In this era, the requirement of high-performance computing at low power cost can be met by the parallel execution of an application on a large number of programmable cores. Emerging many-core architectures provide dense interconnection fabrics leading to new communication requirements. In particular, the effective exploitation of synchronous and asynchronous channels for fast communication from/to internal cores and external devices is a key issue for these architectures. In this paper, we propose a methodology for clustering sequential commands used for configuring the parallel execution of tasks on a globally asynchronous locally synchronous multi-chip many-core neuromorphic platform. With the purpose of reducing communication costs and maximise the exploitation of the available communication bandwidth, we adapted the Multiple Sequence Alignment (MSA) algorithm for clustering the unicast streams of packets used for the configuration of each core so as to generate a coherent multicast stream that configures all cores at once. In preliminary experiments, we demonstrate how the proposed method can lead up to a 97% reduction in packet transmission thus positively affecting the overall communication cost.
Work-in-Progress: Multiple Alignment of Packet Sequences for Efficient Communication in a Many-Core Neuromorphic System / Urgese, Gianvito; Peres, Luca; Barchi, Francesco; Macii, Enrico; Acquaviva, Andrea. - ELETTRONICO. - (2018). ((Intervento presentato al convegno 2018 International Conference on Compilers, Architectures and Synthesis for Embedded Systems (CASES) nel 2018.
Titolo: | Work-in-Progress: Multiple Alignment of Packet Sequences for Efficient Communication in a Many-Core Neuromorphic System |
Autori: | |
Data di pubblicazione: | 2018 |
Abstract: | In this era, the requirement of high-performance computing at low power cost can be met by the pa...rallel execution of an application on a large number of programmable cores. Emerging many-core architectures provide dense interconnection fabrics leading to new communication requirements. In particular, the effective exploitation of synchronous and asynchronous channels for fast communication from/to internal cores and external devices is a key issue for these architectures. In this paper, we propose a methodology for clustering sequential commands used for configuring the parallel execution of tasks on a globally asynchronous locally synchronous multi-chip many-core neuromorphic platform. With the purpose of reducing communication costs and maximise the exploitation of the available communication bandwidth, we adapted the Multiple Sequence Alignment (MSA) algorithm for clustering the unicast streams of packets used for the configuration of each core so as to generate a coherent multicast stream that configures all cores at once. In preliminary experiments, we demonstrate how the proposed method can lead up to a 97% reduction in packet transmission thus positively affecting the overall communication cost. |
ISBN: | 978-153865564-1 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11583/2713315