[Archit3ch]

The sentiment in the title resonates, but for consumer GPUs (the article is about server cards).

The recently leaked M5 benchmarks reveal a 35% faster GPU. These improvements compound, so you can get a GPU that's effectively twice as fast by waiting a couple of years.

Modern GPUs are the equivalent of local supercomputers, but the drivers, languages and libraries are still playing catch up. Imagine the audio processing you could do if only you could target that hardware.

[bigyabai]

Apple gives developers almost all the compute drivers you could want from them. If you can't express your GPU acceleration as a Metal Compute Shader, you probably aren't leaving any GPU horsepower on the table. ANE and MLX will get exposed in higher-level CoreML frameworks, everyone should be happy.

35% raster improvements, it's worth noting, is not super impressive on the GPU side of things. Most raster compute is a square function, to double your render resolution you need a 4x the GPU power (on-paper) to handle the pixel count. That's what, six years of annual iteration? A large component of Apple and AMD's inability to break into Nvidia's CUDA empire is their obsession over raster optimization in a world where DLSS and FSR exists. It's a noble pursuit, but even as a gamer I've gotta admit they're wasting their time. We have software methods that can close the gap in render quality between $100 GPUs and $1000 GPUs, but no such solution for GPGPU compute.

[QuantumNoodle]

> Imagine the audio processing you could do if only you could target that hardware.

That's an interesting thought. Commercial grade signal processing rely on FPGAs and the Fintech field adapted them for high frequency trading. I wonder if we will see signal processing enabled on GPUs for consumers if the GPU drivers were more open.

[Agentlien]

It should definitely be possible already using CUDA or computer shaders. From a theoretical view computer graphics is signal processing but with a signal consisting of up to four color channels across two dimensions. This is the view taken in a lot of papers and practical implementations. After all, a lot of computer graphics is about applying filters (post-processing) such as color grading, anti-aliasing, etc. to this signal.

So, in a very real sense, signal processing is exactly what the GPU is built for and primarily used for.

[djmips]

I recall there have been some efforts in audio DSP on GPUs, the audio bandwidth is low so even transporting the results back to the CPU to be played could be done fast enough to maintain a usable latency.