def run(job_tag, traj):
q.qmkdir_info(f"locks")
q.qmkdir_info(get_save_path(f""))
q.qmkdir_info(get_save_path(f"eig"))
q.qmkdir_info(get_save_path(f"eig/{job_tag}"))
q.qmkdir_info(get_save_path(f"configs"))
q.qmkdir_info(get_save_path(f"configs/{job_tag}"))
#
total_site = ru.get_total_site(job_tag)
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
#
path_gf = get_load_path(f"configs/{job_tag}/ckpoint_lat.{traj}")
if path_gf is None:
gf = mk_sample_gauge_field(job_tag, traj)
gf.show_info()
gf.save(get_save_path(f"configs/{job_tag}/ckpoint_lat.{traj}"))
else:
gf = q.GaugeField()
gf.load(path_gf)
#
if q.obtain_lock(f"locks/{job_tag}-{traj}-compute-eig"):
get_eig = compute_eig(gf,
job_tag,
inv_type=0,
path=f"eig/{job_tag}/traj={traj}")
test_eig(gf, get_eig(), job_tag, inv_type=0)
q.release_lock()
def test_hmc(total_site, ga):
#
q.qmkdir_info("results")
q.qmkdir_info("results/gf_info")
q.qmkdir_info("results/wilson_flow_energy_info")
q.qmkdir_info("results/gm_force_info")
#
geo = q.Geometry(total_site, 1)
rs = q.RngState("test_hmc-{}x{}x{}x{}".format(total_site[0], total_site[1],
total_site[2],
total_site[3]))
gf = q.GaugeField(geo)
q.set_unit(gf)
traj = 0
for i in range(4):
traj += 1
run_hmc(gf, ga, traj, rs.split("hmc-{}".format(traj)))
plaq_avg = q.gf_avg_plaq(gf)
plaq_sum = np.prod(total_site) * 6.0 * (1.0 - plaq_avg)
q.displayln_info("test_hmc: traj={} ; plaq_avg={}".format(
traj, plaq_avg))
if traj % 2 == 0:
q.display_gauge_field_info_table_with_wilson_flow(
"results/gf_info/traj={}.lat".format(traj),
"results/wilson_flow_energy_info/traj={}.lat".format(traj), gf,
0.1, 5, 2)
q.save_gm_force_magnitudes_list(
"results/gm_force_info/traj={}.lat".format(traj))
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 test_src(xg):
q.displayln_info(f"test_src: xg={xg}")
#
src_q = q.mk_point_src(geo, xg)
#
grid = qg.mk_grid(geo)
g_src_gpt = g.mspincolor(grid)
g.create.point(g_src_gpt, xg)
src_g = qg.qlat_from_gpt(g_src_gpt)
#
src_diff = src_q.copy()
src_diff -= src_g
#
q.displayln_info(src_q.qnorm(), src_g.qnorm(), src_diff.qnorm())
assert src_diff.qnorm() == 0
def gm_evolve_fg(gm, gf_init, ga, fg_dt, dt):
geo = gf_init.geo()
gf = q.GaugeField(geo)
gf @= gf_init
#
gm_force = q.GaugeMomentum(geo)
#
q.set_gm_force(gm_force, gf, ga)
#
q.gf_evolve(gf, gm_force, fg_dt)
#
q.set_gm_force(gm_force, gf, ga)
#
q.display_gm_force_magnitudes(gm_force, 5)
q.displayln_info(q.get_gm_force_magnitudes(gm_force, 5))
#
gm_force *= dt
gm += gm_force
def metropolis_accept(delta_h, traj, rs):
flag_d = 0.0
accept_prob = 0.0
if q.get_id_node() == 0:
if delta_h <= 0.0:
accept_prob = 1.0
flag_d = 1.0
else:
accept_prob = m.exp(-delta_h)
rand_num = rs.u_rand_gen(1.0, 0.0)
if rand_num <= accept_prob:
flag_d = 1.0
flag_d = q.glb_sum(flag_d)
accept_prob = q.glb_sum(accept_prob)
flag = flag_d > 0.5
q.displayln_info(
"metropolis_accept: flag={:d} with accept_prob={:.1f}% delta_h={:.16f} traj={:d}"
.format(flag, accept_prob * 100.0, delta_h, traj))
return flag, accept_prob
def run_hmc(gf, ga, traj, rs):
#
is_reverse_test = traj < 3
#
geo = gf.geo()
gf0 = q.GaugeField(geo)
gf0 @= gf
#
gm = q.GaugeMomentum(geo)
q.set_rand_gauge_momentum(gm, 1.0, rs.split("set_rand_gauge_momentum"))
#
steps = 6
md_time = 1.0
#
delta_h = run_hmc_evolve(gm, gf0, ga, rs, steps, md_time)
#
if is_reverse_test:
gm_r = q.GaugeMomentum(geo)
gm_r @= gm
gf0_r = q.GaugeField(geo)
gf0_r @= gf0
delta_h_rev = run_hmc_evolve(gm_r, gf0_r, ga, rs, steps, -md_time)
gf0_r -= gf
q.displayln_info("run_hmc_evolve reversed delta_diff: {} / {}".format(
delta_h + delta_h_rev, delta_h))
q.displayln_info("run_hmc_evolve reversed gf_diff: {} / {}".format(
q.qnorm(gf0_r), q.qnorm(gf0)))
#
flag, accept_prob = metropolis_accept(delta_h, traj,
rs.split("metropolis_accept"))
#
if flag or traj <= 20:
q.displayln_info("run_hmc: update gf (traj={:d})".format(traj))
gf @= gf0
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_inv(geo, inverter):
src = mk_src(geo)
q.displayln_info(f"src info {src.qnorm()} {src.crc32()}")
sol = inverter * src
q.displayln_info(f"sol info {sol.qnorm()} {sol.crc32()}")
sol1 = inverter * sol
q.displayln_info(f"sol1 info {sol1.qnorm()} {sol1.crc32()}")
return src, sol, sol1
def mk_qlat_gpt_copy_plan(ctype, total_site, multiplicity, tag):
geo = q.Geometry(total_site, multiplicity)
f_gpt = mk_gpt_field(ctype, geo)
f_qlat = q.Field(ctype, geo)
lexicographic_coordinates = g.coordinates(f_gpt)
buf = f_qlat.mview()
if tag == "qlat_from_gpt":
qlat_from_gpt = g.copy_plan(buf, f_gpt)
qlat_from_gpt.destination += g.global_memory_view(
f_gpt.grid, [[f_gpt.grid.processor, buf, 0, buf.nbytes]])
qlat_from_gpt.source += f_gpt.view[lexicographic_coordinates]
qlat_from_gpt = qlat_from_gpt(local_only=True)
return qlat_from_gpt
elif tag == "gpt_from_qlat":
gpt_from_qlat = g.copy_plan(f_gpt, buf)
gpt_from_qlat.source += g.global_memory_view(
f_gpt.grid, [[f_gpt.grid.processor, buf, 0, buf.nbytes]])
gpt_from_qlat.destination += f_gpt.view[lexicographic_coordinates]
gpt_from_qlat = gpt_from_qlat(local_only=True)
return gpt_from_qlat
else:
q.displayln_info(tag)
raise Exception("mk_qlat_gpt_copy_plan")
def test_eig(gf, eig, job_tag, inv_type):
geo = gf.geo()
src = q.FermionField4d(geo)
q.displayln_info(f"src norm {src.qnorm()}")
src.set_rand(q.RngState("test_eig:{id(inv)}"))
sol_ref = ru.get_inv(
gf, job_tag, inv_type, inv_acc=2, eig=eig, eps=1e-10,
timer=False) * src
q.displayln_info(f"sol_ref norm {sol_ref.qnorm()} with eig")
for inv_acc in [0, 1, 2]:
sol = ru.get_inv(gf, job_tag, inv_type, inv_acc, eig=eig,
timer=False) * src
sol -= sol_ref
q.displayln_info(
f"sol diff norm {sol.qnorm()} inv_acc={inv_acc} with eig")
sol = ru.get_inv(gf, job_tag, inv_type, inv_acc, timer=False) * src
sol -= sol_ref
q.displayln_info(
f"sol diff norm {sol.qnorm()} inv_acc={inv_acc} without eig")
#!/usr/bin/env python3
import sys
import qlat as q
size_node_list = [[1, 1, 1, 1], [1, 1, 1, 2], [1, 1, 1, 4], [1, 1, 1, 8],
[2, 2, 2, 2], [2, 2, 2, 4]]
q.begin(sys.argv, size_node_list)
q.qremove_all_info("results")
q.qmkdir_info("results")
total_site = [4, 4, 4, 8]
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
rs = q.RngState("seed")
gf = q.GaugeField(geo)
q.displayln_info(gf.geo().show_all())
q.set_unit(gf)
q.gf_show_info(gf)
gf.set_rand(rs.split("gf-init"), 0.3, 1)
gf.show_info()
plaq = gf.plaq()
g.create.point(g_src_gpt, xg)
src_g = qg.qlat_from_gpt(g_src_gpt)
#
src_diff = src_q.copy()
src_diff -= src_g
#
q.displayln_info(src_q.qnorm(), src_g.qnorm(), src_diff.qnorm())
assert src_diff.qnorm() == 0
qg.begin_with_gpt()
rs = q.RngState("seed")
total_site = [4, 4, 4, 8]
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
gf = q.GaugeField(geo)
gf.set_rand(rs, 0.2, 2)
gf.show_info()
test_gf(gf)
for i in range(16):
xg = [
rs.rand_gen() % total_site[0],
rs.rand_gen() % total_site[1],
rs.rand_gen() % total_site[2],
rs.rand_gen() % total_site[3]
]
test_src(xg)
#!/usr/bin/env python3
import qlat_gpt as qg
import qlat as q
import gpt as g
qg.begin_with_gpt()
q.qremove_all_info("results")
q.qmkdir_info("results")
total_site = [4, 4, 4, 8]
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
rs = q.RngState("seed")
gf = q.GaugeField(geo)
gf.set_unit()
gf.show_info()
mass = 0.05
m5 = 1.0
qinv = q.InverterDwfFreeField(mass=mass,
m5=m5,
timer=q.Timer("py:InverterDwfFreeField"))
mobius_params = {
"mass": mass,
"M5": m5,
"b": 1.0,
#!/usr/bin/env python3
import qlat as q
import sys, os
q.begin()
q.qremove_all_info("results")
q.qmkdir_info("results")
rs = q.RngState("seed")
total_site = [4, 4, 4, 8]
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
psel = q.PointSelection([[0,0,0,0], [0,1,2,0]])
psel.save("results/psel.txt")
psel = q.PointSelection()
psel.load("results/psel.txt")
q.displayln_info("psel.list() =", psel.list())
n_per_tslice = 16
fsel = q.FieldSelection(geo.total_site(), n_per_tslice, rs)
q.displayln_info("fsel info =", fsel.geo().show(), fsel.n_per_tslice(), fsel.prob())
fsel.save("results/fsel.field")
#!/usr/bin/env python3
import qlat_gpt as qg
import qlat as q
import gpt as g
qg.begin_with_gpt()
q.qremove_all_info("results")
q.qmkdir_info("results")
total_site = [4, 4, 4, 8]
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
rs = q.RngState("seed")
grid = qg.mk_grid(geo)
rng = g.random("test")
gpt_gf = g.qcd.gauge.random(grid, rng, scale=0.5)
q.displayln_info(
f"g.qcd.gauge.plaquette = {g.qcd.gauge.plaquette(gpt_gf):.17f}")
gpt_gf_f = g.convert(gpt_gf, g.single)
q.displayln_info(
f"g.qcd.gauge.plaquette = {g.qcd.gauge.plaquette(gpt_gf_f):.17f} single precision"
)
gf = qg.qlat_from_gpt(gpt_gf)
import qlat as q
import qlat_gpt as qg
import rbc_ukqcd as ru
qg.begin_with_gpt()
job_tag = "test-8nt16"
traj = 1000
q.qremove_all_info("results")
q.qmkdir_info("results")
total_site = ru.get_total_site(job_tag)
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
rs = q.RngState(f"seed-{job_tag}-{traj}")
gf = q.GaugeField(geo)
gf.set_rand(rs.split("gf-init"), 0.05, 2)
gf.show_info()
inv_type = 1
inv_acc = 0
inv = ru.mk_inverter(gf,
job_tag,
inv_type,
inv_acc,
n_grouped=q.get_num_node())
#!/usr/bin/env python3
import qlat_gpt as qg
import qlat as q
import gpt as g
qg.begin_with_gpt()
q.qremove_all_info("results")
q.qmkdir_info("results")
rs = q.RngState("seed")
geo = q.Geometry([4, 4, 4, 8], 1)
q.displayln_info("geo.show() =", geo.show())
gf = q.GaugeField(geo)
gf.set_rand(rs.split("gf-init"), 0.05, 2)
gf.show_info()
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)
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
#!/usr/bin/env python3
import qlat as q
import os
q.begin()
q.qremove_all_info("results")
q.qmkdir_info("results")
total_site = [4, 4, 4, 8]
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
rs = q.RngState("seed")
prop = q.Prop(geo)
prop.set_rand(rs.split("prop-1"))
q.displayln_info(
f"prop.crc32() = {prop.crc32()} ; prop.qnorm() = {prop.qnorm()}")
prop.save("results/prop.field")
prop = q.Prop()
prop.load("results/prop.field")
q.displayln_info(
f"prop.crc32() = {prop.crc32()} ; prop.qnorm() = {prop.qnorm()}")
prop.save_double("results/prop-double.field")
prop = q.Prop()
prop.load_double("results/prop-double.field")
#!/usr/bin/env python3
import qlat as q
import os
q.begin()
q.qremove_all_info("results")
q.qmkdir_info("results")
rs = q.RngState("seed")
total_site = [4, 4, 4, 8]
geo = q.Geometry(total_site, 1)
q.displayln_info("geo.show() =", geo.show())
psel = q.PointSelection([[0, 0, 0, 0], [0, 1, 2, 0]])
n_per_tslice = 16
fsel = q.FieldSelection(geo.total_site(), n_per_tslice, rs.split("fsel"))
fselc = fsel.copy()
fselc.add_psel(psel)
prop = q.Prop(geo)
prop.set_rand(rs.split("prop-1"))
q.displayln_info("prop", prop.crc32(), prop.qnorm())
sfw = q.open_fields("results/prop.fields", "w", [1, 1, 1, 8])
q.displayln_info("sfw.new_size_node()", sfw.new_size_node())
prop.save_double(sfw, "prop.d")