
Expand All @@ -55,7 +55,7 @@ def gamma_qg(N, nf):
return result


@nb.njit("c16(c16)", cache=True)
@nb.njit(cache=True)
def gamma_gq(N):
"""
Computes the leading-order gluon-quark anomalous dimension
Expand All @@ -77,7 +77,7 @@ def gamma_gq(N):
return result


@nb.njit("c16(c16,c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_gg(N, s1, nf):
"""
Computes the leading-order gluon-gluon anomalous dimension
Expand All @@ -103,7 +103,7 @@ def gamma_gg(N, s1, nf):
return result


@nb.njit("c16[:,:](c16,c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_singlet(N, s1, nf):
r"""
Computes the leading-order singlet anomalous dimension matrix
Expand Down
14 changes: 7 additions & 7 deletions src/eko/anomalous_dimensions/as2.py
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Expand Up @@ -14,7 +14,7 @@
from . import harmonics


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_nsm(n, nf):
"""
Computes the |NLO| valence-like non-singlet anomalous dimension.
Expand Down Expand Up @@ -57,7 +57,7 @@ def gamma_nsm(n, nf):
return result


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_nsp(n, nf):
"""
Computes the |NLO| singlet-like non-singlet anomalous dimension.
Expand Down Expand Up @@ -98,7 +98,7 @@ def gamma_nsp(n, nf):
return result


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_ps(n, nf):
"""
Computes the |NLO| pure-singlet quark-quark anomalous dimension.
Expand All @@ -125,7 +125,7 @@ def gamma_ps(n, nf):
return result


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_qg(n, nf):
"""
Computes the |NLO| quark-gluon singlet anomalous dimension.
Expand Down Expand Up @@ -158,7 +158,7 @@ def gamma_qg(n, nf):
return result


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_gq(n, nf):
"""
Computes the |NLO| gluon-quark singlet anomalous dimension.
Expand Down Expand Up @@ -194,7 +194,7 @@ def gamma_gq(n, nf):
return result


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_gg(n, nf):
"""
Computes the |NLO| gluon-gluon singlet anomalous dimension.
Expand Down Expand Up @@ -232,7 +232,7 @@ def gamma_gg(n, nf):
return result


@nb.njit("c16[:,:](c16,u1)", cache=True)
@nb.njit(cache=True)
def gamma_singlet(N, nf):
r"""
Computes the next-leading-order singlet anomalous dimension matrix
Expand Down
16 changes: 8 additions & 8 deletions src/eko/anomalous_dimensions/as3.py
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Expand Up @@ -16,7 +16,7 @@
zeta3 = harmonics.zeta3


@nb.njit("c16(c16,u1,c16[:])", cache=True)
@nb.njit(cache=True)
def gamma_nsm(n, nf, sx):
"""
Computes the |NNLO| valence-like non-singlet anomalous dimension.
Expand Down Expand Up @@ -93,7 +93,7 @@ def gamma_nsm(n, nf, sx):
return result


@nb.njit("c16(c16,u1,c16[:])", cache=True)
@nb.njit(cache=True)
def gamma_nsp(n, nf, sx):
"""
Computes the |NNLO| singlet-like non-singlet anomalous dimension.
Expand Down Expand Up @@ -170,7 +170,7 @@ def gamma_nsp(n, nf, sx):
return result


@nb.njit("c16(c16,u1,c16[:])", cache=True)
@nb.njit(cache=True)
def gamma_nsv(n, nf, sx):
"""
Computes the |NNLO| valence non-singlet anomalous dimension.
Expand Down Expand Up @@ -225,7 +225,7 @@ def gamma_nsv(n, nf, sx):
return result


@nb.njit("c16(c16,u1,c16[:])", cache=True)
@nb.njit(cache=True)
def gamma_ps(n, nf, sx):
"""
Computes the |NNLO| pure-singlet quark-quark anomalous dimension.
Expand Down Expand Up @@ -297,7 +297,7 @@ def gamma_ps(n, nf, sx):
return result


@nb.njit("c16(c16,u1,c16[:])", cache=True)
@nb.njit(cache=True)
def gamma_qg(n, nf, sx):
"""
Computes the |NNLO| quark-gluon singlet anomalous dimension.
Expand Down Expand Up @@ -371,7 +371,7 @@ def gamma_qg(n, nf, sx):
return result


@nb.njit("c16(c16,u1,c16[:])", cache=True)
@nb.njit(cache=True)
def gamma_gq(n, nf, sx):
"""
Computes the |NNLO| gluon-quark singlet anomalous dimension.
Expand Down Expand Up @@ -461,7 +461,7 @@ def gamma_gq(n, nf, sx):
return result


@nb.njit("c16(c16,u1,c16[:])", cache=True)
@nb.njit(cache=True)
def gamma_gg(n, nf, sx):
"""
Computes the |NNLO| gluon-gluon singlet anomalous dimension.
Expand Down Expand Up @@ -549,7 +549,7 @@ def gamma_gg(n, nf, sx):
return result


@nb.njit("c16[:,:](c16,u1,c16[:])", cache=True)
@nb.njit(cache=True)
def gamma_singlet(N, nf, sx):
r"""
Computes the |NNLO| singlet anomalous dimension matrix
Expand Down
14 changes: 7 additions & 7 deletions src/eko/anomalous_dimensions/harmonics.py
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Expand Up @@ -16,7 +16,7 @@
zeta5 = scipy.special.zeta(5)


@nb.njit("c16(c16,u1)", cache=True)
@nb.njit(cache=True)
def cern_polygamma(Z, K): # pylint: disable=all
"""
Computes the polygamma functions :math:`\\psi_k(z)`.
Expand Down Expand Up @@ -133,7 +133,7 @@ def cern_polygamma(Z, K): # pylint: disable=all
# fmt: on


@nb.njit("c16(c16)", cache=True)
@nb.njit(cache=True)
def harmonic_S1(N):
r"""
Computes the harmonic sum :math:`S_1(N)`.
Expand Down Expand Up @@ -161,7 +161,7 @@ def harmonic_S1(N):
return cern_polygamma(N + 1.0, 0) + np.euler_gamma


@nb.njit("c16(c16)", cache=True)
@nb.njit(cache=True)
def harmonic_S2(N):
r"""
Computes the harmonic sum :math:`S_2(N)`.
Expand Down Expand Up @@ -189,7 +189,7 @@ def harmonic_S2(N):
return -cern_polygamma(N + 1.0, 1) + zeta2


@nb.njit("c16(c16)", cache=True)
@nb.njit(cache=True)
def harmonic_S3(N):
r"""
Computes the harmonic sum :math:`S_3(N)`.
Expand Down Expand Up @@ -217,7 +217,7 @@ def harmonic_S3(N):
return 0.5 * cern_polygamma(N + 1.0, 2) + zeta3


@nb.njit("c16(c16)", cache=True)
@nb.njit(cache=True)
def harmonic_S4(N):
r"""
Computes the harmonic sum :math:`S_4(N)`.
Expand Down Expand Up @@ -245,7 +245,7 @@ def harmonic_S4(N):
return zeta4 - 1.0 / 6.0 * cern_polygamma(N + 1.0, 3)


@nb.njit("c16(c16)", cache=True)
@nb.njit(cache=True)
def harmonic_S5(N):
r"""
Computes the harmonic sum :math:`S_5(N)`.
Expand Down Expand Up @@ -273,7 +273,7 @@ def harmonic_S5(N):
return zeta5 + 1.0 / 24.0 * cern_polygamma(N + 1.0, 4)


@nb.njit("c16(c16)", cache=True)
@nb.njit(cache=True)
def mellin_g3(N):
r"""
Computes the Mellin transform of :math:`\text{Li}_2(x)/(1+x)`.
Expand Down
12 changes: 6 additions & 6 deletions src/eko/beta.py
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Expand Up @@ -11,7 +11,7 @@
from .anomalous_dimensions.harmonics import zeta3


@nb.njit("f8(u1)", cache=True)
@nb.njit(cache=True)
def beta_0(nf):
"""
Computes the first coefficient of the QCD beta function.
Expand All @@ -32,7 +32,7 @@ def beta_0(nf):
return beta_0


@nb.njit("f8(u1)", cache=True)
@nb.njit(cache=True)
def beta_1(nf):
"""
Computes the second coefficient of the QCD beta function.
Expand All @@ -57,7 +57,7 @@ def beta_1(nf):
return beta_1


@nb.njit("f8(u1)", cache=True)
@nb.njit(cache=True)
def beta_2(nf):
"""
Computes the third coefficient of the QCD beta function
Expand Down Expand Up @@ -86,7 +86,7 @@ def beta_2(nf):
return beta_2


@nb.njit("f8(u1)", cache=True)
@nb.njit(cache=True)
def beta_3(nf):
"""
Computes the fourth coefficient of the QCD beta function
Expand All @@ -113,7 +113,7 @@ def beta_3(nf):
return beta_3


@nb.njit("f8(u1,u1)", cache=True)
@nb.njit(cache=True)
def beta(k, nf):
"""
Compute value of a beta coefficients
Expand Down Expand Up @@ -144,7 +144,7 @@ def beta(k, nf):
return beta_


@nb.njit("f8(u1,u1)", cache=True)
@nb.njit(cache=True)
def b(k, nf):
"""
Compute b coefficient.
Expand Down
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