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Fix and update AdaptiveSDE benchmarks (#126) #1605

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0e2a8d6
Fix and update AdaptiveSDE benchmarks (#126)
jitendravjh Jun 28, 2026
c69afef
Route qmax through the step-size controller in qmaxDetermination
jitendravjh Jul 2, 2026
be28a34
Use SOSRI for the Oval2 qmax test
jitendravjh Jul 2, 2026
669a849
Address review: transpose RSwM legend labels and align Oval2 qmax tol…
jitendravjh Jul 5, 2026
b597138
Tune Oval2 qmax controller to gamma=0.7 for zero adaptive failures
jitendravjh Jul 6, 2026
c0bf9f8
Force dtmin and cap maxiters on oval2 qmax sweep
jitendravjh Jul 21, 2026
50c97ea
Switch oval2 qmax test to SROCKEM
jitendravjh Jul 28, 2026
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43 changes: 15 additions & 28 deletions benchmarks/AdaptiveSDE/AdaptiveEfficiencyTests.jmd
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Original file line number Diff line number Diff line change
Expand Up @@ -4,25 +4,14 @@ author: Chris Rackauckas
---

```julia

using Distributed
addprocs(2)
using StochasticDiffEq, SDEProblemLibrary, DiffEqNoiseProcess, DiffEqBase, Plots
import SDEProblemLibrary: prob_sde_additive,
prob_sde_linear, prob_sde_wave

p1 = Vector{Any}(undef, 3)
p2 = Vector{Any}(undef, 3)
p3 = Vector{Any}(undef, 3)

@everywhere begin
using StochasticDiffEq, SDEProblemLibrary, DiffEqNoiseProcess, Plots,
ParallelDataTransfer
import SDEProblemLibrary: prob_sde_additive,
prob_sde_linear, prob_sde_wave
end

using StochasticDiffEq, SDEProblemLibrary, DiffEqNoiseProcess, Plots, ParallelDataTransfer
import SDEProblemLibrary: prob_sde_additive,
prob_sde_linear, prob_sde_wave

probs = Matrix{SDEProblem}(undef, 3, 3)
## Problem 1
prob = prob_sde_linear
Expand Down Expand Up @@ -59,7 +48,8 @@ Ns = [17, 23,
17]
```

Timings are only valid if no workers die. Workers die if you run out of memory.
The Monte Carlo runs use multithreaded ensembles (`EnsembleThreads()`), so start Julia
with multiple threads (e.g. `julia -t auto`) for parallel timing.

```julia
for k in 1:size(probs, 1)
Expand All @@ -76,16 +66,15 @@ for k in 1:size(probs, 1)

#Compile
prob = probs[k, 1]
ParallelDataTransfer.sendto(workers(), prob = prob)
monte_prob = EnsembleProblem(prob)
solve(monte_prob, SRIW1(), dt = 1/2^(4), adaptive = true,
solve(monte_prob, SRIW1(), EnsembleThreads(), dt = 1/2^(4), adaptive = true,
trajectories = 1000, abstol = 2.0^(-1), reltol = 0)

println("RSwM1")
for i in (1 + offset):(N + offset)
tols[i - offset, 1] = 2.0^(-i-1)
msims[i - offset] = DiffEqBase.calculate_monte_errors(solve(monte_prob, SRIW1(),
trajectories = 1000, abstol = 2.0^(-i-1),
msims[i - offset] = DiffEqBase.calculate_ensemble_errors(solve(monte_prob, SRIW1(),
EnsembleThreads(), trajectories = 1000, abstol = 2.0^(-i-1),
reltol = 0, force_dtmin = true))
elapsed[i - offset, 1] = msims[i - offset].elapsedTime
medians[i - offset, 1] = msims[i - offset].error_medians[:final]
Expand All @@ -95,15 +84,14 @@ for k in 1:size(probs, 1)
println("RSwM2")
prob = probs[k, 2]

ParallelDataTransfer.sendto(workers(), prob = prob)
monte_prob = EnsembleProblem(prob)
solve(monte_prob, SRIW1(), dt = 1/2^(4), adaptive = true,
solve(monte_prob, SRIW1(), EnsembleThreads(), dt = 1/2^(4), adaptive = true,
trajectories = 1000, abstol = 2.0^(-1), reltol = 0)

for i in (1 + offset):(N + offset)
tols[i - offset, 2] = 2.0^(-i-1)
msims[i - offset] = DiffEqBase.calculate_monte_errors(solve(monte_prob, SRIW1(),
trajectories = 1000, abstol = 2.0^(-i-1),
msims[i - offset] = DiffEqBase.calculate_ensemble_errors(solve(monte_prob, SRIW1(),
EnsembleThreads(), trajectories = 1000, abstol = 2.0^(-i-1),
reltol = 0, force_dtmin = true))
elapsed[i - offset, 2] = msims[i - offset].elapsedTime
medians[i - offset, 2] = msims[i - offset].error_medians[:final]
Expand All @@ -112,15 +100,14 @@ for k in 1:size(probs, 1)

println("RSwM3")
prob = probs[k, 3]
ParallelDataTransfer.sendto(workers(), prob = prob)
monte_prob = EnsembleProblem(prob)
solve(monte_prob, SRIW1(), dt = 1/2^(4), adaptive = true,
solve(monte_prob, SRIW1(), EnsembleThreads(), dt = 1/2^(4), adaptive = true,
trajectories = 1000, abstol = 2.0^(-1), reltol = 0)

for i in (1 + offset):(N + offset)
tols[i - offset, 3] = 2.0^(-i-1)
msims[i - offset] = DiffEqBase.calculate_monte_errors(solve(monte_prob, SRIW1(),
adaptive = true, trajectories = 1000, abstol = 2.0^(-i-1),
msims[i - offset] = DiffEqBase.calculate_ensemble_errors(solve(monte_prob, SRIW1(),
EnsembleThreads(), adaptive = true, trajectories = 1000, abstol = 2.0^(-i-1),
reltol = 0, force_dtmin = true))
elapsed[i - offset, 3] = msims[i - offset].elapsedTime
medians[i - offset, 3] = msims[i - offset].error_medians[:final]
Expand All @@ -137,7 +124,7 @@ end
```julia
gr(fmt = :svg)
lw=3
leg=String["RSwM1", "RSwM2", "RSwM3"]
leg=["RSwM1" "RSwM2" "RSwM3"]

titleFontSize = 16
guideFontSize = 14
Expand Down
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