Comment by lysace
1 day ago
Nice.
I wonder if 264/520 kB RAM is also enough for a high quality parametric stereo reverb/echo effect? Should fit about 3/6 seconds of uncompressed 16-bit 44.1/48 kHz audio.
Also: Raspberry Pi Ltd - please keep increasing the RAM size in future iterations to unlock even more use cases.
The RP2350 (Pico 2) supports external PSRAM so you can add several MB more there if you need it.
I have always wondered kind of bandwidth you could make by multiple channels of PSRAM driven by PIO/DMA. Individually they're not so speedy(although the APS6408L-OCH-BA seems pretty crazy) , but how many can you run simultaneously. In terms of the RP2350 it would be fascinating to see how many times a second could you replace the entire contents of SRAM.
Can surely get more bandwidth but the it's less useful because it will not be directly accessible by the CPU anymore.
4 replies →
Default specs matter a lot for worldwide availability and affordability, as well as for the willingness of people to spend a lot of time creating free software for it.
520KB of SRAM is actually on the high end for microcontrollers. It doesn't seem like much but SRAM is on-die and significantly lower density than DRAM. For comparison, it's the same type of memory used for CPU caches, which are also small!
You can easily find dev boards with 8MB of PSRAM online if you need it. Or you can buy the PSRAM and hook it up yourself. If you still need more memory than that then you're looking at the wrong chip for the job.
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> high quality parametric stereo reverb/echo effect
I’m sometimes annoyed that the home audio/audiophile world is so separate from the live/professional world.
For playing recordings with fancy effects, you can throw massive overkill CPUs at it with small batches, brutefir style, or you can do high-latency FFT filters, and you can get essentially perfect FIR reverb effects with a latency vs complexity tradeoff.
But the algorithm in the middle exists and is not that exotic. You divide your impulse response into a very short piece at the beginning, then a longer piece after that, then a longer piece after that, in exponentially increasing pieces. And then you add up the results, with straight addition and multiplication for the short one, and (carefully scheduled to avoid stalls) FFT convolution for the long ones, and you get basically arbitrary long FIR filters with logarithmic amortized complexity per sample and as low as zero sample latency if you are so inclined.
I think this is called “non-uniform partitioning” or something to the effect. I’m not aware of any serious, public implementation for audio use.