DSPeed (pronounced dee-ess-speed) is a python-based package that performs bulk, high-performance digital signal processing (DSP) of time-series data such as digitized waveforms. This package is part of the pygama scientific computing suite.

DSPeed enables the user to define an arbitrary chain of vectorized signal processing routines that can be applied in bulk to waveforms and other data provided using the LH5-format. These routines can include numpy ufuncs, custom functions accelerated with numba, or other arbitrary functions. DSPeed will carefully manage file I/O to optimize memory usage and performance. Processing chains are defined using highly portable JSON files that can be applied to data from multiple digitizers.