Oval2 Timings
using StochasticDiffEq, SDEProblemLibrary, Random, Base.Threads
import OrdinaryDiffEqCore: PIController
using SciMLLogging
prob = SDEProblemLibrary.oval2ModelExample(largeFluctuations=true,useBigs=false)
prob_func(prob, ctx) = remake(prob, seed = ctx.sim_id)
prob = EnsembleProblem(remake(prob,tspan=(0.0,1.0)),prob_func=prob_func)
js = 16:21
dts = 1.0 ./ 2.0 .^ (js)
trajectories = 1000
fails = fill(-1, length(dts), 3)
times = fill(NaN, length(dts), 3)6×3 Matrix{Float64}:
NaN NaN NaN
NaN NaN NaN
NaN NaN NaN
NaN NaN NaN
NaN NaN NaN
NaN NaN NaNTiming Runs
sol = solve(prob,SRIW1(),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-7),maxiters=Int(1e11), controller=PIController(SRIW1(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SRIW1(),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-7),maxiters=Int(1e11), controller=PIController(SRIW1(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? Inf : adaptive_time
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 1.414995273sol = solve(prob,SRI(error_terms=2),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-7),maxiters=Int(1e11), controller=PIController(SRI(error_terms=2); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SRI(error_terms=2),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-7),maxiters=Int(1e11), controller=PIController(SRI(error_terms=2); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 1.413461571sol = solve(prob,SRI(),EnsembleThreads(),abstol=2.0^(-14),reltol=2.0^(-18),maxiters=Int(1e11), controller=PIController(SRI(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SRI(),EnsembleThreads(),abstol=2.0^(-14),reltol=2.0^(-18),maxiters=Int(1e11), controller=PIController(SRI(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 11.798118036sol = solve(prob,SRI(tableau=StochasticDiffEq.constructSRIOpt1()),EnsembleThreads(),abstol=2.0^(-7),reltol=2.0^(-4),maxiters=Int(1e11), controller=PIController(SRI(tableau=StochasticDiffEq.constructSRIOpt1()); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SRI(tableau=StochasticDiffEq.constructSRIOpt1()),EnsembleThreads(),abstol=2.0^(-7),reltol=2.0^(-4),maxiters=Int(1e11), controller=PIController(SRI(tableau=StochasticDiffEq.constructSRIOpt1()); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 0.155726578sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-7),reltol=2.0^(-4),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-7),reltol=2.0^(-4),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 0.086083294sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-7),reltol=2.0^(-6),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-7),reltol=2.0^(-6),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 0.191174831sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-12),reltol=2.0^(-15),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-12),reltol=2.0^(-15),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 1.034539642sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-7),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-7),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 0.211252473sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-12),reltol=2.0^(-15),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SOSRI(),EnsembleThreads(),abstol=2.0^(-12),reltol=2.0^(-15),maxiters=Int(1e11), controller=PIController(SOSRI(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 1.125136985sol = solve(prob,SOSRI2(),EnsembleThreads(),abstol=2.0^(-12),reltol=2.0^(-15),maxiters=Int(1e11), controller=PIController(SOSRI2(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SOSRI2(),EnsembleThreads(),abstol=2.0^(-12),reltol=2.0^(-15),maxiters=Int(1e11), controller=PIController(SOSRI2(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 1.333631523sol = solve(prob,SOSRI2(),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-11),maxiters=Int(1e11), controller=PIController(SOSRI2(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SOSRI2(),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-11),maxiters=Int(1e11), controller=PIController(SOSRI2(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 0.524695957sol = solve(prob,SOSRI2(),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-11),maxiters=Int(1e11), controller=PIController(SOSRI2(); qmax=1.125),save_everystep=false,trajectories=Threads.nthreads())
adaptive_time = @elapsed sol = solve(prob,SOSRI2(),EnsembleThreads(),abstol=2.0^(-13),reltol=2.0^(-11),maxiters=Int(1e11), controller=PIController(SOSRI2(); qmax=1.125),save_everystep=false,trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
best_adaptive_time = numfails != 0 ? adaptive_time : min(best_adaptive_time,adaptive_time)
println("The number of Adaptive Fails is $numfails. Elapsed time was $adaptive_time")The number of Adaptive Fails is 0. Elapsed time was 0.54175756for j in eachindex(js)
println("j = $j")
sol =solve(prob,EM(),EnsembleThreads(),dt=dts[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=Threads.nthreads())
t1 = @elapsed sol = solve(prob,EM(),EnsembleThreads(),dt=dts[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
println("The number of Euler-Maruyama Fails is $numfails. Elapsed time was $t1")
fails[j,1] = numfails
times[j,1] = t1
endj = 1
The number of Euler-Maruyama Fails is 10. Elapsed time was 0.535252403
j = 2
The number of Euler-Maruyama Fails is 1. Elapsed time was 1.186223178
j = 3
The number of Euler-Maruyama Fails is 1. Elapsed time was 1.973320553
j = 4
The number of Euler-Maruyama Fails is 0. Elapsed time was 3.996241751
j = 5
The number of Euler-Maruyama Fails is 0. Elapsed time was 7.780787142
j = 6
The number of Euler-Maruyama Fails is 0. Elapsed time was 14.519602612for j in 1:4
println("j = $j")
sol =solve(prob,SRIW1(),EnsembleThreads(),dt=dts[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=Threads.nthreads())
t1 = @elapsed sol = solve(prob,SRIW1(),EnsembleThreads(),dt=dts[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
println("The number of SRIW1 Fails is $numfails. Elapsed time was $t1")
fails[j,3] = numfails
times[j,3] = t1
endj = 1
The number of SRIW1 Fails is 984. Elapsed time was 0.186887579
j = 2
The number of SRIW1 Fails is 975. Elapsed time was 0.50833916
j = 3
The number of SRIW1 Fails is 978. Elapsed time was 0.414168658
j = 4
The number of SRIW1 Fails is 975. Elapsed time was 0.495289084js_imp = 17:21
dts_imp = 1.0 ./ 2.0 .^ (js_imp)
for j in eachindex(dts_imp)
println("j = $j")
sol =solve(prob,ImplicitEM(),EnsembleThreads(),dt=dts_imp[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=Threads.nthreads())
t1 = @elapsed sol = solve(prob,ImplicitEM(),EnsembleThreads(),dt=dts_imp[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
println("The number of Implicit-EM Fails is $numfails. Elapsed time was $t1")
endj = 1
The number of Implicit-EM Fails is 0. Elapsed time was 11.056715721
j = 2
The number of Implicit-EM Fails is 0. Elapsed time was 10.879338335
j = 3
The number of Implicit-EM Fails is 0. Elapsed time was 10.982118101
j = 4
The number of Implicit-EM Fails is 0. Elapsed time was 10.925827093
j = 5
The number of Implicit-EM Fails is 0. Elapsed time was 11.173264094for j in eachindex(dts_imp)
println("j = $j")
sol =solve(prob,ImplicitRKMil(),EnsembleThreads(),dt=dts_imp[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=Threads.nthreads())
t1 = @elapsed sol = solve(prob,ImplicitRKMil(),EnsembleThreads(),dt=dts_imp[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
println("The number of Implicit-RKMil Fails is $numfails. Elapsed time was $t1")
endj = 1
The number of Implicit-RKMil Fails is 0. Elapsed time was 20.666996013
j = 2
The number of Implicit-RKMil Fails is 0. Elapsed time was 21.069603791
j = 3
The number of Implicit-RKMil Fails is 0. Elapsed time was 20.660373685
j = 4
The number of Implicit-RKMil Fails is 0. Elapsed time was 20.62144341
j = 5
The number of Implicit-RKMil Fails is 0. Elapsed time was 20.414338358for j in eachindex(dts)
println("j = $j")
sol =solve(prob,RKMil(),EnsembleThreads(),dt=dts[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=Threads.nthreads())
t1 = @elapsed sol = solve(prob,RKMil(),EnsembleThreads(),dt=dts[j],maxiters=Int(1e11),save_everystep=false,verbose=SciMLLogging.None(),trajectories=trajectories)
numfails = sum([Int(any(isnan,sol.u[i]) || sol.u[i].t[end] != 1) for i in 1:trajectories])
println("The number of RKMil Fails is $numfails. Elapsed time was $t1")
fails[j,2] = numfails
times[j,2] = t1
endj = 1
The number of RKMil Fails is 5. Elapsed time was 0.221908897
j = 2
The number of RKMil Fails is 3. Elapsed time was 0.308504936
j = 3
The number of RKMil Fails is 6. Elapsed time was 0.262556099
j = 4
The number of RKMil Fails is 7. Elapsed time was 0.237720559
j = 5
The number of RKMil Fails is 7. Elapsed time was 0.222163033
j = 6
The number of RKMil Fails is 6. Elapsed time was 0.245782284using Plots, LaTeXStrings
lw = 3
p2 = plot(dts,times,xscale=:log2,yscale=:log2,guidefont=font(16),tickfont=font(14),yguide="Elapsed Time (s)",xguide=L"Chosen $\Delta t$",linewidth=lw,lab=["Euler-Maruyama" "RK-Mil" "RosslerSRI"],legendfont=font(14))
plot!(dts,fill(best_adaptive_time, length(dts)),linewidth=lw,line=:dash,lab="ESRK+RSwM3")
scatter!([2.0^(-20);2.0^(-20);2.0^(-18)],[times[5,1];times[5,2];times[3,3]],markersize=20,c=:red,lab="")
plot(p2,size=(800,800))
Appendix
These benchmarks are a part of the SciMLBenchmarks.jl repository, found at: https://github.com/SciML/SciMLBenchmarks.jl. For more information on high-performance scientific machine learning, check out the SciML Open Source Software Organization https://sciml.ai.
To locally run this benchmark, do the following commands:
using SciMLBenchmarks
SciMLBenchmarks.weave_file("benchmarks/StiffSDE","Oval2Timings.jmd")Computer Information:
Julia Version 1.11.9
Commit 53a02c0720c (2026-02-06 00:27 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 128 × AMD EPYC 7502 32-Core Processor
WORD_SIZE: 64
LLVM: libLLVM-16.0.6 (ORCJIT, znver2)
Threads: 128 default, 0 interactive, 64 GC (on 128 virtual cores)
Environment:
JULIA_DEPOT_PATH = /home/crackauc/github-runners/amdci8-1/.julia
JULIA_NUM_THREADS = auto
Package Information:
Status `~/github-runners/amdci8-1/_work/SciMLBenchmarks.jl/SciMLBenchmarks.jl/benchmarks/StiffSDE/Project.toml`
⌃ [f3b72e0c] DiffEqDevTools v3.2.0
⌃ [77a26b50] DiffEqNoiseProcess v5.34.0
⌃ [b964fa9f] LaTeXStrings v1.4.0
⌃ [bbf590c4] OrdinaryDiffEqCore v4.13.0
⌃ [91a5bcdd] Plots v1.41.6
⌃ [c72e72a9] SDEProblemLibrary v1.2.3
⌅ [0bca4576] SciMLBase v3.43.0
⌃ [31c91b34] SciMLBenchmarks v0.1.3
⌃ [a6db7da4] SciMLLogging v2.0.4
⌃ [10745b16] Statistics v1.11.1
⌃ [789caeaf] StochasticDiffEq v7.1.4
[37e2e46d] LinearAlgebra v1.11.0
[9a3f8284] Random v1.11.0
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated`And the full manifest:
Status `~/github-runners/amdci8-1/_work/SciMLBenchmarks.jl/SciMLBenchmarks.jl/benchmarks/StiffSDE/Manifest.toml`
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[ba0b0d4f] Krylov v0.10.9
⌃ [b964fa9f] LaTeXStrings v1.4.0
⌃ [23fbe1c1] Latexify v0.16.11
⌃ [87fe0de2] LineSearch v0.1.13
⌃ [7ed4a6bd] LinearSolve v5.5.0
[2ab3a3ac] LogExpFunctions v1.0.1
[e6f89c97] LoggingExtras v1.2.0
[1914dd2f] MacroTools v0.5.16
⌃ [bb5d69b7] MaybeInplace v0.1.7
[739be429] MbedTLS v1.1.10
[442fdcdd] Measures v0.3.3
[e1d29d7a] Missings v1.2.0
[46d2c3a1] MuladdMacro v0.2.7
[ffc61752] Mustache v1.0.21
[77ba4419] NaNMath v1.1.4
⌃ [8913a72c] NonlinearSolve v4.25.0
⌃ [be0214bd] NonlinearSolveBase v2.41.0
⌃ [5959db7a] NonlinearSolveFirstOrder v2.3.0
⌃ [9a2c21bd] NonlinearSolveQuasiNewton v1.15.0
⌃ [26075421] NonlinearSolveSpectralMethods v1.8.0
[4d8831e6] OpenSSL v1.6.1
⌅ [bac558e1] OrderedCollections v1.8.2
⌃ [bbf590c4] OrdinaryDiffEqCore v4.13.0
⌃ [4302a76b] OrdinaryDiffEqDifferentiation v3.7.0
⌃ [127b3ac7] OrdinaryDiffEqNonlinearSolve v2.6.1
[90014a1f] PDMats v0.11.41
⌅ [69de0a69] Parsers v2.8.7
[ccf2f8ad] PlotThemes v3.3.0
[995b91a9] PlotUtils v1.4.4
⌃ [91a5bcdd] Plots v1.41.6
[e409e4f3] PoissonRandom v0.4.13
⌃ [d236fae5] PreallocationTools v1.4.1
⌅ [aea7be01] PrecompileTools v1.2.1
[21216c6a] Preferences v1.5.2
⌃ [08abe8d2] PrettyTables v3.4.5
[43287f4e] PtrArrays v1.4.0
⌃ [0c0d3e7f] PureKLU v1.4.0
[1fd47b50] QuadGK v2.11.3
[3cdcf5f2] RecipesBase v1.3.4
[01d81517] RecipesPipeline v0.6.12
⌃ [731186ca] RecursiveArrayTools v4.3.6
[189a3867] Reexport v1.2.2
[05181044] RelocatableFolders v1.0.1
[ae029012] Requires v1.3.1
⌃ [ae5879a3] ResettableStacks v1.3.0
⌃ [9fe22ead] RespecializeParams v1.2.0
[79098fc4] Rmath v0.9.0
⌃ [47965b36] RootedTrees v2.25.4
⌃ [f2b01f46] Roots v3.0.6
⌃ [7e49a35a] RuntimeGeneratedFunctions v0.5.24
⌃ [c72e72a9] SDEProblemLibrary v1.2.3
⌅ [0bca4576] SciMLBase v3.43.0
⌃ [31c91b34] SciMLBenchmarks v0.1.3
⌃ [19f34311] SciMLJacobianOperators v0.1.16
⌃ [a6db7da4] SciMLLogging v2.0.4
⌃ [c0aeaf25] SciMLOperators v1.26.0
⌃ [431bcebd] SciMLPublic v1.2.4
⌃ [53ae85a6] SciMLStructures v1.10.4
[6c6a2e73] Scratch v1.3.0
[efcf1570] Setfield v1.1.2
⌃ [992d4aef] Showoff v1.0.3
[777ac1f9] SimpleBufferStream v1.2.0
⌃ [727e6d20] SimpleNonlinearSolve v2.14.0
[699a6c99] SimpleTraits v0.9.6
[a2af1166] SortingAlgorithms v1.2.3
⌃ [a57abbd0] SparseColumnPivotedQR v2.1.6
⌃ [0a514795] SparseMatrixColorings v0.4.27
⌃ [276daf66] SpecialFunctions v2.8.3
[860ef19b] StableRNGs v1.0.4
⌃ [90137ffa] StaticArrays v1.9.18
[1e83bf80] StaticArraysCore v1.4.4
⌃ [10745b16] Statistics v1.11.1
[82ae8749] StatsAPI v1.8.0
⌃ [2913bbd2] StatsBase v0.34.12
[4c63d2b9] StatsFuns v2.2.1
⌃ [789caeaf] StochasticDiffEq v7.1.4
⌃ [19c5a474] StochasticDiffEqCore v2.0.5
⌃ [0520c28c] StochasticDiffEqHighOrder v2.1.3
⌃ [ebf54054] StochasticDiffEqIIF v2.0.3
⌃ [5080b986] StochasticDiffEqImplicit v2.1.3
⌃ [aefaaa88] StochasticDiffEqLeaping v2.0.3
⌃ [90dbc90e] StochasticDiffEqLevyArea v2.0.3
⌃ [d15fe365] StochasticDiffEqLowOrder v2.0.3
⌃ [8c95a807] StochasticDiffEqMilstein v2.0.3
⌃ [db241ea8] StochasticDiffEqROCK v2.0.3
⌃ [49714585] StochasticDiffEqRODE v2.0.3
⌃ [af2a2fcd] StochasticDiffEqWeak v2.1.3
[69024149] StringEncodings v0.3.7
⌅ [892a3eda] StringManipulation v0.4.7
[09ab397b] StructArrays v0.7.3
⌃ [2efcf032] SymbolicIndexingInterface v0.3.53
[3783bdb8] TableTraits v1.0.1
⌃ [bd369af6] Tables v1.13.0
[62fd8b95] TensorCore v0.1.1
⌃ [a759f4b9] TimerOutputs v1.1.0
[3bb67fe8] TranscodingStreams v0.11.3
[781d530d] TruncatedStacktraces v1.4.0
⌃ [5c2747f8] URIs v1.6.2
[1cfade01] UnicodeFun v0.4.1
[41fe7b60] Unzip v0.2.0
[81def892] VersionParsing v1.3.0
[44d3d7a6] Weave v0.10.12
[ddb6d928] YAML v0.4.16
[c2297ded] ZMQ v1.5.1
[6e34b625] Bzip2_jll v1.0.9+0
[83423d85] Cairo_jll v1.18.7+0
[ee1fde0b] Dbus_jll v1.16.2+0
[2702e6a9] EpollShim_jll v0.0.20230411+1
⌃ [2e619515] Expat_jll v2.8.2+0
⌅ [b22a6f82] FFMPEG_jll v8.1.2+0
[a3f928ae] Fontconfig_jll v2.17.1+0
[d7e528f0] FreeType2_jll v2.14.3+1
[559328eb] FriBidi_jll v1.0.17+0
⌃ [0656b61e] GLFW_jll v3.4.1+1
⌅ [d2c73de3] GR_jll v0.73.26+0
⌅ [b0724c58] GettextRuntime_jll v0.22.4+0
[61579ee1] Ghostscript_jll v9.55.1+0
[020c3dae] Git_LFS_jll v3.7.1+0
[f8c6e375] Git_jll v2.55.0+0
[7746bdde] Glib_jll v2.88.3+0
[3b182d85] Graphite2_jll v1.3.16+0
⌅ [2e76f6c2] HarfBuzz_jll v8.5.1+0
[1d5cc7b8] IntelOpenMP_jll v2025.2.0+0
⌃ [aacddb02] JpegTurbo_jll v3.2.0+0
[c1c5ebd0] LAME_jll v3.100.3+0
[88015f11] LERC_jll v4.1.0+0
[1d63c593] LLVMOpenMP_jll v22.1.7+0
⌅ [e9f186c6] Libffi_jll v3.4.7+0
[7e76a0d4] Libglvnd_jll v1.7.1+1
[94ce4f54] Libiconv_jll v1.18.0+0
[4b2f31a3] Libmount_jll v2.42.0+0
[89763e89] Libtiff_jll v4.7.3+0
[38a345b3] Libuuid_jll v2.42.0+0
[856f044c] MKL_jll v2025.2.0+0
[e7412a2a] Ogg_jll v1.3.6+0
⌃ [9bd350c2] OpenSSH_jll v10.4.1+0
⌃ [458c3c95] OpenSSL_jll v3.5.7+0
[efe28fd5] OpenSpecFun_jll v0.5.6+0
[91d4177d] Opus_jll v1.6.1+0
⌃ [36c8627f] Pango_jll v1.58.0+0
[30392449] Pixman_jll v0.46.4+0
[c0090381] Qt6Base_jll v6.10.2+2
[629bc702] Qt6Declarative_jll v6.10.2+2
[ce943373] Qt6ShaderTools_jll v6.10.2+1
[6de9746b] Qt6Svg_jll v6.10.2+0
[e99dba38] Qt6Wayland_jll v6.10.2+1
[f50d1b31] Rmath_jll v0.5.2+0
[a44049a8] Vulkan_Loader_jll v1.3.243+0
[a2964d1f] Wayland_jll v1.24.0+0
[ffd25f8a] XZ_jll v5.8.3+0
[f67eecfb] Xorg_libICE_jll v1.1.2+0
[c834827a] Xorg_libSM_jll v1.2.6+0
[4f6342f7] Xorg_libX11_jll v1.8.13+0
[0c0b7dd1] Xorg_libXau_jll v1.0.13+0
[935fb764] Xorg_libXcursor_jll v1.2.4+0
[a3789734] Xorg_libXdmcp_jll v1.1.6+0
[1082639a] Xorg_libXext_jll v1.3.8+0
[d091e8ba] Xorg_libXfixes_jll v6.0.2+0
[a51aa0fd] Xorg_libXi_jll v1.8.4+0
[d1454406] Xorg_libXinerama_jll v1.1.7+0
[ec84b674] Xorg_libXrandr_jll v1.5.6+0
[ea2f1a96] Xorg_libXrender_jll v0.9.12+0
[a65dc6b1] Xorg_libpciaccess_jll v0.19.0+0
[c7cfdc94] Xorg_libxcb_jll v1.17.1+0
[cc61e674] Xorg_libxkbfile_jll v1.2.0+0
[e920d4aa] Xorg_xcb_util_cursor_jll v0.1.6+0
[12413925] Xorg_xcb_util_image_jll v0.4.1+0
[2def613f] Xorg_xcb_util_jll v0.4.1+0
[975044d2] Xorg_xcb_util_keysyms_jll v0.4.1+0
[0d47668e] Xorg_xcb_util_renderutil_jll v0.3.10+0
[c22f9ab0] Xorg_xcb_util_wm_jll v0.4.2+0
[35661453] Xorg_xkbcomp_jll v1.4.7+0
[33bec58e] Xorg_xkeyboard_config_jll v2.47.0+2
[c5fb5394] Xorg_xtrans_jll v1.6.0+0
[8f1865be] ZeroMQ_jll v4.3.6+0
[3161d3a3] Zstd_jll v1.5.7+1
[35ca27e7] eudev_jll v3.2.14+0
⌅ [214eeab7] fzf_jll v0.61.1+0
⌃ [a4ae2306] libaom_jll v3.13.3+0
⌃ [0ac62f75] libass_jll v0.17.4+0
[1183f4f0] libdecor_jll v0.2.2+0
[8e53e030] libdrm_jll v2.4.134+0
[2db6ffa8] libevdev_jll v1.13.4+0
[f638f0a6] libfdk_aac_jll v2.0.4+0
[36db933b] libinput_jll v1.28.1+0
[b53b4c65] libpng_jll v1.6.58+0
[a9144af2] libsodium_jll v1.0.21+0
[9a156e7d] libva_jll v2.23.0+0
[f27f6e37] libvorbis_jll v1.3.8+0
[009596ad] mtdev_jll v1.1.7+0
[1317d2d5] oneTBB_jll v2022.3.0+0
⌅ [1270edf5] x264_jll v10164.0.1+0
[dfaa095f] x265_jll v4.1.0+0
[d8fb68d0] xkbcommon_jll v1.13.0+0
[0dad84c5] ArgTools v1.1.2
[56f22d72] Artifacts v1.11.0
[2a0f44e3] Base64 v1.11.0
[ade2ca70] Dates v1.11.0
[8ba89e20] Distributed v1.11.0
[f43a241f] Downloads v1.6.0
[7b1f6079] FileWatching v1.11.0
[9fa8497b] Future v1.11.0
[b77e0a4c] InteractiveUtils v1.11.0
[4af54fe1] LazyArtifacts v1.11.0
[b27032c2] LibCURL v0.6.4
[76f85450] LibGit2 v1.11.0
[8f399da3] Libdl v1.11.0
[37e2e46d] LinearAlgebra v1.11.0
[56ddb016] Logging v1.11.0
[d6f4376e] Markdown v1.11.0
[a63ad114] Mmap v1.11.0
[ca575930] NetworkOptions v1.2.0
[44cfe95a] Pkg v1.11.0
[de0858da] Printf v1.11.0
[3fa0cd96] REPL v1.11.0
[9a3f8284] Random v1.11.0
[ea8e919c] SHA v0.7.0
[9e88b42a] Serialization v1.11.0
[6462fe0b] Sockets v1.11.0
[2f01184e] SparseArrays v1.11.0
[f489334b] StyledStrings v1.11.0
[4607b0f0] SuiteSparse
[fa267f1f] TOML v1.0.3
[a4e569a6] Tar v1.10.0
[8dfed614] Test v1.11.0
[cf7118a7] UUIDs v1.11.0
[4ec0a83e] Unicode v1.11.0
[e66e0078] CompilerSupportLibraries_jll v1.1.1+0
[deac9b47] LibCURL_jll v8.6.0+0
[e37daf67] LibGit2_jll v1.7.2+0
[29816b5a] LibSSH2_jll v1.11.0+1
[c8ffd9c3] MbedTLS_jll v2.28.6+0
[14a3606d] MozillaCACerts_jll v2023.12.12
[4536629a] OpenBLAS_jll v0.3.27+1
[05823500] OpenLibm_jll v0.8.5+0
[efcefdf7] PCRE2_jll v10.42.0+1
[bea87d4a] SuiteSparse_jll v7.7.0+0
[83775a58] Zlib_jll v1.2.13+1
[8e850b90] libblastrampoline_jll v5.11.0+0
[8e850ede] nghttp2_jll v1.59.0+0
[3f19e933] p7zip_jll v17.4.0+2
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`