benchmark added

.gitignore

@@ -21,5 +21,25 @@ docs/site/
 # It records a fixed state of all packages used by the project. As such, it should not be
 # committed for packages, but should be committed for applications that require a static
 # environment.
-Manifest.toml
+/Manifest.toml
+docs/Manifest.toml
 
+# data files
+pglib*.m
+
+# ampl nl files
+*.nl
+
+## Core latex/pdflatex auxiliary files:
+*.aux
+*.lof
+*.log
+*.lot
+*.fls
+*.out
+*.toc
+*.fmt
+*.fot
+*.cb
+*.cb2
+.*.lb

ExaModelsExamples/Project.toml

@@ -7,10 +7,13 @@ version = "0.1.0"
 AmplNLReader = "77dd3d4c-cb1d-5e09-9340-85030ff7ba66"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 CPUTime = "a9c8d775-2e2e-55fc-8582-045d282d599e"
+Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
 ExaModels = "1037b233-b668-4ce9-9b63-f9f681f55dd2"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 MadNLP = "2621e9c9-9eb4-46b1-8089-e8c72242dfb6"
+NLPModelsIpopt = "f4238b75-b362-5c4c-b852-0801c9a21d71"
 NLPModelsJuMP = "792afdf1-32c1-5681-94e0-d7bf7a5df49e"
 PowerModels = "c36e90e8-916a-50a6-bd94-075b64ef4655"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
+SnoopPrecompile = "66db9d55-30c0-4569-8b51-7e840670fc0c"

ExaModelsExamples/src/ExaModelsExamples.jl

@@ -7,100 +7,41 @@ import PyCall: @py_str
 import MadNLP
 import AmplNLReader
 import CPUTime: @CPUtime
-
-silence()
+import SnoopPrecompile
+import NLPModelsIpopt: ipopt
+import Downloads
+import Printf: @printf
 
 include("opf.jl")
 include("luksanvlcek.jl")
 include("distillation.jl")
 include("quadrotor.jl")
+include("extras.jl")
 
-function project!(l,x,u; marg = 1e-4)
-    map!(x,l,x,u) do l,x,u
-        max(l+marg, min(u-marg,x) )
-    end
+const NAMES = filter(names(ExaModelsExamples; all=true)) do x
+    str = string(x)
+    endswith(str, "model") && !startswith(str, "#")
 end
 
-function compile_callbacks(m)
-    nvar = m.meta.nvar
-    ncon = m.meta.ncon
-    nnzj = m.meta.nnzj
-    nnzh = m.meta.nnzh
-
-    x = similar(m.meta.x0, nvar)
-    y = similar(m.meta.x0, ncon)
-    c = similar(m.meta.x0, ncon)
-    g = similar(m.meta.x0, nvar)
-    jac = similar(m.meta.x0, nnzj)
-    hess = similar(m.meta.x0, nnzh)
-    jrows = similar(m.meta.x0, Int, nnzj)
-    jcols = similar(m.meta.x0, Int, nnzj)
-    hrows = similar(m.meta.x0, Int, nnzh)
-    hcols = similar(m.meta.x0, Int, nnzh)
+export ipopt # rexport
 
-    project!(m.meta.lvar, x, m.meta.uvar)
-
-    # println("Objective evaluation")
-    tobj = @elapsed for t=1:100
-        NLPModels.obj(m,x)
-    end
-    # println("Constraints evaluation")
-    tcon = @elapsed for t=1:100
-        NLPModels.cons!(m,x,c)
-    end
-    # println("Gradient evaluation")
-    tgrad = @elapsed for t=1:100
-        NLPModels.grad!(m,x,g)
-    end
-    # println("Jacobian evaluation")
-    tjac = @elapsed for t=1:100
-        NLPModels.jac_coord!(m,x,jac)
-    end
-    # println("Hessian evaluation")
-    thess = @elapsed for t=1:100
-        NLPModels.hess_coord!(m,x,y,hess)
-    end
-    # println("Jacobina sparsity evaluation")
-    tjacs = @elapsed for t=1:100
-        NLPModels.jac_structure!(m,jrows,jcols)
-    end
-    # println("Hessian sparsity evaluation")
-    thesss = @elapsed for t=1:100
-        NLPModels.hess_structure!(m,hrows,hcols)
-    end
-
-    return (
-        tobj = tobj,
-        tcon = tcon,
-        tgrad = tgrad,
-        tjac = tjac,
-        thess = thess,
-        tjacs = tjacs,
-        thesss = thesss,
-    )
+for name in NAMES
+    @eval export $name
 end
 
+function __init__()
+    silence()
+end
 
-function parse_log(file)
-    open(file) do f
-        t1=nothing
-        t2=nothing
-        while !eof(f)
-            s = readline(f)
-            if occursin("Total CPU secs in NLP function evaluations", s)
-                t1 = parse(Float64,split(s, "=")[2])
-            elseif occursin("Total CPU secs in IPOPT (w/o function evaluations)", s)
-                t2 = parse(Float64,split(s, "=")[2])
-            end
+function __compile__()
+    for name in NAMES
+        @eval begin
+            m = $name()
+            ipopt(m; print_level=0)
         end
-        return t1,t2
     end
 end
 
-for name in filter(names(ExaModelsExamples; all=true)) do x
-    endswith(string(x), "model")
-end
-    @eval export $name
-end 
+# SnoopPrecompile.@precompile_all_calls _compile()
 
 end # module ExaModelsExamples

ExaModelsExamples/src/distillation.jl

@@ -1,4 +1,4 @@
-function distillation_column_model(T, backend = nothing)
+function distillation_column_model(T = 3, backend = nothing)
 
     NT = 30
     FT = 17
@@ -60,10 +60,12 @@ function distillation_column_model(T, backend = nothing)
     ExaModels.constraint(c, L2[t]- u[t] * D - F for t in 0:T)
     ExaModels.constraint(c, yA[t,i] * (1-xA[t,i]) - alpha * xA[t,i] * (1-yA[t,i]) for (t,i) in itr2)
 
-    return ExaModels.ExaModel(c)
+    return ADBenchmarkModel(
+        ExaModels.ExaModel(c)
+    )
 end
 
-function jump_distillation_column_model(T)
+function jump_distillation_column_model(T = 3)
 
     NT = 30
     FT = 17
@@ -126,10 +128,12 @@ function jump_distillation_column_model(T)
         yA[t,i] * (1-xA[t,i]) - alpha * xA[t,i] * (1-yA[t,i]) == 0
     )
 
-    return MathOptNLPModel(m)
+    return ADBenchmarkModel(
+        MathOptNLPModel(m)
+    )
 end
 
-function ampl_distillation_column_model(T)
+function ampl_distillation_column_model(T = 3)
     nlfile = tempname()*  ".nl"
 
     py"""
@@ -241,5 +245,7 @@ function ampl_distillation_column_model(T)
     m.write($nlfile)
     """
 
-    return AmplNLReader.AmplModel(nlfile)
+    return ADBenchmarkModel(
+        AmplNLReader.AmplModel(nlfile)
+    )
 end