In release 2.2.0, ATK gained new EQ filters that are vectorized. These filters cannot be used to filter different bands from the same input signal (yet), but they can be used to filter in the same way several channels.
I’ve started working on adaptive filtering a long time ago, but could never figure out why my simple implementation of the RLS algorithm failed. Well, there was a typo in the reference book!
Now that this is fixed, let’s see what this guy does.
Recently, I got access to the latest release of Parallel Studio with an update version of Advisor. 6 years after my last review, let’s dive into it again!
Focus on this release was on performance. As such the core functions were optimized, as well as some tools and EQ.
A new filter dedicated to fast convolution (using a fixed-size partition with a mix of FFT convolution and explicit FIR filter) with 0 latency was added.
After my post on HPCToolkit, I felt that I prefered QCacheGrind as a GUI to explore profiling results. So here is a gist with a Python script to convert XML HPCToolkit experiments to callgrind format: https://gist.github.com/mbrucher/6cad31e38beca770523b
For instance, this is a display of an Audio Toolkit test of L2 cache misses:
Convolution is an algorithm that is often used for reverberations. If the equation is easy to understand and to implement, the implementation is costly. The other way of doing it is to use Fast Fourier Transform (FFT), but the direct/crude implementation requires latency. If it is possible to optimize the basic convolution code, it is sometimes more interesting to use a different algorithm, as it is the case here.
I’ve explained in earlier posts how to simulate a simple overdrive circuit. I’ve also explained how I implemented this in QtVST (and yes, I should have added labels on those images!), which was more or less the predecessor of Audio TK.
The main problem with simulating non linear circuits is that it costs a lot. Let’s see if I can improve the timings a little bit.
I’ve looked on github for a good C++ implementation of Cover Trees for nearest-neighbors search, but I didn’t find one. I may have overlooked some repositories, but in the end, implementing it myself wasn’t that difficult.