One further refinement to Piggy is required before I make a release of the tool: a wrapper to get the tool under MSBuild. Like the Antlr4BuildTasks wrapper I forked from Antlr4cs, I want Piggy to work seamlessly during the build of a C# project that uses a native library. My plan is for C# projects to contain the Piggy templates required to generate the declarations for C# of the interface needed by the project. Required by the user would be a template for Piggy and C++ file for the Clang compiler. During a build, the Piggy tool would run and produce C# output in the build directory, compiled and linked with the project. So, instead of users writing the DllImport decls to work with a native library, just indicate what you want and let Piggy do the rest. The build tool would be released to NuGet, and would contain the Clang serializer, the Piggy tool, the assembly wrapper for the Clang serializer and Piggy, and all the build rules.
It never ceases to amaze me how people can write a huge API and never bother to document how to use it. But, it’s been that way for as long as I can remember, going back 35 years. In my latest adventures, I’ve been trying to compile, link, and run C# code dynamically using Roslyn for Piggy, my transformational system. If you’ve ever used Roslyn in C#, you’ve probably discovered that it can be such a pain in the arse to use because Microsoft gives doc for the API, does give some tutorials, but I can’t find a simple example for compiling, linking, and running C#. I don’t need to know all the details yet, just a starting point framework. Unfortunately, the solution is quite sensitive to whether you use Net Core or Net Framework.
In order to better support Piggy, which uses Antlr4, I’ve added a NuGet package called Antlr4BuildTasks. This package is a pared-down derivative of the excellent work of Sam Hartwell Antlr4cs code generator package, and includes just the rules and code needed to do builds in MSBuild, Dotnet, or Visual Studio 2017 IDE–just no Antlr4 tool itself. This package decouples the build rules from the Antlr4 tool and runtime, so you can build Antlr programs using the latest Java-based Antlr tool and runtime release. To use this package, make a reference to this package as if you would to any NuGet package; make sure to also reference the Antlr4.Runtime.Standard package, install Java, the Java-based Antler tool, and set JAVA_HOME and Antlr4ToolPath. The tool works with Net Core, Net Framework, or Net Standard code, and on Windows or Linux.
While I now have Piggy producing a p/invoke header for a Clang-C header file, there are several improvements that I’ve made or will make soon.
With a bit of hacking for the last month or two, and I can finally see that I am making progress on Piggy, a new kind of p/invoke generator. Some might say “Why in the world are you wasting time writing a p/invoke generator? Aren’t there tools already that do this?” Well, yeah, there are other generators, but they all…how should I say…suck! I need a p/invoke generator for Campy, a compiler and runtime for C# for GPUs, which I am still working on, but had to place on the back burner to work on this. Campy uses LLVM and CUDA. Because these libraries are large and constantly changing, I have to have an automated way of handling new releases.
If you’ve been programming in C# for a while, at some point you found yourself needing to call C libraries. It isn’t often, but when you have to do it, it’s like pulling teeth. One option is to set up a C++/CLI interface; the other is a p/invoke interface to a DLL containing the C code. It’s relatively easy to set up a p/invoke interface in your C# code for the C code, which you export with a DLL–if you only need to call a few C functions. But, if the API is large, you stare at the code for a while, deciding whether it is really worth writing out all the declarations you need to make the calls. Many people throw caution to the wind, write packages for large, popular C APIs so you don’t have to, which you can find on the Nuget website. One example is ManagedCuda, an API for CUDA programming from C#. Unfortunately, people get tired of trying to keep these packages up to date, and so these packages become obsolete. Another approach is through automatic means, whereby a tool reads the C++ headers (or DLL) and output the decls you call. A p/invoke generator reads C header files and outputs C# code with the p/invoke declarations that you can include in your code. These tools sometimes work, but often they don’t.
This blog entry is a “heads up” note about my thoughts for a new type of p/invoke generator. Continue reading
For these last few weeks, I’ve been trying to grapple with the problem of p/invoke–the nasty but must-use feature in C#. While one could write these declarations out by hand, some libraries are too large, and change too often, so people use p/invoke generators, like SWIG. However, the is no generator that is easy to use or generates 100% correct C# declarations. So, as every software developer does, so I go to re-invent the wheel.
Lately, I’ve been catching up on some reading. Here are some links to blogs in programming, computer science, and math, which I find interesting and useful. Enjoy. –Ken
I’ve been lax the last six months on my blog, working instead on Campy (a C#/GPU programming language extension). Now that that is slightly under control, time to get back to the blog. And, by the way, the whole reason for Campy is to implement popular algorithms to run on a GPU, I thought I’d take some time to review what information is available on the internet on algorithms. The following is a list I’ve been working on for a few months. It is by no means a complete list. But, I hope it covers some of the more popular sites. The entries are not in any particular order. Note, this list does not include parallel algorithms, which will be a post unto itself, nor the seemingly required AI algorithms you must have nowadays.