DiffEqGPU.jl
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GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
Such that `makedocs` `warnonly = [:missing_docs]` can be removed.
Hi all, calculating derivates wrt to the ode parameters of a gpu ensemble of odes fails when the parameters are a CuArray. Solvign the odes works, also ebverything works on...
MWE: ```julia using DiffEqGPU, DiffEqBase, StaticArrays function lorenz!(du,u,p,t) du[1] = 10.0(u[2]-u[1]) du[2] = u[1]*(28.0-u[3]) - u[2] du[3] = u[1]*u[2] - (8/3)*u[3] end u0 = @MArray [1.0;0.0;0.0] tspan = (0.0,100.0) prob...
Hi! This package doesn't have any Stratonovich SDE solvers. It would be nice to add one.
Is there any plan to add Python support for `DiffEqGPU.jl`similar to how `DifferentialEquations.jl` can be used from Python using `diffeqpy`?
Hi, I attempted to solve a second-order differential equation using a Julia library. However, I encountered an issue with the EnsembleGPUArray function, as the generated ensemble is not working as...
The following code locks up a 1080 strix according to the GPU Tweak III software. ```julia using DiffEqGPU, DifferentialEquations, StaticArrays function sys_gpu!(u, params, t) du1 = params[1] du2 = params[2]...
@ChrisRackauckas @utkarsh530 Per our conversation here is an example demonstrating how texture memory interpolation could be use. I would like to be able to leverage CUDA.jl's texture memory support for...
Hi, just copy pasting the example: ```julia # ╔═╡ 0094c9ce-0bf7-40ff-b6df-dcddf94828cd using DiffEqGPU, OrdinaryDiffEq, StaticArrays, CUDA # ╔═╡ 0c65ebbf-95b8-44eb-8789-8c03c29442d8 function lorenz(u, p, t) σ = p[1] ρ = p[2] β =...