But beyond the operating system, computer audio latency is also limited by the sampling rate as well. For example, when recording stereo audio at 44100Hz with 16-bit samples, filling a 1024 byte buffer takes 6ms. A buffer size for sub-millisecond latency would need to be 128 bytes, which is about the size of a memory cache line. This translates to about 32 samples. A very small number for audio effects processing. For example, computing Fourier Transform on a block size this small is not very interesting. This means that in order to achieve zero-latency computer audio effect, the algorithm has to be designed as a stream of samples.

Here I'm just noting two algorithms that are streamable: low-pass and high-pass filters. Both algorithms have a “discrete-time realization” (taken from Wikipedia) as follows:

- Low-pass filter: \[ y_i = \alpha x_i + (1 - \alpha) y_{i-1} \qquad \text{where} \qquad \alpha \triangleq \frac{\Delta_T}{RC + \Delta_T} \]
- High-pass filter: \[ y_i = \alpha y_{i-1} + \alpha (x_{i} - x_{i-1}) \qquad \text{where} \qquad \alpha \triangleq \frac{RC}{RC + \Delta_T} \]

In both cases, the cutoff frequency is \( f_c = \frac{1}{2\pi RC} \), and \( \Delta_T \) is the duration of time between samples (the reciprocal of the sampling rate).