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Issue No. 01 - Jan. (2013 vol. 62)
ISSN: 0018-9340
pp: 163-172
Fabrizio Lombardi , The University of Nottingham Malaysia Campus, Selangor
T. Nandha Kumar , Notheastern University, Boston
ABSTRACT
This paper presents a new method for generating configurations for application-dependent testing of a SRAM-based FPGA interconnect. This method connects an activating input to multiple nets, thus generating activating test vectors for detecting stuck-at, open, and bridging faults. This arrangement permits a reduction in the number of redundant configurations, thus also achieving a reduction in test time for application-dependent testing at full fault coverage. As the underlying solution requires an exponential complexity, a heuristic algorithm that is polynomial and greedy in nature (based on sorting) is used for net selection in the configuration generation process. It is proved that this algorithm has an execution complexity of O(L^3 ) (where L is the number of LUTs in the design). The proposed method requires at most {\rm log}_{2}(M+2) configurations (where M denotes the number of activating inputs) as Walsh coding is employed. Moreover, it is scalable with respect to LUT inputs. Extensive logic-based simulation results are provided for ISCAS89 sequential benchmark designs implemented on Xilinx Virtex4 FPGAs; these results shows that the proposed method achieves a considerable reduction in the number of test configurations compared with methods found in the technical literature (on average, a reduction of 49.5 percent).
INDEX TERMS
Table lookup, Vectors, Field programmable gate arrays, Circuit faults, Testing, Integrated circuit interconnections, Complexity theory, configuration generation, Field programmable gate array (FPGA), interconnect testing, multiple fault detection, test configurations
CITATION
Fabrizio Lombardi, T. Nandha Kumar, "A Novel Heuristic Method for Application-Dependent Testing of a SRAM-Based FPGA Interconnect", IEEE Transactions on Computers, vol. 62, no. , pp. 163-172, Jan. 2013, doi:10.1109/TC.2011.247
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