Scheduling, Binding and Routing System for a Run-Time Reconfigurable Operator Based Multimedia Architecture

International audienceThis article presents an integrated environment for application scheduling, binding and routing used for the run-time reconfigurable, operator based, ROMA multimedia architecture. The environment is very flexible and after a minor modification can support other reconfigurable architectures. Currently, it supports the architecture model composed of a bank of single (double) port memories, two communication networks (with different topologies) and a set of run-time functionally reconfigurable non-pipelined and pipelined operators. The main novelty of this work is simultaneous solving of the scheduling, binding and routing tasks. This frequently generates optimal results, which has been shown by extensive experiments using the constraint programming paradigm. In order to show flexibility of our environment, we have used it in this article for optimization of application scheduling, binding and routing (the case of the non-pipelined execution model) and for space exploration (case of the pipelined execution model)

EPICURE: A partitioning and co-design framework for reconfigurable computing

This paper presents a new design methodology able to bridge the gap between an abstract specification and a heterogeneous reconfigurable architecture. The EPICURE contribution is the result of a joint study on abstraction/refinement methods and a smart reconfigurable architecture within the formal Esterel design tools suite. The original points of this work are: (i) a generic HW/SW interface model, (ii) a specification methodology that handles the control, and includes efficient verification and HW/SW synthesis capabilities, (iii) a method for parallelism exploration based on abstract resources/performance estimation expressed in terms of area/delay tradeoffs, (iv) a HW/SW partitioning approach that refines the specification into explicit HW configurations and the associated SW control. The EPICURE framework shows how a cooperation of complementary methodologies and CAD tools associated with a relevant architecture can signficantly improve the designer productivity, especially in the context of reconfigurable architectures

Ordonnancement, assignation et transformations dynamiques de graphe simultanés pour projeter efficacement des applications sur CGRAs

National audiencePorter une application sur une architecture reconfigurable à gros grain est une tâche complexe qui reste encore souvent réalisée entièrement ou partiellement manuellement. Cet article présente un flot original de synthèse automatisé basé sur des étapes d'ordonnancement et d'assignation simultanées. L'approche proposée parcourt en sens inverse les noeuds du modèle formel extrait à partir du code de l'application compilé pour le transformer dynamiquement uniquement si nécessaire. Les résultats des expériences montrent que l'approche proposée permet une meilleure exploration de l'espace de solution et obtient la meilleure latence dans 90% des cas

Introduction d'aléas dans le processus de projection d'applications sur CGRA

National audienceLes architectures reconfigurables à gros grains offrent un compromis flexibilité-performance intéressant à travers les nombreuses unités de calculs élémentaires qu'elles proposent. Cependant, projeter automatiquement une application sur une architecture reconfigurable à gros grain est un processus complexe qui nécessite d'explorer un vaste espace de solutions. Cet article propose d'étudier l'apport d'aléas dans le processus de projection. L'introduction d'aléas est effectué en particulier dans les étapes d'ordonnancement et d'assignation. Différentes stratégies permettant de garantir un nombre minimum et maximum de solutions sont présentées. Les résultats montrent que notre méthode, couplée à une approche de transformation du graphe d'application, explore mieux l'espace de solutions et permet de trouver la latence la plus courte

Compiler and Architecture Design for Coarse-Grained Programmable Accelerators

abstract: The holy grail of computer hardware across all market segments has been to sustain performance improvement at the same pace as silicon technology scales. As the technology scales and the size of transistors shrinks, the power consumption and energy usage per transistor decrease. On the other hand, the transistor density increases significantly by technology scaling. Due to technology factors, the reduction in power consumption per transistor is not sufficient to offset the increase in power consumption per unit area. Therefore, to improve performance, increasing energy-efficiency must be addressed at all design levels from circuit level to application and algorithm levels. At architectural level, one promising approach is to populate the system with hardware accelerators each optimized for a specific task. One drawback of hardware accelerators is that they are not programmable. Therefore, their utilization can be low as they perform one specific function. Using software programmable accelerators is an alternative approach to achieve high energy-efficiency and programmability. Due to intrinsic characteristics of software accelerators, they can exploit both instruction level parallelism and data level parallelism. Coarse-Grained Reconfigurable Architecture (CGRA) is a software programmable accelerator consists of a number of word-level functional units. Motivated by promising characteristics of software programmable accelerators, the potentials of CGRAs in future computing platforms is studied and an end-to-end CGRA research framework is developed. This framework consists of three different aspects: CGRA architectural design, integration in a computing system, and CGRA compiler. First, the design and implementation of a CGRA and its instruction set is presented. This design is then modeled in a cycle accurate system simulator. The simulation platform enables us to investigate several problems associated with a CGRA when it is deployed as an accelerator in a computing system. Next, the problem of mapping a compute intensive region of a program to CGRAs is formulated. From this formulation, several efficient algorithms are developed which effectively utilize CGRA scarce resources very well to minimize the running time of input applications. Finally, these mapping algorithms are integrated in a compiler framework to construct a compiler for CGRADissertation/ThesisDoctoral Dissertation Computer Science 201

EPICURE : A Partitioning and CoDesign Framework For Reconfigurable Computing

This paper presents a new global design methodology capable to bridge the gap between an abstract specification level and a heterogeneous reconfigurable architecture level. The Epicure contribution is the result of a joint study on abstraction/refinement methods and a smart reconfigurable architecture within the formal Esterel design tools suite. The original points of this work are : i) a generic HW/SW interface model, ii) a specification methodology that handles the control, includes efficient verification and HW/SW synthesis capabilities, iii) a method for parallelism exploration based on abstract resources/performance estimation expressed in terms of area/delay tradeoffs, iv) a HW/SW partitioning approach that refines the specification into explicit HW configurations and the associated SW control. The Epicure framework shows how a cooperation of complementary methodologies and CAD tools associated with a relevant architecture can significantly improve the designer productivity, especially in the context of reconfigurable architectures

An embedded system supporting dynamic partial reconfiguration of hardware resources for morphological image processing

Processors for high-performance computing applications are generally designed with a focus on high clock rates, parallelism of operations and high communication bandwidth, often at the expense of large power consumption. However, the emphasis of many embedded systems and untethered devices is on minimal hardware requirements and reduced power consumption. With the incessant growth of computational needs for embedded applications, which contradict chip power and area needs, the burden is put on the hardware designers to come up with designs that optimize power and area requirements. This thesis investigates the efficient design of an embedded system for morphological image processing applications on Xilinx FPGAs (Field Programmable Gate Array) by optimizing both area and power usage while delivering high performance. The design leverages a unique capability of FPGAs called dynamic partial reconfiguration (DPR) which allows changing the hardware configuration of silicon pieces at runtime. DPR allows regions of the FPGA to be reprogrammed with new functionality while applications are still running in the remainder of the device. The main aim of this thesis is to design an embedded system for morphological image processing by accounting for real time and area constraints as compared to a statically configured FPGA. IP (Intellectual Property) cores are synthesized for both static and dynamic time. DPR enables instantiation of more hardware logic over a period of time on an existing device by time-multiplexing the hardware realization of functions. A comparison of power consumption is presented for the statically and dynamically reconfigured designs. Finally, a performance comparison is included for the implementation of the respective algorithms on a hardwired ARM processor as well as on another general-purpose processor. The results prove the viability of DPR for morphological image processing applications

Hardware implementation of intelligent systems

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