439 research outputs found

    OPTIMIZING LARGE COMBINATIONAL NETWORKS FOR K-LUT BASED FPGA MAPPING

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    Optimizing by partitioning is a central problem in VLSI design automation, addressing circuit’s manufacturability. Circuit partitioning has multiple applications in VLSI design. One of the most common is that of dividing combinational circuits (usually large ones) that will not fit on a single package among a number of packages. Partitioning is of practical importance for k-LUT based FPGA circuit implementation. In this work is presented multilevel a multi-resource partitioning algorithm for partitioning large combinational circuits in order to efficiently use existing and commercially available FPGAs packagestwo-way partitioning, multi-way partitioning, recursive partitioning, flat partitioning, critical path, cutting cones, bottom-up clusters, top-down min-cut

    A survey of algorithmic methods in IC reverse engineering

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    The discipline of reverse engineering integrated circuits (ICs) is as old as the technology itself. It grew out of the need to analyze competitor’s products and detect possible IP infringements. In recent years, the growing hardware Trojan threat motivated a fresh research interest in the topic. The process of IC reverse engineering comprises two steps: netlist extraction and specification discovery. While the process of netlist extraction is rather well understood and established techniques exist throughout the industry, specification discovery still presents researchers with a plurality of open questions. It therefore remains of particular interest to the scientific community. In this paper, we present a survey of the state of the art in IC reverse engineering while focusing on the specification discovery phase. Furthermore, we list noteworthy existing works on methods and algorithms in the area and discuss open challenges as well as unanswered questions. Therefore, we observe that the state of research on algorithmic methods for specification discovery suffers from the lack of a uniform evaluation approach. We point out the urgent need to develop common research infrastructure, benchmarks, and evaluation metrics

    The Logic of Random Pulses: Stochastic Computing.

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    Recent developments in the field of electronics have produced nano-scale devices whose operation can only be described in probabilistic terms. In contrast with the conventional deterministic computing that has dominated the digital world for decades, we investigate a fundamentally different technique that is probabilistic by nature, namely, stochastic computing (SC). In SC, numbers are represented by bit-streams of 0's and 1's, in which the probability of seeing a 1 denotes the value of the number. The main benefit of SC is that complicated arithmetic computation can be performed by simple logic circuits. For example, a single (logic) AND gate performs multiplication. The dissertation begins with a comprehensive survey of SC and its applications. We highlight its main challenges, which include long computation time and low accuracy, as well as the lack of general design methods. We then address some of the more important challenges. We introduce a new SC design method, called STRAUSS, that generates efficient SC circuits for arbitrary target functions. We then address the problems arising from correlation among stochastic numbers (SNs). In particular, we show that, contrary to general belief, correlation can sometimes serve as a resource in SC design. We also show that unlike conventional circuits, SC circuits can tolerate high error rates and are hence useful in some new applications that involve nondeterministic behavior in the underlying circuitry. Finally, we show how SC's properties can be exploited in the design of an efficient vision chip that is suitable for retinal implants. In particular, we show that SC circuits can directly operate on signals with neural encoding, which eliminates the need for data conversion.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113561/1/alaghi_1.pd

    Taylor Expansion Diagrams: A Canonical Representation for Verification of Data Flow Designs

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    Real Time Fault Detection and Diagnostics Using FPGA-Based Architecture

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    Errors within circuits caused by radiation continue to be an important concern to developers. A new methodology of real time fault detection and diagnostics utilizing FPGA based architectures while under radiation were investigated in this research. The contributions of this research are focused on three areas; a full test platform to evaluate a circuit while under irradiation, an algorithm to detect and diagnose fault locations within a circuit, and finally to characterize Triple Design Triple Modular Redundancy (TDTMR), a new form of TMR. Five different test setups, injected fault test, gamma radiation test, thermal radiation test, optical laser test, and optical flash test, were used to assess the effectiveness of these three research goals. The testing platform was constructed with two FPGA boards, the Device Under Test (DUT) and the controller board, to generate and evaluate specific vector sets sent to the DUT. The testing platform combines a myriad of testing and measuring equipment and work hours onto one small reprogrammable and reusable FPGA. This device was able to be used in multiple test setups. The controlling logic can be interchanged to test multiple circuit designs under various forms of radiation. The detection and diagnostic algorithm was designed to determine fault locations in real time. The algorithm used for diagnosing the fault location uses inverse deductive elimination. By using test generation tools, fault lists were developed. The fault lists were used to narrow \ the possible fault locations within the circuit. The algorithm is able to detect single stuck at faults based on these lists. The algorithm can also detect multiple output errors but not able to diagnose multiple stuck at faults in real time

    Ant colony multi-optimization algorithm for circuit bi-partitioning

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