Smart technologies for effective reconfiguration: the FASTER approach

Current and future computing systems increasingly require that their functionality stays flexible after the system is operational, in order to cope with changing user requirements and improvements in system features, i.e. changing protocols and data-coding standards, evolving demands for support of different user applications, and newly emerging applications in communication, computing and consumer electronics. Therefore, extending the functionality and the lifetime of products requires the addition of new functionality to track and satisfy the customers needs and market and technology trends. Many contemporary products along with the software part incorporate hardware accelerators for reasons of performance and power efficiency. While adaptivity of software is straightforward, adaptation of the hardware to changing requirements constitutes a challenging problem requiring delicate solutions. The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) project aims at introducing a complete methodology to allow designers to easily implement a system specification on a platform which includes a general purpose processor combined with multiple accelerators running on an FPGA, taking as input a high-level description and fully exploiting, both at design time and at run time, the capabilities of partial dynamic reconfiguration. The goal is that for selected application domains, the FASTER toolchain will be able to reduce the design and verification time of complex reconfigurable systems providing additional novel verification features that are not available in existing tool flows

MARTE based modeling approach for Partial Dynamic Reconfigurable FPGAs

International audienceAs System-on-Chip (SoC) architectures become pivotal for designing embedded systems, the SoC design complexity continues to increase exponentially necessitating the need to find new design methodologies. In this paper we present a novel SoC co-design methodology based on Model Driven Engineering using the MARTE (Modeling and Analysis of Real-time and Embedded Systems) standard. This methodology is utilized to model fine grain reconfigurable architectures such as FPGAs and extends the standard to integrate new features such as Partial Dynamic Reconfiguration supported by modern FPGAs. The goal is to carry out modeling at a high abstraction level expressed in UML (Unified Modeling Language) and following transformations of these models, automatically generate the code necessary for FPGA implementation

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

© 2016 Cheung, Schultz and Luk.NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation

From MARTE to dynamically reconfigurable FPGAs : Introduction of a control extension in a model based design flow

System-on-Chip (SoC) can be considered as a particular case of embedded systems and has rapidly became a de-facto solution for implement- ing these complex systems. However, due to the continuous exponential rise in SoC's design complexity, there is a critical need to find new seamless method- ologies and tools to handle the SoC co-design aspects. This paper addresses this issue and proposes a novel SoC co-design methodology based on Model Driven Engineering (MDE) and the MARTE (Modeling and Analysis of Real-Time and Embedded Systems) standard proposed by OMG (Object Management Group), in order to raise the design abstraction levels. Extensions of this standard have enabled us to move from high level specifications to execution platforms such as reconfigurable FPGAs; and allow to implement the notion of Partial Dy- namic Reconfiguration supported by current FPGAs. The overall objective is to carry out system modeling at a high abstraction level expressed in UML (Unified Modeling Language); and afterwards, transform these high level mod- els into detailed enriched lower level models in order to automatically generate the necessary code for final FPGA synthesis