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runbench.jl
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runbench.jl
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using SparseArrays
using LinearAlgebra
using Random
using GLPK
using MathOptInterface
# using ProfileView
const MOI = MathOptInterface
using TimerOutputs
struct RandomLP
rows::Int
cols::Int
dens::Float64
end
function generate_moi_problem(model, At, b, c;
var_bounds = true, scalar = true)
cols, rows = size(At)
x = MOI.add_variables(model, cols)
A_cols = rowvals(At)
A_vals = nonzeros(At)
if var_bounds
for col in 1:cols
MOI.add_constraint(model, MOI.SingleVariable(x[col]),
MOI.LessThan(10.0))
MOI.add_constraint(model, MOI.SingleVariable(x[col]),
MOI.GreaterThan(-10.0))
end
end
if scalar
for row in 1:rows
MOI.add_constraint(model, MOI.ScalarAffineFunction(
[MOI.ScalarAffineTerm(A_vals[i], x[A_cols[i]]) for i in nzrange(At, row)], 0.0),
MOI.LessThan(b[row]))
end
else
for row in 1:rows
MOI.add_constraint(model, MOI.VectorAffineFunction(
[MOI.VectorAffineTerm(1,
MOI.ScalarAffineTerm(A_vals[i], x[A_cols[i]])
) for i in nzrange(At, row)], [-b[row]]),
MOI.Nonpositives(1))
end
end
objective = MOI.ScalarAffineFunction(
[MOI.ScalarAffineTerm(c[i], x[i]) for i in findall(!iszero, c)],
0.0)
MOI.set(model, MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}(), objective)
MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
return x
end
function random_data(seed, data)
rows = data.rows
cols = data.cols
density = data.dens
p_neg_element = 0.0 # 0.25
rng = Random.MersenneTwister(seed)
f_A(r, n) = ifelse.(rand(r, n) .> p_neg_element, 1, -1) .* (15 .+ 30 .* rand(r, n))
At = sprand(rng, cols, rows, density, f_A)
b = 50 * rand(rng, rows)
# not using signs now
sign = ifelse.(rand(rng, rows) .> 0.2, 'L', 'G')
f_c(r, n) = 20 .* 2 .* (rand(r, n) .- 0.5)
c = sprand(rng, cols, 0.5, f_c)
return At, b, c
end
function bridged_cache_and_solver()
model = MOI.Bridges.full_bridge_optimizer(MOI.Utilities.CachingOptimizer(
MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}()),
MOI.Utilities.MANUAL), Float64)
GLPK_ = GLPK.Optimizer()
MOI.set(GLPK_, MOI.Silent(), true)
return model, GLPK_
end
function cache_and_solver()
model = MOI.Utilities.CachingOptimizer(
MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}()),
MOI.Utilities.MANUAL)
GLPK_ = GLPK.Optimizer()
MOI.set(GLPK_, MOI.Silent(), true)
return model, GLPK_
end
function bridged_cached_solver()
model = MOI.Bridges.full_bridge_optimizer(MOI.Utilities.CachingOptimizer(
MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}()),
GLPK.Optimizer()), Float64)
MOI.set(model, MOI.Silent(), true)
return model
end
function cached_solver()
model = MOI.Utilities.CachingOptimizer(
MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}()),
GLPK.Optimizer())
MOI.set(model, MOI.Silent(), true)
return model
end
function time_build_and_solve(to_build, to_solve, At, b, c, scalar = true)
@timeit "build" x = generate_moi_problem(to_build, At, b, c, scalar = scalar)
if to_build !== to_solve
@timeit "copy" MOI.copy_to(to_solve, to_build, copy_names = false)
end
MOI.set(to_solve, MOI.TimeLimitSec(), 0.0010)
@time @timeit "opt" MOI.optimize!(to_solve)
val = MOI.get(to_solve, MOI.SolveTime())
println(val)
@show MOI.get(to_solve, MOI.ObjectiveValue())
@show MOI.get(to_solve, MOI.TerminationStatus())
end
function solve_GLPK(seed, data; time_limit_sec=Inf)
reset_timer!()
@timeit "data" At, b, c = random_data(1, data)
for i in 1:seed
# mod(i,5) == 0 && GC.gc()
GC.gc()
bridged_cache, pure_solver = bridged_cache_and_solver()
@timeit "bc + s" time_build_and_solve(bridged_cache, pure_solver, At, b, c)
GC.gc()
cache, pure_solver2 = cache_and_solver()
@timeit "c + s" time_build_and_solve(cache, pure_solver2, At, b, c)
GC.gc()
full_solver = bridged_cached_solver()
@timeit "bcs" time_build_and_solve(full_solver, full_solver, At, b, c)
GC.gc()
full_solver = bridged_cached_solver()
@timeit "bcs + v" time_build_and_solve(full_solver, full_solver, At, b, c, false)
GC.gc()
cache_solver = cached_solver()
@timeit "cs" time_build_and_solve(cache_solver, cache_solver, At, b, c)
end
print_timer()
end
solve_GLPK(2, RandomLP(11, 11, 0.5); time_limit_sec=5)
solve_GLPK(20, RandomLP(10000, 10000, 0.005); time_limit_sec=5)