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Bug fixes (#10)
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Shifted incrementation of _iteration_count to match current version of EAGO, added Reexport to deps, re-ran README examples.
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@RXGottlieb
RXGottlieb authored Nov 8, 2024
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4 changes: 3 additions & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,14 +1,15 @@
name = "SourceCodeMcCormick"
uuid = "a7283dc5-4ecf-47fb-a95b-1412723fc960"
authors = ["Robert Gottlieb <[email protected]>"]
version = "0.4.0"
version = "0.4.1"

[deps]
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
IfElse = "615f187c-cbe4-4ef1-ba3b-2fcf58d6d173"
Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
SymbolicUtils = "d1185830-fcd6-423d-90d6-eec64667417b"
Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"

Expand All @@ -17,6 +18,7 @@ CUDA = "5"
DocStringExtensions = "0.8 - 0.9"
Graphs = "1"
IfElse = "0.1.0 - 0.1.1"
Reexport = "~1"
SymbolicUtils = "3"
Symbolics = "6"
julia = "1.10"
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37 changes: 18 additions & 19 deletions README.md
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Expand Up @@ -524,15 +524,15 @@ Running this code (after an initial compilation run) generates the following out
---------------------------------------------------------------------------------------------------------------------------------
| Iteration # | Nodes | Lower Bound | Upper Bound | Gap | Ratio | Timer | Time Left |
---------------------------------------------------------------------------------------------------------------------------------
| 10 | 47818 | -8.337E-01 | -7.048E-01 | 1.289E-01 | 1.546E-01 | 0.74 | 3599.26 |
| 20 | 117316 | -7.703E-01 | -7.048E-01 | 6.549E-02 | 8.503E-02 | 1.47 | 3598.53 |
| 30 | 162052 | -7.608E-01 | -7.048E-01 | 5.604E-02 | 7.365E-02 | 1.90 | 3598.10 |
| 40 | 177018 | -7.473E-01 | -7.048E-01 | 4.254E-02 | 5.693E-02 | 2.38 | 3597.62 |
| 50 | 161712 | -7.411E-01 | -7.048E-01 | 3.632E-02 | 4.901E-02 | 3.24 | 3596.76 |
| 60 | 128062 | -7.293E-01 | -7.048E-01 | 2.453E-02 | 3.363E-02 | 4.10 | 3595.90 |
| 70 | 73936 | -7.211E-01 | -7.048E-01 | 1.631E-02 | 2.262E-02 | 5.03 | 3594.97 |
| 80 | 11916 | -7.180E-01 | -7.048E-01 | 1.321E-02 | 1.841E-02 | 5.59 | 3594.41 |
| 83 | 4560 | -7.051E-01 | -7.048E-01 | 3.648E-04 | 5.173E-04 | 5.64 | 3594.36 |
| 10 | 47818 | -8.337E-01 | -7.048E-01 | 1.289E-01 | 1.546E-01 | 0.47 | 3599.53 |
| 20 | 117316 | -7.703E-01 | -7.048E-01 | 6.549E-02 | 8.503E-02 | 0.83 | 3599.17 |
| 30 | 162052 | -7.608E-01 | -7.048E-01 | 5.604E-02 | 7.365E-02 | 1.26 | 3598.74 |
| 40 | 177018 | -7.473E-01 | -7.048E-01 | 4.254E-02 | 5.693E-02 | 1.74 | 3598.26 |
| 50 | 161712 | -7.411E-01 | -7.048E-01 | 3.632E-02 | 4.901E-02 | 2.62 | 3597.38 |
| 60 | 128062 | -7.293E-01 | -7.048E-01 | 2.453E-02 | 3.363E-02 | 3.17 | 3596.83 |
| 70 | 73936 | -7.211E-01 | -7.048E-01 | 1.631E-02 | 2.262E-02 | 3.76 | 3596.24 |
| 80 | 11916 | -7.180E-01 | -7.048E-01 | 1.321E-02 | 1.841E-02 | 4.36 | 3595.64 |
| 82 | 4560 | -7.051E-01 | -7.048E-01 | 3.648E-04 | 5.173E-04 | 4.42 | 3595.58 |
---------------------------------------------------------------------------------------------------------------------------------
Relative Tolerance Achieved
Expand All @@ -550,13 +550,13 @@ Solution:
p[8] = 0.9999999998842802
```

Using the subgradient-free method, and processing 8192 nodes per iteration, this problem converged in 83
iterations (roughly 679,936 nodes explored), with a total time of 5.64 seconds. These times were obtained
Using the subgradient-free method, and processing 8192 nodes per iteration, this problem converged in 82
iterations (roughly 671,744 nodes explored), with a total time of 4.42 seconds. These times were obtained
on a workstation with an Intel i7-9850H processor and an NVIDIA Quadro T2000 GPU. Using a GPU with a
greater capacity for double-precision floating point calculations will, of course, improve the overall
performance of the algorithm, but even with a fairly "typical" GPU such as this, relatively competitive
speed can be obtained. As compared to the base version of EAGO (which makes use of subgradients), this
example ran roughly 9x faster.
example ran roughly 11x faster.

It is also important to note that, because a subgradient-free method was used, the lower bounds for any
individual branch-and-bound node are not as tight as those that can be obtained using subgradient-based
Expand Down Expand Up @@ -662,16 +662,15 @@ Running this code (after an initial compilation run) generates the following out
---------------------------------------------------------------------------------------------------------------------------------
| Iteration # | Nodes | Lower Bound | Upper Bound | Gap | Ratio | Timer | Time Left |
---------------------------------------------------------------------------------------------------------------------------------
| 10 | 16280 | -7.754E-01 | -7.048E-01 | 7.067E-02 | 9.113E-02 | 0.59 | 3599.41 |
| 20 | 59342 | -7.353E-01 | -7.048E-01 | 3.055E-02 | 4.154E-02 | 1.16 | 3598.84 |
| 30 | 46048 | -7.108E-01 | -7.048E-01 | 5.983E-03 | 8.418E-03 | 1.82 | 3598.18 |
| 40 | 2240 | -7.058E-01 | -7.048E-01 | 9.852E-04 | 1.396E-03 | 2.30 | 3597.70 |
| 41 | 2240 | -7.058E-01 | -7.048E-01 | 9.852E-04 | 1.396E-03 | 2.30 | 3597.70 |
| 10 | 16280 | -7.754E-01 | -7.048E-01 | 7.067E-02 | 9.113E-02 | 0.45 | 3599.55 |
| 20 | 59342 | -7.353E-01 | -7.048E-01 | 3.055E-02 | 4.154E-02 | 1.09 | 3598.91 |
| 30 | 46048 | -7.108E-01 | -7.048E-01 | 5.983E-03 | 8.418E-03 | 1.85 | 3598.15 |
| 40 | 2240 | -7.058E-01 | -7.048E-01 | 9.852E-04 | 1.396E-03 | 2.33 | 3597.67 |
---------------------------------------------------------------------------------------------------------------------------------
Absolute Tolerance Achieved
Optimal Solution Found at Node 1
Lower Bound: -0.7057619894307734
Lower Bound: -0.7057619894307733
Upper Bound: -0.7047768067379733
Solution:
p[1] = -0.9999999998903418
Expand All @@ -688,7 +687,7 @@ As in the previous examples, these results were generated using an Intel i7-9850
Quadro T2000 GPU. Effectively, ParBB is running precisely the same lower-bounding routine as the base
version of the global solver EAGO, except that the routine is being performed in parallel on a GPU
rather than serially on the CPU. This example converges in 40 iterations of at most 8192 nodes per iteration,
for a total of roughly 327,680 nodes explored, and reaches its solution in 2.30 seconds. As compared to the
for a total of roughly 327,680 nodes explored, and reaches its solution in 2.33 seconds. As compared to the
base version of EAGO, this implementation of ParBB solves the problem roughly 22x faster. As in the previous
subsection, it should be noted that a GPU with better double-precision floating-point calculation throughput
would yield even faster results.
Expand Down
7 changes: 4 additions & 3 deletions examples/ParBB/subroutines.jl
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Expand Up @@ -31,8 +31,7 @@ function solve_gpu!(m::EAGO.GlobalOptimizer)
# Identify the extension
ext = EAGO._ext(m)

# Set counts to 1
m._iteration_count = 1
# Set node count to 1
m._node_count = 1

# Prepare to run branch-and-bound
Expand All @@ -54,6 +53,9 @@ function solve_gpu!(m::EAGO.GlobalOptimizer)
# Run branch and bound; terminate when the stack is empty or when some
# tolerance or limit is hit
while !EAGO.termination_check(m)

# Update iteration counter
m._iteration_count += 1

# Garbage collect every gc_freq iterations
if mod(m._iteration_count, EAGO._ext(m).gc_freq)==0
Expand Down Expand Up @@ -105,7 +107,6 @@ function solve_gpu!(m::EAGO.GlobalOptimizer)
m._time_left = m._parameters.time_limit - m._run_time
EAGO.log_iteration!(m)
EAGO.print_iteration!(m, false)
m._iteration_count += 1
end
EAGO.print_iteration!(m, true)

Expand Down
7 changes: 3 additions & 4 deletions src/SourceCodeMcCormick.jl
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@@ -1,7 +1,8 @@

module SourceCodeMcCormick

using Symbolics
using Reexport
@reexport using Symbolics
using SymbolicUtils.Code
using IfElse
using DocStringExtensions
Expand Down Expand Up @@ -51,8 +52,6 @@ export McCormickIntervalTransform, IntervalTransform
export apply_transform, all_evaluators, convex_evaluator, extract_terms,
genvar, genparam, get_name, factor, binarize!, pull_vars, shrink_eqs,
grad, shrink_grad!, convex_subgradient, all_subgradients, grad_transform!,
levels, eqn_edges, eval_generator, grad_eval_generator, fgen_cv, fgen_cvgrad,
fgen, fgen2
export @variables, Num
levels, eqn_edges, eval_generator, grad_eval_generator, fgen

end

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Registration pull request created: JuliaRegistries/General/119000

Tip: Release Notes

Did you know you can add release notes too? Just add markdown formatted text underneath the comment after the text
"Release notes:" and it will be added to the registry PR, and if TagBot is installed it will also be added to the
release that TagBot creates. i.e.

@JuliaRegistrator register

Release notes:

## Breaking changes

- blah

To add them here just re-invoke and the PR will be updated.

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.4.1 -m "<description of version>" 57cba3f3dac9c1a12dd15d11c71abc36539b0d40
git push origin v0.4.1

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