%0 Journal Article
%T Runtime Scheduling, Allocation, and Execution of Real-Time Hardware Tasks onto Xilinx FPGAs Subject to Fault Occurrence
%A Xabier Iturbe
%A Khaled Benkrid
%A Chuan Hong
%A Ali Ebrahim
%A Tughrul Arslan
%A Imanol Martinez
%J International Journal of Reconfigurable Computing
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/905057
%X This paper describes a novel way to exploit the computation capabilities delivered by modern Field-Programmable Gate Arrays (FPGAs), not only towards a higher performance, but also towards an improved reliability. Computation-specific pieces of circuitry are dynamically scheduled and allocated to different resources on the chip based on a set of novel algorithms which are described in detail in this article. These algorithms consider most of the technological constraints existing in modern partially reconfigurable FPGAs as well as spontaneously occurring faults and emerging permanent damage in the silicon substrate of the chip. In addition, the algorithms target other important aspects such as communications and synchronization among the different computations that are carried out, either concurrently or at different times. The effectiveness of the proposed algorithms is tested by means of a wide range of synthetic simulations, and, notably, a proof-of-concept implementation of them using real FPGA hardware is outlined. 1. Introduction Dynamic Partial Reconfiguration (DPR) permits to adjust some logic resources on FPGA chips at runtime, whilst the rest are still performing active computations. During the last few years, DPR has become a hot research topic with the objective of building more reliable, efficient, and powerful electronic systems. Indeed, DPR is the enabling technology for a new computing paradigm which combines computation in time and space [1¨C3]. In Reconfigurable Computing (RC), a battery of computation-specific circuits (ˇ°hardware tasksˇ±) is swapped in and out of the FPGA on demand to hold a continuous stream of input operands, computation, and output results. Multitasking, adaptation, and specialization are key properties in RC, as multiple swappable tasks can run concurrently at different positions on chip, each with custom data paths for efficient execution of specific computations. Besides task switching, DPR makes it possible to deal with the increasing fault rate currently observed in advanced electronic devices [4] in a more reliable way than ASICs do. While the latter, traditionally, simply tolerates the fault effect by using redundancy, FPGAs permit to route around damaged resources on-the-fly, keeping the system fault-free at all times [5]. However, DPR penetration in the commercial market is still testimonial, mainly due to the lack of suitable high-level design tools to exploit this technology. Indeed, currently, special skills are required to successfully develop a dynamically reconfigurable application. In light of the
%U http://www.hindawi.com/journals/ijrc/2013/905057/