Add OPF benchmark

Author: blegat

perf/opf/Project.toml

@@ -0,0 +1,6 @@
+[deps]
+BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
+Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
+JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
+MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
+PowerModels = "c36e90e8-916a-50a6-bd94-075b64ef4655"

perf/opf/opf.jl

@@ -0,0 +1,30 @@
+ROSETTA_OPF_DIR = "/home/blegat/git/rosetta-opf"
+include(joinpath(ROSETTA_OPF_DIR, "jump.jl"))
+model = opf_model(parse_data(joinpath(ROSETTA_OPF_DIR, "data/opf_warmup.m")))
+import MathOptInterface as MOI
+JuMP.optimize!(model)
+ipopt = JuMP.unsafe_backend(model)
+ipopt.nlp_model
+ad = ipopt.nlp_data.evaluator
+x = ipopt.inner.x
+g = zeros(length(ipopt.nlp_data.constraint_bounds))
+bench0(ad, x, g)
+bench1(ad, x, g)
+bench2(ad, x, g)
+
+function bench0(ad, x, y)
+    @time MOI.eval_constraint(ad, g, x)
+end
+
+function bench1(ad, x, y)
+    J = @time MOI.jacobian_structure(ad)
+    V = zeros(length(J))
+    @time MOI.eval_constraint_jacobian(ad, V, x)
+end
+
+function bench2(ad, x, y)
+    J = @time MOI.hessian_lagrangian_structure(ad)
+    V = zeros(length(J))
+    σ = 1.0
+    @time MOI.eval_hessian_lagrangian(ad, V, x, σ, y)
+end