def mk_eig(gf, job_tag, inv_type):
timer = q.Timer(f"py:mk_eig({job_tag},{inv_type})", True)
timer.start()
gpt_gf = g.convert(qg.gpt_from_qlat(gf), g.single)
parity = g.odd
params = get_lanc_params(job_tag, inv_type)
q.displayln_info(f"mk_eig: job_tag={job_tag} inv_type={inv_type}")
q.displayln_info(f"mk_eig: params={params}")
fermion_params = params["fermion_params"]
if "omega" in fermion_params:
qm = g.qcd.fermion.zmobius(gpt_gf, fermion_params)
else:
qm = g.qcd.fermion.mobius(gpt_gf, fermion_params)
w = g.qcd.fermion.preconditioner.eo2_ne(parity=parity)(qm)
def make_src(rng):
src = g.vspincolor(w.F_grid_eo)
# src[:] = g.vspincolor([[1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1]])
rng.cnormal(src)
src.checkerboard(parity)
return src
pit = g.algorithms.eigen.power_iteration(**params["pit_params"])
pit_ev, _, _ = pit(w.Mpc, make_src(g.random("lanc")))
q.displayln_info(f"mk_eig: pit_ev={pit_ev}")
#
cheby = g.algorithms.polynomial.chebyshev(params["cheby_params"])
irl = g.algorithms.eigen.irl(params["irl_params"])
evec, ev = irl(cheby(w.Mpc), make_src(g.random("lanc")))
evals = g.algorithms.eigen.evals(w.Mpc, evec, check_eps2=1e-6, real=True)
g.mem_report()
#
timer.stop()
return evec, evals
def test_gf(gf):
q.displayln_info(f"test_gf")
#
plaq = gf.plaq()
#
gpt_gf = qg.gpt_from_qlat(gf)
g_plaq = g.qcd.gauge.plaquette(gpt_gf)
#
q.displayln_info(
f"gf.plaq()={plaq} ; g.qcd.gauge.plaquette(gpt_gf) = {g_plaq:.17f}")
assert abs(plaq - g_plaq) < 1.0e-10
def mk_inverter_gpt(gf, timer):
mobius_params = {
"mass": 0.1,
"M5": 1.0,
"b": 1.0,
"c": 0.0,
"Ls": 8,
"boundary_phases": [1.0, 1.0, 1.0, 1.0],
}
gpt_gf = qg.gpt_from_qlat(gf)
qm = g.qcd.fermion.mobius(gpt_gf, mobius_params)
pc = g.qcd.fermion.preconditioner
inv = g.algorithms.inverter
cg = inv.cg({"eps": 1e-8, "maxiter": 10000})
slv_5d = inv.preconditioned(pc.eo2_ne(), cg)
slv_qm = qm.propagator(slv_5d)
inv_qm = qg.InverterGPT(inverter=slv_qm, timer=timer)
return inv_qm
m5 = 1.0
qinv = q.InverterDwfFreeField(mass=mass,
m5=m5,
timer=q.Timer("py:InverterDwfFreeField"))
mobius_params = {
"mass": mass,
"M5": m5,
"b": 1.0,
"c": 0.0,
"Ls": 32,
"boundary_phases": [1.0, 1.0, 1.0, 1.0],
}
gpt_gf = qg.gpt_from_qlat(gf)
qm = g.qcd.fermion.mobius(gpt_gf, mobius_params)
pc = g.qcd.fermion.preconditioner
inv = g.algorithms.inverter
cg = inv.cg({"eps": 1e-11, "maxiter": 10000})
slv_5d = inv.preconditioned(pc.eo2_ne(), cg)
slv_qm = qm.propagator(slv_5d)
ginv = qg.InverterGPT(inverter=slv_qm, timer=q.Timer("py:InverterGPT"))
src_p = q.mk_point_src(geo, [0, 0, 0, 0])
src_r = q.Prop(geo)
src_r.set_rand(rs.split("src_r"))
for src in [src_p, src_r]:
sol = qinv * src
def mk_gpt_inverter(gf,
job_tag,
inv_type,
inv_acc,
*,
gt=None,
mpi_split=None,
n_grouped=1,
eig=None,
eps=1e-8,
timer=True):
if mpi_split is None:
mpi_split = g.default.get_ivec("--mpi_split", None, 4)
if mpi_split is not None:
n_grouped = g.default.get_int("--grouped", 4)
gpt_gf = qg.gpt_from_qlat(gf)
pc = g.qcd.fermion.preconditioner
if inv_type in [0, 1]:
param = get_fermion_param(job_tag, inv_type, inv_acc)
if eig is not None:
# may need madwf
param0 = get_fermion_param(job_tag, inv_type, inv_acc=0)
is_madwf = get_ls_from_fermion_params(
param) != get_ls_from_fermion_params(param0)
else:
is_madwf = False
if "omega" in param:
qm = g.qcd.fermion.zmobius(gpt_gf, param)
else:
qm = g.qcd.fermion.mobius(gpt_gf, param)
inv = g.algorithms.inverter
if job_tag[:5] == "test-":
cg_mp = inv.cg({"eps": eps, "maxiter": 100})
elif inv_type == 0:
cg_mp = inv.cg({"eps": eps, "maxiter": 200})
elif inv_type == 1:
cg_mp = inv.cg({"eps": eps, "maxiter": 300})
else:
raise Exception("mk_gpt_inverter")
if mpi_split is None:
cg_split = cg_mp
else:
cg_split = inv.split(cg_mp, mpi_split=mpi_split)
if eig is not None:
cg_defl = inv.coarse_deflate(eig[1], eig[0], eig[2])
cg = inv.sequence(cg_defl, cg_split)
else:
cg = cg_split
if inv_type == 0:
slv_5d = inv.preconditioned(pc.eo2_ne(), cg)
elif inv_type == 1:
slv_5d = inv.preconditioned(pc.eo2_ne(), cg)
else:
raise Exception("mk_gpt_inverter")
if is_madwf:
gpt_gf_f = g.convert(gpt_gf, g.single)
if "omega" in param0:
qm0 = g.qcd.fermion.zmobius(gpt_gf_f, param0)
else:
qm0 = g.qcd.fermion.mobius(gpt_gf_f, param0)
cg_pv_f = inv.cg({"eps": eps, "maxiter": 90})
slv_5d_pv_f = inv.preconditioned(pc.eo2_ne(), cg_pv_f)
slv_5d = pc.mixed_dwf(slv_5d, slv_5d_pv_f, qm0)
if inv_acc == 0:
maxiter = 1
elif inv_acc == 1:
maxiter = 2
elif inv_acc == 2:
maxiter = 200
else:
raise Exception("mk_gpt_inverter")
slv_qm = qm.propagator(
inv.defect_correcting(inv.mixed_precision(slv_5d, g.single,
g.double),
eps=eps,
maxiter=maxiter)).grouped(n_grouped)
if timer is True:
timer = q.Timer(f"py:inv({job_tag},{inv_type},{inv_acc})", True)
elif timer is False:
timer = q.TimerNone()
inv_qm = qg.InverterGPT(inverter=slv_qm, timer=timer)
else:
raise Exception("mk_gpt_inverter")
if gt is None:
return inv_qm
else:
return q.InverterGaugeTransform(inverter=inv_qm, gt=gt)
def mk_ceig(gf, job_tag, inv_type):
timer = q.Timer(f"py:mk_ceig({job_tag},{inv_type})", True)
timer.start()
gpt_gf = g.convert(qg.gpt_from_qlat(gf), g.single)
parity = g.odd
params = get_lanc_params(job_tag, inv_type)
q.displayln_info(f"mk_ceig: job_tag={job_tag} inv_type={inv_type}")
q.displayln_info(f"mk_ceig: params={params}")
fermion_params = params["fermion_params"]
if "omega" in fermion_params:
qm = g.qcd.fermion.zmobius(gpt_gf, fermion_params)
else:
qm = g.qcd.fermion.mobius(gpt_gf, fermion_params)
w = g.qcd.fermion.preconditioner.eo2_ne(parity=parity)(qm)
def make_src(rng):
src = g.vspincolor(w.F_grid_eo)
# src[:] = g.vspincolor([[1, 1, 1], [1, 1, 1], [1, 1, 1], [1, 1, 1]])
rng.cnormal(src)
src.checkerboard(parity)
return src
pit = g.algorithms.eigen.power_iteration(**params["pit_params"])
pit_ev, _, _ = pit(w.Mpc, make_src(g.random("lanc")))
q.displayln_info(f"mk_ceig: pit_ev={pit_ev}")
#
cheby = g.algorithms.polynomial.chebyshev(params["cheby_params"])
irl = g.algorithms.eigen.irl(params["irl_params"])
evec, ev = irl(cheby(w.Mpc), make_src(g.random("lanc")))
evals = g.algorithms.eigen.evals(w.Mpc, evec, check_eps2=1e-6, real=True)
g.mem_report()
#
inv = g.algorithms.inverter
#
cparams = get_clanc_params(job_tag, inv_type)
q.displayln_info(f"mk_ceig: cparams={cparams}")
#
grid_coarse = g.block.grid(w.F_grid_eo,
[get_ls_from_fermion_params(fermion_params)] +
cparams["block"])
nbasis = cparams["nbasis"]
basis = evec[0:nbasis]
b = g.block.map(grid_coarse, basis)
for i in range(2):
b.orthonormalize()
del evec
gc.collect()
#
ccheby = g.algorithms.polynomial.chebyshev(cparams["cheby_params"])
cop = b.coarse_operator(ccheby(w.Mpc))
#
cstart = g.vcomplex(grid_coarse, nbasis)
cstart[:] = g.vcomplex([1] * nbasis, nbasis)
eps2 = g.norm2(cop * cstart - b.project * ccheby(w.Mpc) * b.promote *
cstart) / g.norm2(cstart)
g.message(f"Test coarse-grid promote/project cycle: {eps2}")
cirl = g.algorithms.eigen.irl(cparams["irl_params"])
cevec, cev = cirl(cop, cstart)
#
smoother = inv.cg(cparams["smoother_params"])(w.Mpc)
smoothed_evals = []
tmpf = g.lattice(basis[0])
for i, cv in enumerate(cevec):
tmpf @= smoother * b.promote * cv
smoothed_evals = smoothed_evals + g.algorithms.eigen.evals(
w.Mpc, [tmpf], check_eps2=10, real=True)
g.mem_report()
#
timer.stop()
return basis, cevec, smoothed_evals