This year, Lego published a set based on the Bugatti Chiron, one of the craziest cars, and built near my home town. It’s the second set in the Technic car collection series, and contrary to the Porsche, the color is inspired by a gorgeous real life car (I don’t think that the real Porsche exists…).
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.
A decade ago, the objective was to have a build farm and do continuous integration (on each commit, build the application and run unit tests). Now, the objective is continuous delivery. This means that the new build is directly put into production. All the major applications are doing this, from Chrome to Spotify. You may not get every version on your machine, but you should consider a build as something you could deploy.
The nice thing is that there are tools to ease this workflow.
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.
Recently, at work, I encountered a strange bug with GCC 7.2 and clang 6 (I didn’t test it with Visual Studio 2017 for different reasons). The bug was not visible on “old” compilers like gcc 4, Visual Studio 2013 or even Intel Compiler 2017. In debug mode, everything was fine, but in release mode, the application crashed. But not always at the same location.
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.