EURETILE D7.3 - Dynamic DAL benchmark coding, measurements on MPI version of DPSNN-STDP (distributed plastic spiking neural net) and improvements to other DAL codes

TL;DR

This paper presents the development and measurement of a dynamic DAL benchmark on an MPI version of DPSNN-STDP, aiming to improve distributed neural network codes for future many-tile systems.

Contribution

It introduces new benchmark coding techniques and performance measurements for distributed neural network simulations on tiled architectures.

Findings

Enhanced performance of MPI-based DPSNN-STDP

Benchmarking results on dynamic workloads

Improvements to DAL codes for neural simulations

Abstract

The EURETILE project required the selection and coding of a set of dedicated benchmarks. The project is about the software and hardware architecture of future many-tile distributed fault-tolerant systems. We focus on dynamic workloads characterised by heavy numerical processing requirements. The ambition is to identify common techniques that could be applied to both the Embedded Systems and HPC domains. This document is the first public deliverable of Work Package 7: Challenging Tiled Applications.