Michel Schanen

```jl using ForwardDiff function speelpenning(x) res = [1.0] for i in x res = res*i end return res end dim = parse(Int,ARGS[1]) println("Speelpenning with dim = ", dim) @time fjac...

The artifact one below. I also tried a system MPICH and OpenMPI. It should not work with any MPI library. Let me know if it does. ``` (jlScratch) pkg> st...

Oh sorry, I did not notice it tries to use the system one even if the environment variable `JULIA_MPI_BINARY` is not set. Anyhow, tried with `JULIA_MPI_BINARY=""` which falls back to...

Updating output with 0.9.2 [log.tar.gz](https://github.com/EnzymeAD/Enzyme.jl/files/8413498/log.tar.gz) with ```Enzyme.API.printall!(true) Enzyme.API.printtype!(true)```.

@vchuravy @wsmoses Updated the MWE and title. What breaks the differentiation is the function it dispatches to with the default `*` initialization (1.0). [log.txt](https://github.com/EnzymeAD/Enzyme.jl/files/8428112/log.txt) attached. Using the commented-out line and...

Updated the example. The `KernelGradients.jl` one had mistakes and returns a correct gradient now. The third check still fails. However, not with an error. It just returns a zero gradient,...

Here is actually the behavior that I am not sure is desired: ```julia using ForwardDiff using Enzyme using Test function speelpenning(x) reduce(*, x) end n = 16 x = [i/(1.0+i)...

This error appeared with Julia 1.6 and 1.8. Peng then pointed me to not load the oneAPI module on the target system, but only load the Intel Compute Runtime. We...

> Sadly the code uses Float64 We should make the code base type independent.

When doing ```julia @device_code_llvm dump_module=true auglag_linelimit_two_level_alternative_ka(device, 32, data.nline*32)( Val(mod.n), data.nline, mod.line_start, info.inner, par.max_auglag, par.mu_max, par.scale, sol.u_curr, sol.v_curr, sol.z_curr, sol.l_curr, sol.rho, par.shift_lines, mod.membuf, data.YffR, data.YffI, data.YftR, data.YftI, data.YttR, data.YttI, data.YtfR, data.YtfI,...