Use show_time for sparse AD backends #326
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
I also tested it with the example in the documentation: julia> @elapsed begin
nlp = ADNLPModel!(f, xi, lvar, uvar, [1], [1], T[1], c!, lcon, ucon; hessian_backend = ADNLPModels.EmptyADbackend, show_time=true)
end
gradient backend ADNLPModels.ForwardDiffADGradient: 2.3452e-5 seconds;
hprod backend ADNLPModels.ForwardDiffADHvprod: 0.000875063 seconds;
jprod backend ADNLPModels.ForwardDiffADJprod: 2.0362e-5 seconds;
jtprod backend ADNLPModels.ForwardDiffADJtprod: 2.1778e-5 seconds;
• Sparsity pattern detection of the Jacobian: 1.114339083 seconds.
• Coloring of the sparse Jacobian: 0.005564487 seconds.
• Allocation of the AD buffers for the sparse Jacobian: 4.063e-6 seconds.
jacobian backend ADNLPModels.SparseADJacobian: 1.120131293 seconds;
hessian backend ADNLPModels.EmptyADbackend: 6.645e-6 seconds;
ghjvprod backend ADNLPModels.ForwardDiffADGHjvprod: 3.881e-6 seconds.
1.126924784julia> @elapsed begin
Is = Vector{Int}(undef, 4 * (N - 1))
Js = Vector{Int}(undef, 4 * (N - 1))
Vs = ones(Bool, 4 * (N - 1))
for i = 1:(N - 1)
Is[((i - 1) * 4 + 1):(i * 4)] = [i; i; i; i]
Js[((i - 1) * 4 + 1):(i * 4)] = [i; i + 1; N + i; N + i + 1]
end
J = sparse(Is, Js, Vs, N - 1, n)
end
0.161432748julia> @elapsed begin
Is = Vector{Int}(undef, 4 * (N - 1))
Js = Vector{Int}(undef, 4 * (N - 1))
Vs = ones(Bool, 4 * (N - 1))
for i = 1:(N - 1)
Is[((i - 1) * 4 + 1):(i * 4)] = [i; i; i; i]
Js[((i - 1) * 4 + 1):(i * 4)] = [i; i + 1; N + i; N + i + 1]
end
J = sparse(Is, Js, Vs, N - 1, n)
jac_back = ADNLPModels.SparseADJacobian(n, f, N - 1, c!, J, show_time=true);
nlp = ADNLPModel!(f, xi, lvar, uvar, [1], [1], T[1], c!, lcon, ucon; hessian_backend = ADNLPModels.EmptyADbackend, jacobian_backend = jac_back);
end
• Coloring of the sparse Jacobian: 0.005673536 seconds.
• Allocation of the AD buffers for the sparse Jacobian: 3.4547e-5 seconds.
0.191296527 |
|
|
@amontoison do you mean that it shows how much time is spent for the automatic detection? PS. side note: recent PR in ADNLPModels fail on buildkite; I have a rough idea of what is does (it's not free, AFAIR), what is the benefit in you case? do you recommend it? |
|
@jbcaillau |
|
Buildkite is free if you request your packages to be part of JuliaGPU CI buildkite: We can have CI with GPU for free on all platforms (NVIDIA, AMD, Intel, Apple). It's why I installed on it Krylov.jl, MadNLP.jl, ExaModels.jl, etc... I also use buildkite to test some extensions like Enzyme / Zygote in ADNLPModels.jl. |
|
If you use GPU in your packages, I highly recommend it! |
Benchmark resultJudge resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsA ratio greater than
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoTargetBaselineTarget resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoBaseline resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoRuntime information
|
Benchmark resultJudge resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsA ratio greater than
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoTargetBaselineTarget resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoBaseline resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoRuntime information
|
Benchmark resultJudge resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsA ratio greater than
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoTargetBaselineTarget resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoBaseline resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoRuntime information
|
Benchmark resultJudge resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsA ratio greater than
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoTargetBaselineTarget resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoBaseline resultBenchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoRuntime information
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
close #325
cc @PierreMartinon @jbcaillau
It helps determine how much time you can gain by detecting the sparsity pattern yourself.