Mattias Fält
Mattias Fält
Great, I'll start implementing ASAP, I wanted to do a presentation for some colleagues, and realized that forward-backward was not as straight forward (no pun intended) to implement as I...
Most processors today are able to perform operations on a chunk of data, often 8 units (4 float64s), and this macro mainly tells the compiler that it is all right...
After reading some more about simd (https://software.intel.com/en-us/articles/vectorization-in-julia) I was able to speed it up a bit more and added the example to the original post.
The problem definitely seems to be with how memory is created on threads. By running on the same set of threads every time, the problem seem to dissapear. I am...
The problem was not solved by changing CUDA.jl versions or changing system drivers. However, the problem does not seem to be reproducible on other machines. I tried myself on AWS...
Yes, I have tried several different configurations but I am only able to reproduce it on that machine. Not sure if it could be specific to the gpu model or...
I can confirm the error reported by @StephenVavasis The following creates an internal error in julia (tested on 1.5.2) `d3 = SwissDict((1 => 2, 3 => "b"))`
It says ``` julia julia> PyPlot.backend "qt4agg" ```
This problem is probably a result of issues #58 and #32
Isproper no longer breaks silently, but this feature should still be added.