NIST has conducted testing of one-to-one SDK (Software Development Kit) based COTS (Commercial Off-The-Shelf) fingerprint matching systems to evaluate the accuracy of one-to-one matching used in the US-VISIT program. Fingerprint matching systems from eight vendors not used in US-VISIT were also evaluated to insure that the accuracy of the matcher tested was comparable to the most accurate available COTS products. The SDK based matching application was tested on 12 different single finger data sets of varying difficulty. The average true accept rate (TAR) at a false accept rate (FAR) of 0.01% was better than 98% for the two most accurate systems while the worst TAR at a FAR of 0.01% was greater than 94%. The data sets used and the ranking of the systems are discussed in detail in the report.
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The synthetic‐perturbation screening (SPS) methodology is based on an empirical approach; SPS introduces artificial perturbations into the MIMD program and captures the effects of such perturbations by using the modern branch of statistics called design of experiments. SPS can provide the basis of a powerful tool for screening MIMD programs for performance bottlenecks. This technique is portable across machines and architectures, and scales extremely well on massively parallel processors. The purpose of this paper is to explain the general approach and to extend it to address specific features that are the main source of poor performance on the shared memory programming model. These include performance degradation due to load imbalance and insufficient parallelism, and overhead introduced by synchronizations and by accessing shared data structures. We illustrate the practicality of SPS by demonstrating its use on two very different case studies: a large image understanding benchmark and a parallel quicksort.
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