mirror of
https://igit.ific.uv.es/alramos/latticegpu.jl.git
synced 2025-05-14 11:13:42 +02:00
423 lines
14 KiB
Julia
423 lines
14 KiB
Julia
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import ..YM.flw, ..YM.force_gauge, ..YM.flw_adapt
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function flw(U, psi, int::FlowIntr{NI,T}, ns::Int64, eps, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace) where {NI,T}
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@timeit "Integrating flow equations" begin
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for i in 1:ns
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force_gauge(ymws, U, int.c0, 1, gp, lp)
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if int.add_zth
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add_zth_term(ymws::YMworkspace, U, lp)
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end
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Nablanabla!(dws.sAp, U, psi, dpar, dws, lp)
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psi .= psi + 2*int.r*eps*dws.sAp
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ymws.mom .= ymws.frc1
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U .= expm.(U, ymws.mom, 2*eps*int.r)
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for k in 1:NI
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force_gauge(ymws, U, int.c0, 1, gp, lp)
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if int.add_zth
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add_zth_term(ymws::YMworkspace, U, lp)
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end
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Nablanabla!(dws.sp, U, psi, dpar, dws, lp)
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dws.sAp .= int.e0[k].*dws.sAp .+ int.e1[k].*dws.sp
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psi .= psi + 2*eps*dws.sAp
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ymws.mom .= int.e0[k].*ymws.mom .+ int.e1[k].*ymws.frc1
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U .= expm.(U, ymws.mom, 2*eps)
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end
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end
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end
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return nothing
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end
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flw(U, psi, int::FlowIntr{NI,T}, ns::Int64, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace) where {NI,T} = flw(U, psi, int::FlowIntr{NI,T}, ns::Int64, int.eps, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace)
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"""
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function backflow(psi, U, Dt, nsave::Int64, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace)
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Performs one step back in flow time for the fermion field, according to 1302.5246. The fermion field must me that of the time-slice Dt and is flowed back to the first time-slice
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nsave is the total number of gauge fields saved in the process
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"""
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function backflow(psi, U, Dt, maxnsave::Int64, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace)
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int = wfl_rk3(Float64,0.01,1.0) # Default integrator, it has to be order 3 rk but in can be zfl
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@timeit "Backflow integration" begin
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@timeit "GPU to CPU" U0 = Array(U)
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nt,eps_all = flw_adapt(U, int, Dt, gp, lp, ymws)
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nsave = min(maxnsave,nt)
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nsave != 0 ? dsave = Int64(floor(nt/nsave)) : dsave = nt
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Usave = Vector{typeof(U0)}(undef,nsave)
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@timeit "CPU to GPU" copyto!(U,U0)
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for i in 1:(dsave*nsave)
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flw(U, int, 1, eps_all[i], gp, lp, ymws)
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(i%dsave)==0 ? Usave[Int64(i/dsave)] = Array(U) : nothing
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end
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for j in (nt%nsave):-1:1
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@timeit "CPU to GPU" copyto!(U,Usave[end])
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for k in 1:j-1
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flw(U, int, 1, eps_all[nsave*dsave + k], gp, lp, ymws)
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end
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bflw_step!(psi, U, eps_all[nsave*dsave + j], int::FlowIntr, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace)
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end
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for i in (nsave-1):-1:1
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for j in dsave:-1:1
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@timeit "CPU to GPU" copyto!(U,Usave[i])
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for k in 1:j-1
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flw(U, int, 1, eps_all[i*dsave + k], gp, lp, ymws)
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end
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bflw_step!(psi, U, eps_all[i*dsave + j], int::FlowIntr, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace)
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end
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end
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@timeit "CPU to GPU" copyto!(U,U0)
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for j in dsave:-1:1
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@timeit "CPU to GPU" copyto!(U,U0)
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for k in 1:j-1
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flw(U, int, 1, eps_all[k], gp, lp, ymws)
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end
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bflw_step!(psi, U, eps_all[j], int::FlowIntr, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace)
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end
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@timeit "CPU to GPU" copyto!(U,U0)
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end
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return nothing
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end
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"""
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function bflw_step!(U, psi, eps, int::FlowIntr, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace)
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Performs ONE backstep in psi, from t to t-\eps. U is supposed to be the one in t-\eps and is left unchanged. So far, int has to be rk4
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"""
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function bflw_step!(psi, U, eps, int::FlowIntr, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace)
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@timeit "Backflow step" begin
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V = copy(U)
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V .= U
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force_gauge(ymws, U, int.c0, 1, gp, lp)
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if int.add_zth
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add_zth_term(ymws::YMworkspace, U, lp)
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end
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ymws.mom .= ymws.frc1
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U .= expm.(U, ymws.mom, 2*eps*int.r)
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force_gauge(ymws, U, int.c0, 1, gp, lp)
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if int.add_zth
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add_zth_term(ymws::YMworkspace, U, lp)
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end
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ymws.mom .= int.e0[1].*ymws.mom .+ int.e1[1].*ymws.frc1
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U .= expm.(U, ymws.mom, 2*eps)
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Nablanabla!(dws.sp, U, 0.75*2*eps*psi, dpar, dws, lp)
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U .= V
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force_gauge(ymws, U, int.c0, 1, gp, lp)
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if int.add_zth
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add_zth_term(ymws::YMworkspace, U, lp)
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end
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U .= expm.(U, ymws.frc1, 2*eps*int.r)
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Nablanabla!(dws.sAp, U, 2*eps*dws.sp, dpar, dws, lp)
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dws.sAp .= psi + (8/9)*dws.sAp
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U .= V
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Nablanabla!(psi, U, 2*eps*(dws.sAp - (8/9)*dws.sp), dpar, dws, lp)
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psi .= (1/4)*psi + dws.sp + dws.sAp
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end
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return nothing
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end
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"""
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function Nablanabla!(so, U, si, dpar::DiracParam, dws::DiracWorkspace, lp::SpaceParm{4,6,B,D})
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Computes /`/` \\nabla^* \\nabla /`/` `si` and stores it in `si`.
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"""
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function Nablanabla!(so, U, si, dpar::DiracParam, dws::DiracWorkspace, lp::SpaceParm{4,6,B,D}) where {B,D}
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@timeit "Laplacian" begin
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CUDA.@sync begin
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CUDA.@cuda threads=lp.bsz blocks=lp.rsz krnl_Nablanabla(so, U, si, dpar.th, lp)
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end
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end
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return nothing
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end
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function krnl_Nablanabla(so, U, si, th, lp::SpaceParm{4,6,B,D}) where {B,D}
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b = Int64(CUDA.threadIdx().x); r = Int64(CUDA.blockIdx().x)
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@inbounds begin
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so[b,r] = -4*si[b,r]
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bu1, ru1 = up((b,r), 1, lp)
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bd1, rd1 = dw((b,r), 1, lp)
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bu2, ru2 = up((b,r), 2, lp)
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bd2, rd2 = dw((b,r), 2, lp)
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bu3, ru3 = up((b,r), 3, lp)
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bd3, rd3 = dw((b,r), 3, lp)
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bu4, ru4 = up((b,r), 4, lp)
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bd4, rd4 = dw((b,r), 4, lp)
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so[b,r] += 0.5*( th[1] * (U[b,1,r]*si[bu1,ru1]) +conj(th[1]) * (U[bd1,1,rd1]\si[bd1,rd1]) +
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th[2] * (U[b,2,r]*si[bu2,ru2]) +conj(th[2]) * (U[bd2,2,rd2]\si[bd2,rd2]) +
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th[3] * (U[b,3,r]*si[bu3,ru3]) +conj(th[3]) * (U[bd3,3,rd3]\si[bd3,rd3]) +
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th[4] * (U[b,4,r]*si[bu4,ru4]) +conj(th[4]) * (U[bd4,4,rd4]\si[bd4,rd4]) )
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end
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return nothing
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end
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function krnl_Nablanabla(so, U, si, th, lp::Union{SpaceParm{4,6,BC_SF_ORBI,D},SpaceParm{4,6,BC_SF_AFWB,D}}) where {D}
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b = Int64(CUDA.threadIdx().x); r = Int64(CUDA.blockIdx().x)
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@inbounds begin
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if (point_time((b,r),lp) != 1)
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so[b,r] = -4*si[b,r]
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bu1, ru1 = up((b,r), 1, lp)
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bd1, rd1 = dw((b,r), 1, lp)
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bu2, ru2 = up((b,r), 2, lp)
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bd2, rd2 = dw((b,r), 2, lp)
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bu3, ru3 = up((b,r), 3, lp)
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bd3, rd3 = dw((b,r), 3, lp)
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bu4, ru4 = up((b,r), 4, lp)
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bd4, rd4 = dw((b,r), 4, lp)
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so[b,r] += 0.5*( th[1] * (U[b,1,r]*si[bu1,ru1]) +conj(th[1]) * (U[bd1,1,rd1]\si[bd1,rd1]) +
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th[2] * (U[b,2,r]*si[bu2,ru2]) +conj(th[2]) * (U[bd2,2,rd2]\si[bd2,rd2]) +
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th[3] * (U[b,3,r]*si[bu3,ru3]) +conj(th[3]) * (U[bd3,3,rd3]\si[bd3,rd3]) +
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th[4] * (U[b,4,r]*si[bu4,ru4]) +conj(th[4]) * (U[bd4,4,rd4]\si[bd4,rd4]) )
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end
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end
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return nothing
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end
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function flw_adapt(U, psi, int::FlowIntr{NI,T}, tend::T, epsini::T, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace) where {NI,T}
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eps = epsini
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dt = tend
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nstp = 0
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eps_all = Vector{T}(undef,0)
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while true
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ns = convert(Int64, floor(dt/eps))
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if ns > 10
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flw(U, psi, int, 9, eps, gp, dpar, lp, ymws, dws)
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ymws.U1 .= U
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flw(U, psi, int, 1, eps, gp, dpar, lp, ymws, dws)
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flw(ymws.U1, int, 2, eps/2, gp, lp, ymws)
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dt = dt - 10*eps
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nstp = nstp + 10
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push!(eps_all,ntuple(i->eps,10)...)
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# adjust step size
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ymws.U1 .= ymws.U1 ./ U
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maxd = CUDA.mapreduce(dev_one, max, ymws.U1, init=zero(tend))
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eps = min(int.max_eps, 2*eps, int.sft_fac*eps*(int.tol/maxd)^(one(tend)/3))
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else
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flw(U, psi, int, ns, eps, gp, dpar, lp, ymws, dws)
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dt = dt - ns*eps
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push!(eps_all,ntuple(i->eps,ns)...)
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push!(eps_all,dt)
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flw(U, psi, int, 1, dt, gp, dpar, lp, ymws, dws)
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dt = zero(tend)
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nstp = nstp + ns + 1
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end
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if dt == zero(tend)
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break
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end
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end
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return nstp, eps_all
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end
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flw_adapt(U, psi, int::FlowIntr{NI,T}, tend::T, gp::GaugeParm, dpar::DiracParam, lp::SpaceParm, ymws::YMworkspace, dws::DiracWorkspace) where {NI,T} = flw_adapt(U, psi, int, tend, int.eps_ini, gp, dpar, lp, ymws, dws)
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export Nablanabla!, flw, backflow, flw_adapt, bflw_step!
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"""
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function Dslash_sq!(so, U, si, dpar::DiracParam, dws::DiracWorkspace, lp::SpaceParm{4,6,B,D})
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Computes /`/` //slashed{D}^2 si /`/` ans stores it in `si`.
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"""
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function Dslash_sq!(so, U, si, dpar::DiracParam, dws::DiracWorkspace, lp::SpaceParm{4,6,B,D}) where {B,D}
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@timeit "DwdagDw" begin
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@timeit "g5Dslsh" begin
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CUDA.@sync begin
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CUDA.@cuda threads=lp.bsz blocks=lp.rsz krnl_g5Dslsh!(dws.st, U, si, dpar.th, lp)
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end
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end
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if abs(dpar.csw) > 1.0E-10
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@timeit "Dw_improvement" begin
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CUDA.@sync begin
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CUDA.@cuda threads=lp.bsz blocks=lp.rsz krnl_g5Dslsh_impr!(dws.st, dws.csw, dpar.csw, si, lp)
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end
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end
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end
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@timeit "g5Dslsh" begin
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CUDA.@sync begin
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CUDA.@cuda threads=lp.bsz blocks=lp.rsz krnl_g5Dslsh!(so, U, dws.st, dpar.th, lp)
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end
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end
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if abs(dpar.csw) > 1.0E-10
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@timeit "Dw_improvement" begin
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CUDA.@sync begin
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CUDA.@cuda threads=lp.bsz blocks=lp.rsz krnl_g5Dslsh_impr!(so, dws.csw, dpar.csw, dws.st, lp)
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end
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end
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end
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end
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return nothing
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end
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function krnl_g5Dslsh!(so, U, si, th, lp::Union{SpaceParm{4,6,BC_SF_ORBI,D},SpaceParm{4,6,BC_SF_AFWB,D}}) where {D}
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b = Int64(CUDA.threadIdx().x); r = Int64(CUDA.blockIdx().x)
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if (point_time((b,r),lp) != 1)
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@inbounds begin
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so[b,r] = 4*si[b,r]
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bu1, ru1 = up((b,r), 1, lp)
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bd1, rd1 = dw((b,r), 1, lp)
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bu2, ru2 = up((b,r), 2, lp)
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bd2, rd2 = dw((b,r), 2, lp)
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bu3, ru3 = up((b,r), 3, lp)
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bd3, rd3 = dw((b,r), 3, lp)
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bu4, ru4 = up((b,r), 4, lp)
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bd4, rd4 = dw((b,r), 4, lp)
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so[b,r] -= 0.5*(th[1]*gpmul(Pgamma{1,-1},U[b,1,r],si[bu1,ru1]) +conj(th[1])*gdagpmul(Pgamma{1,+1},U[bd1,1,rd1],si[bd1,rd1]) +
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th[2]*gpmul(Pgamma{2,-1},U[b,2,r],si[bu2,ru2]) +conj(th[2])*gdagpmul(Pgamma{2,+1},U[bd2,2,rd2],si[bd2,rd2]) +
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th[3]*gpmul(Pgamma{3,-1},U[b,3,r],si[bu3,ru3]) +conj(th[3])*gdagpmul(Pgamma{3,+1},U[bd3,3,rd3],si[bd3,rd3]) +
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th[4]*gpmul(Pgamma{4,-1},U[b,4,r],si[bu4,ru4]) +conj(th[4])*gdagpmul(Pgamma{4,+1},U[bd4,4,rd4],si[bd4,rd4]) )
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so[b,r] = dmul(Gamma{5}, so[b,r])
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end
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end
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return nothing
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end
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function krnl_g5Dslsh!(so, U, si, th, lp::SpaceParm{4,6,B,D}) where {D,B}
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b = Int64(CUDA.threadIdx().x); r = Int64(CUDA.blockIdx().x)
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@inbounds begin
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so[b,r] = 4*si[b,r]
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bu1, ru1 = up((b,r), 1, lp)
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bd1, rd1 = dw((b,r), 1, lp)
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bu2, ru2 = up((b,r), 2, lp)
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bd2, rd2 = dw((b,r), 2, lp)
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bu3, ru3 = up((b,r), 3, lp)
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bd3, rd3 = dw((b,r), 3, lp)
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bu4, ru4 = up((b,r), 4, lp)
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bd4, rd4 = dw((b,r), 4, lp)
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so[b,r] -= 0.5*(th[1]*gpmul(Pgamma{1,-1},U[b,1,r],si[bu1,ru1]) +conj(th[1])*gdagpmul(Pgamma{1,+1},U[bd1,1,rd1],si[bd1,rd1]) +
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th[2]*gpmul(Pgamma{2,-1},U[b,2,r],si[bu2,ru2]) +conj(th[2])*gdagpmul(Pgamma{2,+1},U[bd2,2,rd2],si[bd2,rd2]) +
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th[3]*gpmul(Pgamma{3,-1},U[b,3,r],si[bu3,ru3]) +conj(th[3])*gdagpmul(Pgamma{3,+1},U[bd3,3,rd3],si[bd3,rd3]) +
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th[4]*gpmul(Pgamma{4,-1},U[b,4,r],si[bu4,ru4]) +conj(th[4])*gdagpmul(Pgamma{4,+1},U[bd4,4,rd4],si[bd4,rd4]) )
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so[b,r] = dmul(Gamma{5}, so[b,r])
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end
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return nothing
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end
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function krnl_g5Dslsh_impr!(so, Fcsw, csw, si, lp::SpaceParm{4,6,B,D}) where {B,D}
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@inbounds begin
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b = Int64(CUDA.threadIdx().x);
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r = Int64(CUDA.blockIdx().x)
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so[b,r] += 0.5*csw*im*dmul(Gamma{5},( Fcsw[b,1,r]*dmul(Gamma{10},si[b,r]) + Fcsw[b,2,r]*dmul(Gamma{11},si[b,r]) + Fcsw[b,3,r]*dmul(Gamma{12},si[b,r])
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-Fcsw[b,4,r]*dmul(Gamma{15},si[b,r]) - Fcsw[b,5,r]*dmul(Gamma{14},si[b,r]) - Fcsw[b,6,r]*dmul(Gamma{13},si[b,r])))
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end
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return nothing
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end
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function krnl_g5Dslsh_impr!(so, Fcsw, csw, si, lp::Union{SpaceParm{4,6,BC_SF_ORBI,D},SpaceParm{4,6,BC_SF_AFWB,D}}) where {D}
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@inbounds begin
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b = Int64(CUDA.threadIdx().x);
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r = Int64(CUDA.blockIdx().x)
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if (point_time((b,r),lp) != 1)
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so[b,r] += 0.5*csw*im*dmul(Gamma{5},( Fcsw[b,1,r]*dmul(Gamma{10},si[b,r]) + Fcsw[b,2,r]*dmul(Gamma{11},si[b,r]) + Fcsw[b,3,r]*dmul(Gamma{12},si[b,r])
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-Fcsw[b,4,r]*dmul(Gamma{15},si[b,r]) - Fcsw[b,5,r]*dmul(Gamma{14},si[b,r]) - Fcsw[b,6,r]*dmul(Gamma{13},si[b,r])))
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end
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return nothing
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end
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end
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