Reconfigurable computing | EPFL Graph Search

Reconfigurable computing is a computer architecture combining some of the flexibility of software with the high performance of hardware by processing with very flexible high speed computing fabrics like field-programmable gate arrays (FPGAs). The principal difference when compared to using ordinary microprocessors is the ability to make substantial changes to the datapath itself in addition to the control flow. On the other hand, the main difference from custom hardware, i.e. application-specific integrated circuits (ASICs) is the possibility to adapt the hardware during runtime by "loading" a new circuit on the reconfigurable fabric. History The concept of reconfigurable computing has existed since the 1960s, when Gerald Estrin's paper proposed the concept of a computer made of a standard processor and an array of "reconfigurable" hardware. The main processor would control the behavior of the reconfigurable hardware. The latter would then be tailored to perform a specific t

A Fast Parallel Matrix Multiplication Reconfigurable Unit Utilized In Face Recognitions Systems

Ioannis Sotiropoulos

In this paper we present a reconfigurable device which significantly improves the execution time of the most computational intensive functions of three of the most widely used face recognition algorithms; those tasks multiply very large dense matrices. The presented architecture utilizes numerous digital signal processing units (DSPs) organized in a parallel manner within a state-of-the-art FPGA device. In order to accelerate those functions we have implemented a "blocked" matrix multiplication algorithm which multiplies certain sub-matrices of fixed-point 32-bit numbers; the size of the sub-matrices has been selected so as to fully exploit the resources of the underlying reconfigurable device. Our system is up to 550 times faster than a conventional general purpose processor when implementing the most CPU intensive parts of a number of very widely used Face Identification Schemes, whereas it is more than 40 times faster than the similar schemes implemented in reconfigurable devices. Moreover, our system is general enough so as to be efficiently utilized in any application incorporating fixed-point matrix multiplications.

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EPICURE : A Partitioning and CoDesign Framework For Reconfigurable Computing

Sébastien Bilavarn

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.

2006

Hardware / Software Architectural and Technological Exploration for Energy-Efficient and Reliable Biomedical Devices

Loris Gérard Duch

Nowadays, the ubiquity of smart appliances in our everyday lives is increasingly strengthening the links between humans and machines. Beyond making our lives easier and more convenient, smart devices are now playing an important role in personalized healthcare delivery. This technological breakthrough is particularly relevant in a world where population aging and unhealthy habits have made non-communicable diseases the first leading cause of death worldwide according to international public health organizations. In this context, smart health monitoring systems termed Wireless Body Sensor Nodes (WBSNs), represent a paradigm shift in the healthcare landscape by greatly lowering the cost of long-term monitoring of chronic diseases, as well as improving patients' lifestyles. WBSNs are able to autonomously acquire biological signals and embed on-node Digital Signal Processing (DSP) capabilities to deliver clinically-accurate health diagnoses in real-time, even outside of a hospital environment. Energy efficiency and reliability are fundamental requirements for WBSNs, since they must operate for extended periods of time, while relying on compact batteries. These constraints, in turn, impose carefully designed hardware and software architectures for hosting the execution of complex biomedical applications. In this thesis, I develop and explore novel solutions at the architectural and technological level of the integrated circuit design domain, to enhance the energy efficiency and reliability of current WBSNs. Firstly, following a top-down approach driven by the characteristics of biomedical algorithms, I perform an architectural exploration of a heterogeneous and reconfigurable computing platform devoted to bio-signal analysis. By interfacing a shared Coarse-Grained Reconfigurable Array (CGRA) accelerator, this domain-specific platform can achieve higher performance and energy savings, beyond the capabilities offered by a baseline multi-processor system. More precisely, I propose three CGRA architectures, each contributing differently to the maximization of the application parallelization. The proposed Single, Multi and Interleaved-Datapath CGRA designs allow the developed platform to achieve substantial energy savings of up to 37%, when executing complex biomedical applications, with respect to a multi-core-only platform. Secondly, I investigate how the modeling of technology reliability issues in logic and memory components can be exploited to adequately adjust the frequency and supply voltage of a circuit, with the aim of optimizing its computing performance and energy efficiency. To this end, I propose a novel framework for workload-dependent Bias Temperature Instability (BTI) impact analysis on biomedical application results quality. Remarkably, the framework is able to determine the range of safe circuit operating frequencies without introducing worst-case guard bands. Experiments highlight the possibility to safely raise the frequency up to 101% above the maximum obtained with the classical static timing analysis. Finally, through the study of several well-known biomedical algorithms, I propose an approach allowing energy savings by dynamically and unequally protecting an under-powered data memory in a new way compared to regular error protection schemes. This solution relies on the Dynamic eRror compEnsation And Masking (DREAM) technique that reduces by approximately 21% the energy consumed by traditional error correction codes.

EPFL2018

Hardware / Software Architectural and Technological Exploration for Energy-Efficient and Reliable Biomedical Devices

Loris Gérard Duch

EPFL2018