Відео

LOW PROJECT !!

Bambi was a pioneer of sorts in the NLE arena.

Awesome, thank you. 14:56 Black Mirror S05E03: Rachel, Jack and Ashley Too

Super interesting thanks

Why would you need 44100^3 nodes to simulate wave propagation in a 1m^3 space? The speed of sound is 340 m/s so I would assume you need more like (44100/340)^3 nodes per cubic meter?

This is the area I want to work. This is the video I needed. I also did the simple filter of Jan, and ran it in Ableton. It was an amazing feeling. I will pursue this feeling. Thank you Jan.

mojo :P

17:08 I was wondering if I use cppyy in a python project can i have the speed of c++ in python? like in a flask project.

Interesting and Brilliant study

A little question, in 3d real time, delays might change if the character move, could this provoke pitch modulation ? Do we have to make special delay that blend to a different time without pitch modulation ? Or the effect of those modulation/interpolation are not so much pronounced at normal speed ?

on 12:30 regarding "Linear complexity" is it linear or Exponential, because we multiply three variables in sequence: refl. depth * triangles & rays.

Def. good discussion. Would love to see Binaural simulation as well, because most of us today use headphones when listening to music or gaming… maybe not so much when watching a movie but 80% of the time we deal with headphones.

I love your content and energy. Can't wait to see more!

Are IIR filters are worth it, given the fact that FIR filters can use SIMD very efficiently with good implementation? Latency isn't that much of a problem. 64 tap filter (2x) is like 1.5ms roundtrip and is pretty much negligible, unless there are lots of oversampled plugins in a chain. Also, going past 128 taps for oversampling is way beyond diminishing returns, so might aswell not bother. High order IIRs are prone to numerical issues and are way harder for CPUs, because they include long dependency chains in it's computations. FIRs don't have that problem at all IF implemented correctly. Ah, and yes, min-phase FIRs are possible as well, and their implementation is pretty much identical other than the fact that the kernel must be min-phased. But latency benefits are not all that great. Also, multistage oversampling is kinda not worth it, single stage is simpler to design and performance is pretty much the same if not better.

GG

Very interesting and provides a lot of knowledge. Thanks man!

GRRRRRRRREAT Stuff, Sam. Thanks!!

Andrew what a genius

I’d like to remind the author that oversampling and upsampling are different concepts

Is this presentation available for download?

Got questions? Leave them here and I’ll do my best to answer!

Incredible I have a project perfect for this

this is amazing! the node-based design is really well thought through, reminds me of comfyui. very nice work, Changhun!

I am currently in Bulgaria - Sofia. I am from Turkey. I work as a software engineer here. I want to pursue a career in C++ audio, as an audio/software engineer. I am also very familiar with music production. I love programming and I love music production. Combination of this is my ikigai. I love the idea of making music plugins. There are not much possibilities here about the position I want to work. I feel like I should improve my C++ skills because my daily job includes only Kotlin. The C++ jobs require a strong foundation about the language. I just felt like saying all of this because I wanted to let it out. :D GREAT EVENT! I hope I can join one day.

Where is Naud available? I don't see any information about it on the Supertone website, or anywhere else for that matter. I work a lot with modular audio design so the concept appeals to me.

Seriously - why would I want to use web tech in anything related to audio?

How do get in on the beta? The Twitter account has been suspended and there is no mention of Naud anywhere on the website?

been waiting on this !!!

Wow, this seems really cool, I don't have the head for code or the resources probably to pay for the niche programming courses but I would like to be able to make a few plugins to see how it all works, this could be amazing for peeps like me! Wehoo! ;D

1st comment! It's a sign! 🥰

Can we try it out somewhere?

Very very nice!

What’s wrong with Max ?! It’s already very rich in objects. Even neuronal networks are possible with flucoma for example?! That’s ML as well. I wonder what they are doing better

Loved the talk. Masterclass in spatial audio!

Thank you! Great presentation

This is really cool, thanks!.

This lecture is full of useful intuitions, thanks!

I wish he went into how to build an interface... looking all over for how to do that.

Frequency and Amplitude were huge influences on me growing up. Harmonix has done so much for interactive audio.

Very nice practical introduction to this topic. Thanks!

Very nice and interesting presentation. Have you tried anything around gamaks? I find it hard to visualise how it could be coded since it can get very complex for many raag.

This is really cool, excited to see how this develops

This was such a promising talk!

This is such a great talk, packed with information!

Here is a summary of the talk with timestamps: Introduction @00:00 Speaker is Gusta Anderson, senior software dev at Elk Audio Elk Audio makes Elk Audio OS (Linux-based OS for musical instruments) and Elk Live (low latency online music collaboration tool) Optimizing DSP code with compiler assistance @01:00 Readability and clarity should be prioritized, but code should express intent so compiler can optimize Collapsing abstractions: abstractions like loops, functions, classes should disappear when compiling What affects performance @05:29 CPU bound, memory bound, pipeline bound (long dependency chains) What compilers do @11:29 Inlining, loop optimization, auto-vectorization, rearranging statements, removing unneeded variables Compilers are good at optimizing, so avoid sacrificing readability prematurely Promoting auto-vectorization @17:39 Loop count should be known at compile time, no control flow in loop Fixed buffer sizes allow better optimization, but many plugin APIs don't support this well Fixed size arrays often faster than dynamic ones like std::vector Inlining and constants @21:01 Functions in headers, especially member functions, are usually inlined Avoid virtual functions in inner loops Be careful with float/double division - multiply by reciprocal if dividing by a constant value Branchless code @26:06 Branchless code is deterministic and doesn't depend on data Compilers can often make simple code branchless, like max(), even in loops - trust the compiler Use optimized math libraries before trying to hand-code branchless algorithms Reducing memory access @31:29 Fastest data is in registers, then cache, then main memory Copying state variables to stack may allow better compiler optimization Aliasing (having multiple pointers to same data) can prevent optimization C++ lacks good "restrict" keyword to indicate no aliasing - raw pointers or compiler extensions needed Handling recursive filters @38:50 Recursive algorithms like IIR filters are hard to optimize due to dependencies Interleaving samples from parallel instances (e.g. stereo) can help Adding delays between cascaded sections allows parallelizing higher-order filters Summary @42:29 Use fixed buffer sizes Ensure functions are inlined Write clear branchless code Exploit parallelism opportunities Benchmark standard library functions Avoid float divisions More resources @43:52 Compiler Explorer, Agner Fog's optimization guides, Elk Audio blog posts, CppCon/ADC talks

Amazing talk, well done :)

Does it do, meends, kampan etc?

Very nice and interesting. I am wondering we should now already also start using Deep Learning and Neural Nets for such compositions. I hope research has started to train Transformer models with Rag and their nuances from our great masters.