1. Writing and compiling a “query” (in the current release, LINQ lambda only – but a Roslyn powered regular method coming soon).
2. Running this “compiled query” with real arguments in a command queue, with synchronization markers.

If you can perform the “compile” step ahead of time, you can execute the compiled query as many times as you want in the “OnGPU” method (and pass in the right arguments) so the kernel runs on the GPU and returns its results to you. I would recommend you start looking at the code samples in the source to understand the process I’ve outlined above. You can then move the appropriate pieces to the methods/classes you want.

first of all: I’m very impressed of your work. A year ago I already did some testing with your lib and liked it very much. I’m glad to see that it continues to get better.

I’m currently developing a component that heavily relies on IQueryable and IQbservable to do some data mining, calculations and analysis on different kinds of data. I would love to integrate the possibility to offload some work on the GPU there.
My dream would be to have a simple .OnGPU() extension method for IQueryable and IQbservable that automatically offloads all following work to the GPU. Is that possible? I’m not very deep into the current codebase, I just had a quick look, therefore I’m not sure how to start with that or if there are any constraints that makes my idea senseless.

Best regards,
Patrick

What in the next version of C# do you expect will change this?

The idea of being able to run a nice clean command like the following very much excites me…
gpu.exec(computationFunction, inputParamArray, outputArray, onChangeFunction)
Where onChangeFunction is executed after each instance of computationFunction exits (with or without exception) so that aggregation and intermediate cancellation can be done. Maybe I’m dreaming.

Thanks for the suggestion!

Thanks