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# using MPI | ||
using LinearAlgebra | ||
using MKL | ||
using SpinGlassEngine | ||
using SpinGlassNetworks | ||
using SpinGlassTensors | ||
#using SpinGlassExhaustive | ||
using Logging | ||
using CSV | ||
using DataFrames | ||
using Memoization | ||
using JSON3 | ||
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#= | ||
function brute_force_gpu(ig::IsingGraph; num_states::Int) | ||
brute_force(ig, :GPU, num_states=num_states) | ||
end | ||
=# | ||
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# MPI.Init() | ||
size = 1 | ||
rank = 0 | ||
# size = MPI.Comm_size(MPI.COMM_WORLD) | ||
# rank = MPI.Comm_rank(MPI.COMM_WORLD) | ||
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M, N, T = 7,7,3 | ||
INSTANCE_DIR = "$(@__DIR__)/../test/instances/pegasus_random/P8/RCO/SpinGlass/single" | ||
OUTPUT_DIR = "$(@__DIR__)/results/pegasus_random/P8/RCO/droplets/final_bench_Z_EngGauges" | ||
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if !Base.Filesystem.isdir(OUTPUT_DIR) | ||
Base.Filesystem.mkpath(OUTPUT_DIR) | ||
end | ||
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BETAS = collect(0.1:0.1:1.0) #[0.5,] | ||
LAYOUT = (EnergyGauges,) | ||
TRANSFORM = [all_lattice_transformations[4],] | ||
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GAUGE = NoUpdate | ||
STRATEGY = Zipper | ||
SPARSITY = Sparse | ||
graduate_truncation = :graduate_truncate | ||
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INDβ = [3,] | ||
MAX_STATES = [1024,] | ||
BOND_DIM = [8,] | ||
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MAX_SWEEPS = [0,] | ||
VAR_TOL = 1E-16 | ||
TOL_SVD = 1E-16 | ||
ITERS_SVD = 2 | ||
ITERS_VAR = 1 | ||
DTEMP_MULT = 2 | ||
METHOD = :psvd_sparse | ||
I = [1,] | ||
eng = [40, ] | ||
hamming_dist = 74 | ||
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disable_logging(LogLevel(1)) | ||
# BLAS.set_num_threads(1) | ||
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function pegasus_sim(inst, trans, β, Layout, bd, ms, eng, hamming_dist, mstates) | ||
δp = 0.0 | ||
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cl_h = clustered_hamiltonian( | ||
ising_graph(INSTANCE_DIR * "/" * inst), | ||
spectrum=full_spectrum, | ||
cluster_assignment_rule=pegasus_lattice((M, N, T)) | ||
) | ||
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params = MpsParameters(bd, VAR_TOL, ms, TOL_SVD, ITERS_SVD, ITERS_VAR, DTEMP_MULT, METHOD) | ||
search_params = SearchParameters(mstates, δp) | ||
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net = PEPSNetwork{SquareCrossDoubleNode{Layout}, SPARSITY}(M, N, cl_h, trans) | ||
ctr = MpsContractor{STRATEGY, GAUGE}(net, [β/6, β/3, β/2, β], graduate_truncation, params) | ||
sol1, schmidts = low_energy_spectrum(ctr, search_params, merge_branches(ctr, :nofit, SingleLayerDroplets(eng, hamming_dist, :hamming))) | ||
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sol2 = unpack_droplets(sol1, β) | ||
ig_states = decode_clustered_hamiltonian_state.(Ref(cl_h), sol2.states) | ||
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ldrop = length(sol2.states) | ||
cRAM = round(Base.summarysize(Memoization.caches) * 1E-9; sigdigits=2) | ||
clear_memoize_cache() | ||
sol1, ctr, cRAM, schmidts, ldrop, sol2, ig_states | ||
end | ||
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function run_bench(inst::String, β::Real, t, l, bd, ms, eng, hamming_dist, mstates, i) | ||
hash_name = hash(string(inst, β, t, l, bd, ms, eng, hamming_dist, mstates, i)) | ||
out_path = string(OUTPUT_DIR, "/", hash_name, ".json") | ||
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if isfile(out_path) | ||
println("Skipping for $β, $t, $l, $bd, $eng, $hamming_dist, $ms, $mstates.") | ||
else | ||
data = try | ||
tic_toc = @elapsed sol, ctr, cRAM, schmidts, ldrop, droplets, ig_states = pegasus_sim(inst, t, β, l, bd, ms, eng, hamming_dist, mstates) | ||
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data = DataFrame( | ||
:instance => inst, | ||
:β => β, | ||
:Layout => l, | ||
:transform => t, | ||
:energy => sol.energies[begin], | ||
:probabilities => sol.probabilities, | ||
:discarded_probability => sol.largest_discarded_probability, | ||
:statistic => minimum(values(ctr.statistics)), | ||
:max_states => mstates, | ||
:bond_dim => bd, | ||
:max_sweeps => ms, | ||
:eng => eng, | ||
:hamming_dist => hamming_dist, | ||
:drop_eng => [droplets.energies], | ||
:drop_states => [droplets.states], | ||
:ig_states => [ig_states], | ||
:drop_prob => [droplets.probabilities], | ||
:drop_degeneracy => [droplets.degeneracy], | ||
:drop_ldp => [droplets.largest_discarded_probability], | ||
:drop_number => ldrop, | ||
:iters_svd => ITERS_SVD, | ||
:iters_var => ITERS_VAR, | ||
:dtemp_mult => DTEMP_MULT, | ||
:var_tol => VAR_TOL, | ||
:time => tic_toc, | ||
:cRAM => cRAM, | ||
:schmidts => schmidts | ||
) | ||
catch err | ||
data = DataFrame( | ||
:instance => inst, | ||
:β => β, | ||
:Layout => l, | ||
:transform => t, | ||
:max_states => mstates, | ||
:hamming_dist => hamming_dist, | ||
:iters_svd => ITERS_SVD, | ||
:iters_var => ITERS_VAR, | ||
:dtemp_mult => DTEMP_MULT, | ||
:bond_dim => bd, | ||
:max_sweeps => ms, | ||
:var_tol => VAR_TOL, | ||
:error => err | ||
) | ||
end | ||
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json_data = JSON3.write(data) | ||
open(out_path, "w") do io | ||
print(io, json_data) | ||
end | ||
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end | ||
end | ||
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all_params = collect( | ||
Iterators.product( | ||
readdir(INSTANCE_DIR, join=false), BETAS, TRANSFORM, LAYOUT, BOND_DIM, MAX_SWEEPS, eng, hamming_dist, MAX_STATES, I) | ||
) | ||
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for i ∈ (1+rank):size:length(all_params) | ||
run_bench(all_params[i]...) | ||
GC.gc() | ||
end |
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