Once BlinkenSort successfully showed fascinatingly complex sorting algorithms on an LED strip using an ESP8266 (see other article), I naturally ventured to add the sound output from the Sound of Sorting program. This turned out much harder than initially thought, because the sound generation software required more processing power than available in the cheap standard microcontrollers. After much trail and error, I found out that a sufficiently new Raspberry Pi (I happened to have a Pi 3 model B) has the rare combination of enough compute power, can drive an LED strip directly via SPI, and has an audio line-out.

The Raspberry Pi, however, cannot drive the same type of LED strip reliably as the ESP8266 can, because the Raspberry Pi runs a time-shared Linux system instead of a real-time program. But it can drive the more expensive APA102 or SK9822 LEDs which have a separate clock line. These are 4-pin LED strips with clock and data, which can easily be attached to the Pi's SPI output pins. Furthermore, the APA102 LEDs can be driven at a much higher refresh rate than the WS2812B and SK6812, due to the extra clock signal. This ultimately makes the sorting animations even smoother than with the ESP8266 (where the frame rate is already unnoticeable). I could not find any off-the-shelf library to drive the APA102 with a C++ program on the Pi, but it was trivial to write a frame buffer class and access the /dev/spi0.0 devices directly.

Then there was the question of adding a display. And after more experimentation, I found the MAX7219 dot LED matrix modules work well. These can also be driven by SPI from the Pi, which actually has two SPI outputs on the models with 40 pins. And as a bonus these dot LED matrix models can pull off an amazing frame rate. That means that besides showing the algorithm name, the super-fast refresh rate enables displaying of (nearly) every comparison counter increment, despite the human viewer only being able to see around 25 changes per second. Simply adding a HDMI display to the Pi would have also worked, but the LED matrix is cooler and has a retro feeling to it.

As you can see in the following YouTube video, each algorithm does something quite different which makes this a very interesting art installation with deep connections to informatics. BlinkenSort currently contains the following eighteen sorting algorithms (listed in the same order as in the video): MergeSort, Insertion Sort, QuickSort (LR) Hoare, QuickSort (LL) Lomoto, QuickSort Dual Pivot, ShellSort, HeapSort, CycleSort, RadixSort-MSD (High First), RadixSort-LSD (Low First), std::sort, std::stable_sort, WikiSort, TimSort, Selection Sort, Bubble Sort, Cocktail-Shaker Sort, and BozoSort. Besides sorting algorithms the collection also contains four hash table implementations: Linear Probing Hash Table, Quadratic Probing Hash Table, Cuckoo-Hashing with two places, and Cuckoo-Hashing with three places.

The video above (https://youtu.be/kAjQ8shElP8) shows the LED strip with sound in action and I added a voice-over commentary about the algorithms. There is also a second YouTube video available, without my commentary.

All source code for the sorting algorithms and other Neopixel animations is available from Github:
https://github.com/bingmann/BlinkenAlgorithms.git

About two years ago I first got my hands on one of the fancy addressable "Neopixel" LED strips, which can be programmed to show colorful animations. I quickly saw there was one project I just had to do with these strips: use them to display sorting algorithms as animations. Since my Sound of Sorting project already contained the source code for many algorithms, the step to using an addressable LED strip as a "display" was not a large one. The strips can be animated using microcontrollers such as the Arduino or Espressif ESP chips, which have way enough compute power for running sorting algorithms on a few hundred items. Since all sorting algorithms run on random input data and may make random decisions themselves, the shown animations are near infinitely varying and fascinatingly complex.

The outcome of my project of displaying sorting algorithms on LED strips are two pieces of art:

• "BlinkenSort", which are sorting algorithms animated on SK6812 RGBW LEDs using an ESP8266 microcontroller, is described in this article.
• "BlinkenSort with Sound", which are sorting algorithms animated using APA102 RGB LEDs and a Raspberry Pi 3 with real-time sound, is detailed in a second blog article!

For both projects I created a YouTube video and provide a construction manual on this website if you are interested in the internals or want to build something similar.

Our paper "Engineering Parallel String Sorting" was accepted for publication in Springer's Algorithmica Journal, and is available online at http://dx.doi.org/10.1007/s00453-015-0071-1.

Compare to our older technical report, the journal edition contains many (minor and major) corrections, additional references and better explanations.

A pre-print version is available here: Engineering-Parallel-String-Sorting.pdf .

Please refer to the main parallel-string-sorting page for details and source code.

Some time last week my YouTube video "15 Sorting Algorithms in 6 Minutes" reached 1 million views. The original video was uploaded on 2013-05-20 which is just 524 days ago, so on average about every 45.2 seconds someone started to watch the video (which itself is about 6 minutes long). The world is a really big place. Most of the views, however, occured in spikes of interest, as seen in the graph below.

The original video contained only 15 algorithms. The program "Sound of Sorting" itself, which was used to create the animations, now contains 30 algorithms or variants. For some of the additional algorithms I also created videos on YouTube, which are also worthwhile watching.

There are two parallel algorithms based on sorting networks, where each left-to-right sweep is one parallel sorting step:

• Batcher's Odd-Event Mergesort and Batcher's Bitonic Sort

An algorithm, which is optimal in terms of the number of writes to sort the array:

• Cycle Sort

An adaptive sorting algorithm which detects presorted areas, and is used in many modern programming language runtime libraries:

• Tim Sort

An in-place stable mergesort with O(1) extra space:

• Block Merge Sort (WikiSort)

And two algorithms, that have a high asymptotic worst-case complexity, and are thus more a joke, but still pretty to watch:

• Slow Sort and Stooge Sort

This short post announces the second public version of our parallel string sorting project. It is a test framework and algorithm collection containing most sequential and parallel string sorting implementations.

The collection includes parallel super scalar string sample sort (pS⁵), which we developed and showed to have the highest parallel speedups on modern single-socket multi-core shared memory systems. Additionally, the collection now contains parallel multiway LCP-mergesort, which can be used to speed up string sorting on NUMA multi-socket machines.

See the parallel-string-sorting project page for our technical report and more information about version 0.6.

Little did I expect what would happen when coding the Sound of Sorting demo program. The initial motivation was to create a program that counts the number of comparisons of sorting algorithms, so that the students in our lecture "Algorithms 1" could compare the results of theoretical analysis and real implementations. There were many programs similar to the one I finally made, but there was no program in which the sorting algorithms were easily readable, and not entwined with visualization code. I needed the third-year students to see "simple" code and at the same time have comparison counting and nice visualizations. And none of the existing programs highlighted the internal workings of the algorithms well.

These were the initial goals what became the Sound of Sorting. The program itself took only about seven days of coding work, which was done from the 17th to 21st of May this year. The program had to be finished for the lecture on the 22nd, so there was a hard deadline to meet. The videos were created on the following weekends, and additional algorithms were added later.

Adding sound effects was very much an afterthought, because I had done some similar work previously with manipulating waveforms. Thus there was no learning curve to overcome to have comparisons play sounds. What kind of sound to play, however, needed a lot of artistic touch, trial and error, and the ability to map and transform frequency, oscillators and envelopes as needed. Forming, mixing and bending sound waves as done in the Sound of Sorting requires a mathematical mindset and some appropriate background.

The by-product of this demo program for teaching sort algorithms was the YouTube video "15 Sorting Algorithms in 6 Minutes" which, to my great surprise, went viral on social networks and was viewed 420.000 times to-date. I'm glad that many people with otherwise no connections to algorithmics find this video interesting, and hope that those with further interest view the slower videos, which provide more insight into the algorithms.

Today, the video infected the front page of my current employer: the Department of Informatics at the Karlsruhe Institute of Technology (KIT), which is of course whom I originally made the demo program for. The text, which I wrote for that occasion, can be viewed in German at the original news article about the viral video (or in the screenshots below). I have translated it into English below, since it contains some further comments about the video.

This post announces the publication of my demo program for integer string sorting algorithms, called "The Sound of Sorting". It both visualizes the internals of sorting algorithms, and generates sound effects from the values being compared!

The demo is implemented using the cross-platform toolkits wxWidgets and SDL, can be executed on Windows, Linux and Mac, and runs in real time.

There are also many videos of the sorting algorithm on my new YouTube channel.

See the Sound of Sorting project page for the demo program and source code, and more information about version 0.6.

This short post announces the first public version of our parallel string sorting project. It is a test framework and algorithm collection containing many sequential and parallel string sorting implementations.

The collection includes parallel super scalar string sample sort (pS⁵), which we developed and showed to have the highest parallel speedups on modern multi-core shared memory systems.

See the parallel-string-sorting project page for our technical report and more information about version 0.5.