Audio ToolKit started with only C++11 a long time ago, and now with version 3.1, it’s going to be full C++17.
I have tried to find the proper receipts to compile on the fly C++ code with clang and LLVM. It’s actually not that easy to achieve if you are not targeting LLVM Intermediate Representation, and unfortunately, the code here, working for LLVM 7, may not work for LLVM 8. Or 6.
A few year ago, Packt Publishing contacted to be a technical reviewer for the first edition of Building Machine Learning Systems with Python, and I was impressed by the writing of Luis Pedro Coelho and Willi Richert. For the second edition, I was again a technical reviewer.
Writing is not easy, especially when it’s not your mother tongue, and scientific books are plagued with books that are not that great, with low technical content or bad English (that can be said for novels as well, the worst I ever read probably being the Hunger games series…). Even if I don’t like the books, I know that the authors did their best, having written in the past a book that I can say was not very great in terms of flow. Writing a book always deserves the deepest respect.
After my previous post on SPICE modelling in Python, I need to use a good support example to go up to on the fly compilation in C++. This schema will also require some changes to support more than simple nodal analysis, so this now becomes Modified Nodal Analysis with state equations.
A few month ago, mystran published on KVR a small SPICE simulator for real-time processing. I liked the idea, the drawback being that the code is generic and not tailored like a static version of the optimizer. So I wondered if it was doable. But for this, I have to start from the basics and build from there. So let’s go.
I’m happy to announce the update of ATK Side-Chain Compressor based on the Audio Toolkit and JUCE. It is available on Windows (AVX compatible processors) and OS X (min. 10.9, SSE4.2) in different formats.
This update changes storage format and allows linked channels to be steered by a mix of power coming from each channel, each passing through its own attack-release filter. It enables more creative workflows with makeup gain specific to each channel. The rest of the plugin works as before, with an optional Middle/Side processing as well as side-chain working either on each channel separately or in middle/side.
This plugin requires the universal runtime on Windows, which is automatically deployed with Windows update (see tis discussion on the JUCE forum). If you don’t have it installed, please check Microsoft website.
After the book on LLVM core libraries, I want to have a look at the cookbook.
LLVM has always intrigued me. Actually, I always thought about one day writing a compiler. But it was more a challenge than a requirement for any of my works, private or professional, so never dived into it. The design of LLVM was also very well thought, and probably close to something I would have had liked to create.
So now the easiest is just to use LLVM for the different goals I want to achieve. I recently had to write clang-tidy rules, and I also want to perhaps create a JIT for Audio Toolkit and the modeling libraries. So lots of reasons to look at LLVM.
I started taking a heavier interest in clang-tidy a few months ago, as I was looking at static analyzers. I found at the time that it was quite complicated to work on clang internal AST. It is a wonderful tool, but it is also a very complex one. Thankfully, the cfe-dev mailing list is full of nice people.
I also started my journey in the LLVM/clang land with the help of this blog post.