Pathfinder

Abstract: Routing FPGAs is a challenging problem because of the relative scarcity of routing resources, both wires and connection points. This can lead either to slow implementations caused by long wiring paths that avoid congestion or a failure to route all signals. This paper presents PathFinder, a router that balances the goals of performance and routability. PathFinder uses an iterative algorithm that converges to a solution in which all signals are routed while achieving close to the optimal performance allowed by the placement. Routability is achieved by forcing signals to negotiate for a resource and thereby determine which signal needs the resource most. Delay is minimized by allowing the more critical signals a greater say in this negotiation. Because PathFinder requires only a directed graph to describe the architecture of routing resources, it adapts readily to a wide variety of FPGA architectures such as Triptych, Xilinx 3000 and mesh-connected arrays of FPGAs. The results of routing ISCAS benchmarks on the Triptych FPGA architecture show an average increase of only 4.5% in critical path delay over the optimum delay for a placement. Routes of ISCAS benchmarks on the Xilinx 3000 architecture show a greater completion rate than commercial tools, as well as 11% faster implementations.

Abstract: The National Oceanic and Atmospheric Administration (NOAA)/NASA Oceans Pathfinder sea surface temperature (SST) data are derived from measurements made by the advanced very high resolution radiometers (AVHRRs) on board the NOAA 7, 9, 11, and 14 polar orbiting satellites. All versions of the Pathfinder SST algorithm are based on the NOAA/National Environmental Satellite Data and Information Service nonlinear SST operational algorithm (NLSST). Improvements to the NLSST operational algorithm developed by the Pathfinder program include the use of monthly calibration coefficients selected on the basis of channel brightness temperature difference (T4–T5). This channel difference is used as a proxy for water vapor regime. The latest version (version 4.2) of the Pathfinder processing includes the use of decision trees to determine objectively pixel cloud contamination and quality level (0–7) of the SST retrieval. The 1985–1998 series of AVHRR global measurements has been reprocessed using the Pathfinder version 4.2 processing protocol and is available at various temporal and spatial resolutions from NASA's Jet Propulsion Laboratory Distributed Active Archive Center. One of the highlights of the Pathfinder program is that in addition to the daily global area coverage fields, a matchup database of coincident in situ buoy and satellite SST observations also is made available for independent algorithm development and validation.

Abstract: Network scaling algorithms such as the Pathfinder algorithm are used to prune many different kinds of networks, including citation networks, random networks, and social networks. However, this algorithm suffers from run time problems for large networks and online processing due to its O(n4) time complexity. In this article, we introduce a new alternative, the MST-Pathfinder algorithm, which will allow us to prune the original network to get its PFNET(∞, n - 1) in just O(n2 · log n) time. The underlying idea comes from the fact that the union (superposition) of all the Minimum Spanning Trees extracted from a given network is equivalent to the PFNET resulting from the Pathfinder algorithm parameterized by a specific set of values (r = ∞ and q = n - 1), those usually considered in many different applications. Although this property is well-known in the literature, it seems that no algorithm based on it has been proposed, up to now, to decrease the high computational cost of the original Pathfinder algorithm. We also present a mathematical proof of the correctness of this new alternative and test its good efficiency in two different case studies: one dedicated to the post-processing of large random graphs, and the other one to a real world case in which medium networks obtained by a cocitation analysis of the scientific domains in different countries are pruned. © 2008 Wiley Periodicals, Inc.

Abstract: Pathfinder is an expert system that assists surgical pathologists with the diagnosis of lymph-node diseases. The program is one of a growing number of normative expert systems that use probability and decision theory to acquire, represent, manipulate, and explain uncertain medical knowledge. In this article, we describe Pathfinder and our research in uncertain-reasoning paradigms that was stimulated by the development of the program. We discuss limitations with early decision-theoretic methods for reasoning under uncertainty and our initial attempts to use non-decision-theoretic methods. Then, we describe experimental and theoretical results that directed us to return to reasoning methods based in probability and decision theory.