**Benchmarking a Many-Core Neuromorphic Platform With an MPI-Based DNA Sequence Matching Algorithm**

**Gianvito Urgese 1,\* , Francesco Barchi <sup>2</sup> , Emanuele Parisi <sup>2</sup> , Evelina Forno <sup>2</sup> , Andrea Acquaviva <sup>3</sup> and Enrico Macii <sup>1</sup>**


Received: 29 September 2019; Accepted: 12 November 2019; Published: 14 November 2019

**Abstract:** SpiNNaker is a neuromorphic globally asynchronous locally synchronous (GALS) multi-core architecture designed for simulating a spiking neural network (SNN) in real-time. Several studies have shown that neuromorphic platforms allow flexible and efficient simulations of SNN by exploiting the efficient communication infrastructure optimised for transmitting small packets across the many cores of the platform. However, the effectiveness of neuromorphic platforms in executing massively parallel general-purpose algorithms, while promising, is still to be explored. In this paper, we present an implementation of a parallel DNA sequence matching algorithm implemented by using the MPI programming paradigm ported to the SpiNNaker platform. In our implementation, all cores available in the board are configured for executing in parallel an optimised version of the *Boyer-Moore* (BM) algorithm. Exploiting this application, we benchmarked the SpiNNaker platform in terms of scalability and synchronisation latency. Experimental results indicate that the SpiNNaker parallel architecture allows a linear performance increase with the number of used cores and shows better scalability compared to a general-purpose multi-core computing platform.

**Keywords:** benchmarking neuromorphic HW; neuromorphic platform; spiNNaker; spinMPI; MPI for neuromorphic HW; Boyer-Moore; DNA matching algorithm
