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Documenter.jl committed Nov 11, 2023
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2 changes: 1 addition & 1 deletion dev/.documenter-siteinfo.json
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{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-11-02T19:26:35","documenter_version":"1.1.2"}}
{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-11-11T17:20:33","documenter_version":"1.1.2"}}
301 changes: 210 additions & 91 deletions dev/assets/Manifest.toml
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@time sol = solve(monteprob, Tsit5(), EnsembleGPUArray(CUDA.CUDABackend()),
trajectories = 10_000,
saveat = 1.0f0)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">EnsembleSolution Solution of length 10000 with uType:
SciMLBase.ODESolution{ForwardDiff.Dual{Nothing, Float64, 3}, 2, uType, Nothing, Nothing, Vector{Float32}, rateType, SciMLBase.ODEProblem{Vector{ForwardDiff.Dual{Nothing, Float64, 3}}, Tuple{Float32, Float32}, true, Vector{Float32}, SciMLBase.ODEFunction{true, SciMLBase.FullSpecialize, typeof(Main.lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}, IType, SciMLBase.DEStats, Nothing} where {uType, rateType, IType}</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../sde/">« GPU Parallel Solving of Stochastic Differential Equations</a><a class="docs-footer-nextpage" href="../reductions/">Batched Reductions for Lowering Peak Memory Requirements »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.2 on <span class="colophon-date" title="Thursday 2 November 2023 19:26">Thursday 2 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
SciMLBase.ODESolution{ForwardDiff.Dual{Nothing, Float64, 3}, 2, uType, Nothing, Nothing, Vector{Float32}, rateType, SciMLBase.ODEProblem{Vector{ForwardDiff.Dual{Nothing, Float64, 3}}, Tuple{Float32, Float32}, true, Vector{Float32}, SciMLBase.ODEFunction{true, SciMLBase.FullSpecialize, typeof(Main.lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}, IType, SciMLBase.DEStats, Nothing} where {uType, rateType, IType}</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../sde/">« GPU Parallel Solving of Stochastic Differential Equations</a><a class="docs-footer-nextpage" href="../reductions/">Batched Reductions for Lowering Peak Memory Requirements »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.2 on <span class="colophon-date" title="Saturday 11 November 2023 17:20">Saturday 11 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
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11.5
u: 2-element Vector{CUDA.CuArray{Float64, 3, CUDA.Mem.DeviceBuffer}}:
[0.0 0.12134432813715873 … 0.1213443281371586 0.0; 0.0 0.12134432813715873 … 0.1213443281371586 0.0; … ; 0.0 0.12134432813715873 … 0.1213443281371586 0.0; 0.0 0.12134432813715873 … 0.1213443281371586 0.0;;; 0.0 0.0 … 0.0 0.0; 0.14892258453196755 0.14892258453196755 … 0.14892258453196755 0.14892258453196755; … ; 0.14892258453196738 0.14892258453196738 … 0.14892258453196738 0.14892258453196738; 0.0 0.0 … 0.0 0.0]
[3.0478431718176133 3.0478158588958384 … 3.047934407132488 3.0478829076399707; 3.0478921742796787 3.0478615839692695 … 3.0479950350866707 3.0479368431642384; … ; 3.0477574497062734 3.04773545592171 … 3.0478300382484087 3.047789226504652; 3.047797767524695 3.0477733366890103 … 3.047878867861117 3.047833184325156;;; 2.567054744858359 2.5670562676074793 … 2.567049778296592 2.567052560054736; 2.567051711744317 2.56705334622074 … 2.5670463664110166 2.5670493630392817; … ; 2.567060148333675 2.567061482264857 … 2.567055819529447 2.567058240137795; 2.567057591432184 2.567059013089459 … 2.567052966605906 2.567055554756332]</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../reaction_diffusion/">« GPU-Accelerated Stochastic Partial Differential Equations</a><a class="docs-footer-nextpage" href="../../manual/ensemblegpukernel/">EnsembleGPUKernel »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.2 on <span class="colophon-date" title="Thursday 2 November 2023 19:26">Thursday 2 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
[3.0478431718176133 3.0478158588958384 … 3.047934407132488 3.0478829076399707; 3.0478921742796787 3.0478615839692695 … 3.0479950350866707 3.0479368431642384; … ; 3.0477574497062734 3.04773545592171 … 3.0478300382484087 3.047789226504652; 3.047797767524695 3.0477733366890103 … 3.047878867861117 3.047833184325156;;; 2.567054744858359 2.5670562676074793 … 2.567049778296592 2.567052560054736; 2.567051711744317 2.56705334622074 … 2.5670463664110166 2.5670493630392817; … ; 2.567060148333675 2.567061482264857 … 2.567055819529447 2.567058240137795; 2.567057591432184 2.567059013089459 … 2.567052966605906 2.567055554756332]</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../reaction_diffusion/">« GPU-Accelerated Stochastic Partial Differential Equations</a><a class="docs-footer-nextpage" href="../../manual/ensemblegpukernel/">EnsembleGPUKernel »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.2 on <span class="colophon-date" title="Saturday 11 November 2023 17:20">Saturday 11 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
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reduction = reduction, u_init = Vector{eltype(prob.u0)}([0.0]))
sim4 = solve(prob2, Tsit5(), EnsembleGPUArray(CUDA.CUDABackend()), trajectories = 100,
batch_size = 20)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">EnsembleSolution Solution of length 1 with uType:
Float64</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../ad/">« Using GPU-accelerated Ensembles with Automatic Differentiation</a><a class="docs-footer-nextpage" href="../reaction_diffusion/">GPU-Accelerated Stochastic Partial Differential Equations »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.2 on <span class="colophon-date" title="Thursday 2 November 2023 19:26">Thursday 2 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
Float64</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../ad/">« Using GPU-accelerated Ensembles with Automatic Differentiation</a><a class="docs-footer-nextpage" href="../reaction_diffusion/">GPU-Accelerated Stochastic Partial Differential Equations »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.2 on <span class="colophon-date" title="Saturday 11 November 2023 17:20">Saturday 11 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
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monteprob = EnsembleProblem(prob, prob_func = prob_func)
sol = solve(monteprob, SOSRI(), EnsembleGPUArray(CUDA.CUDABackend()), trajectories = 10_000,
saveat = 1.0f0)</code></pre><pre class="documenter-example-output"><code class="nohighlight hljs ansi">EnsembleSolution Solution of length 10000 with uType:
SciMLBase.RODESolution{Float32, 2, uType, Nothing, Nothing, Vector{Float32}, randType, SciMLBase.SDEProblem{Vector{Float32}, Tuple{Float32, Float32}, true, Vector{Float32}, Nothing, SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, typeof(Main.lorenz), typeof(Main.multiplicative_noise), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, typeof(Main.multiplicative_noise), Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Nothing}, StochasticDiffEq.SOSRI, IType, SciMLBase.DEStats, Nothing} where {uType, randType, IType}</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../tutorials/within_method_gpu/">« Within-Method GPU Parallelism of Ordinary Differential Equation Solves</a><a class="docs-footer-nextpage" href="../ad/">Using GPU-accelerated Ensembles with Automatic Differentiation »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.2 on <span class="colophon-date" title="Thursday 2 November 2023 19:26">Thursday 2 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
SciMLBase.RODESolution{Float32, 2, uType, Nothing, Nothing, Vector{Float32}, randType, SciMLBase.SDEProblem{Vector{Float32}, Tuple{Float32, Float32}, true, Vector{Float32}, Nothing, SciMLBase.SDEFunction{true, SciMLBase.FullSpecialize, typeof(Main.lorenz), typeof(Main.multiplicative_noise), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, typeof(Main.multiplicative_noise), Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Nothing}, StochasticDiffEq.SOSRI, IType, SciMLBase.DEStats, Nothing} where {uType, randType, IType}</code></pre></article><nav class="docs-footer"><a class="docs-footer-prevpage" href="../../tutorials/within_method_gpu/">« Within-Method GPU Parallelism of Ordinary Differential Equation Solves</a><a class="docs-footer-nextpage" href="../ad/">Using GPU-accelerated Ensembles with Automatic Differentiation »</a><div class="flexbox-break"></div><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="auto">Automatic (OS)</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.1.2 on <span class="colophon-date" title="Saturday 11 November 2023 17:20">Saturday 11 November 2023</span>. Using Julia version 1.9.3.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
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