Tutorial fails using Metal.jl #315
Comments
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More information in case relevant: Metal.versioninfo()
macOS 14.0.0, Darwin 23.0.0
Toolchain:
- Julia: 1.9.0
- LLVM: 14.0.6
Julia packages:
- Metal.jl: 0.5.1
- Metal_LLVM_Tools_jll: 0.5.1+0
1 device:
- Apple M1 (2.406 MiB allocated) |
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The Apple M1 does not support Float64 values yet, which is causing some issues with type I am trying to fix it using #317. Thanks for bringing it up! |
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I'm getting a different error with the previous tutorial (no Error: No solution found
│ tspan = 0.0f0
│ ts =
│ 2-element view(::Matrix{Float32}, :, 1) with eltype Float32:
│ 0.0
│ 0.0
└ @ DiffEqGPU ~/.julia/packages/DiffEqGPU/I999k/src/solve.jl:175
ERROR: Batch solve failedCode
using DiffEqGPU, OrdinaryDiffEq, StaticArrays, Metal
function lorenz(u, p, t)
σ = p[1]
ρ = p[2]
β = p[3]
du1 = σ * (u[2] - u[1])
du2 = u[1] * (ρ - u[3]) - u[2]
du3 = u[1] * u[2] - β * u[3]
return SVector{3}(du1, du2, du3)
end
u0 = @SVector [1.0f0; 0.0f0; 0.0f0]
tspan = (0.0f0, 10.0f0)
p = @SVector [10.0f0, 28.0f0, 8 / 3.0f0]
prob = ODEProblem{false}(lorenz, u0, tspan, p)
prob_func = (prob, i, repeat) -> remake(prob, p = (@SVector rand(Float32, 3)) .* p) # this fails
#prob_func = (prob, i, repeat) -> remake(prob, p = (@SVector rand(Float32, 3)) .* p .* 0.1f0) # this works
monteprob = EnsembleProblem(prob, prob_func = prob_func, safetycopy = false)
sol = solve(monteprob, GPUTsit5(), EnsembleGPUKernel(Metal.MetalBackend()), trajectories = 10_000)Complete error
Package versions
Metal.versioninfo()
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Hi,
I am trying to run this tutorial on my laptop, which has an M1 processor. My understanding is that to do this, I should just change
CUDAtoMetal:However, when I run the code above, the last line gives the error:
These are the package versions:
Is this the expected behavior?
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