The objective of this work is to use a multi-core embedded platform as computing architectures for neural applications relevant to neuromorphic engineering: e.g. robotics, artificial and spiking neural networks. Recently it has been shown how spike-timing-dependent plasticity (STDP) can play a key role in pattern recognition. In particular multiple repeating arbitrary spatiotemporal spike patterns hidden in spike trains can be robustly detected and learned by multiple neurons equipped with spike-timing-dependent plasticity listening to the incoming spike trains. This paper presents an implementation on a biological time scale of STDP algorithm to localize a repeating spatio-temporal spike patterns on a multi-core embedded platform.