An event-based architecture for solving constraint satisfaction problems

Constraint satisfaction problems (CSPs) are typically solved using conventional von Neumann computing architectures. However, these architectures do not reflect the distributed nature of many of these problems and are thus ill-suited to solving them. In this paper we present a hybrid analog/digital hardware architecture specifically designed to solve such problems. We cast CSPs as networks of stereotyped multi-stable oscillatory elements that communicate using digital pulses, or events. The oscillatory elements are implemented using analog non-stochastic circuits. The non-repeating phase relations among the oscillatory elements drive the exploration of the solution space. We show that this hardware architecture can yield state-of-the-art performance on a number of CSPs under reasonable assumptions on the implementation. We present measurements from a prototype electronic chip to demonstrate that a physical implementation of the proposed architecture is robust to practical non-idealities and to validate the theory proposed.Comment: First two authors contributed equally to this wor

MINIMALIST: An Environment for the Synthesis, Verification and Testability of Burst-Mode Asynchronous Machines

MINIMALIST is a new extensible environment for the synthesis and verification of burst-mode asynchronous finite-state machines. MINIMALIST embodies a complete technology-independent synthesis path, with state-of-the-art exact and heuristic asynchronous synthesis algorithms, e.g.optimal state assignment (CHASM), two-level hazard-free logic minimization (HFMIN, ESPRESSO-HF, and IMPYMIN), and synthesis-for-testability. Unlike other asynchronous synthesis packages, MINIMALIST also offers many options:literal vs. product optimization, single- vs. multi-output logic minimization, using vs. not using fed-back outputs as state variables, and exploring varied code lengths during state assignment, thus allowing the designer to explore trade-offs and select the implementation style which best suits the application. MINIMALIST benchmark results demonstrate its ability to produce implementations with an average of 34% and up to 48% less area, and an average of 11% and up to 37% better performance, than the best existing package. Our synthesis-for-testability method guarantees 100% testability under both stuck-at and robust path delay fault models,requiring little or no overhead. MINIMALIST also features both command-line and graphic user interfaces, and supports extension via well-defined interfaces for adding new tools. As such, it is easily augmented to form a complete path to technology-dependent logic

Deductive Fault Simulation Technique for Asynchronous Circuits

Fault simulator for acpASC needs to deal with hazards, oscillations and races. The simplest algorithm for simulating faults is the serial fault simulation technique which was successfully used for the acpASC. Faster fault simulation techniques, for example deductive fault simulation, was previously used for the combinational and synchronous sequential circuits only. In this paper a deductive fault simulator for the stuck-at faults of acSI acpASC is presented. An algorithm for the propagation of the fault lists is proposed which can deal with the complex gates of the acpASC. The implemented deductive fault simulator was tested using acSI benchmark circuits. The experimental results show significant reduction of the computation time and negligible increase of the memory requirements in comparison with the serial fault simulation technique

Synthesis of timed circuits using BDDs*

Journal ArticleThis paper presents a tool which synthesizes timed circuits from reduced state graphs. Using timing information to reduce state graphs can lead to significantly smaller and faster circuits. The tool uses implicit techniques (binary decision diagrams) to represent these graphs. This allows us to synthesize larger, more complex systems which may be intractable with an explicit representation. We are also able to create a parameterized family of solutions, facilitating technology mapping

Doctor of Philosophy

dissertationAsynchronous design has a very promising potential even though it has largely received a cold reception from industry. Part of this reluctance has been due to the necessity of custom design languages and computer aided design (CAD) flows to design, optimize, and validate asynchronous modules and systems. Next generation asynchronous flows should support modern programming languages (e.g., Verilog) and application specific integrated circuits (ASIC) CAD tools. They also have to support multifrequency designs with mixed synchronous (clocked) and asynchronous (unclocked) designs. This work presents a novel relative timing (RT) based methodology for generating multifrequency designs using synchronous CAD tools and flows. Synchronous CAD tools must be constrained for them to work with asynchronous circuits. Identification of these constraints and characterization flow to automatically derive the constraints is presented. The effect of the constraints on the designs and the way they are handled by the synchronous CAD tools are analyzed and reported in this work. The automation of the generation of asynchronous design templates and also the constraint generation is an important problem. Algorithms for automation of reset addition to asynchronous circuits and power and/or performance optimizations applied to the circuits using logical effort are explored thus filling an important hole in the automation flow. Constraints representing cyclic asynchronous circuits as directed acyclic graphs (DAGs) to the CAD tools is necessary for applying synchronous CAD optimizations like sizing, path delay optimizations and also using static timing analysis (STA) on these circuits. A thorough investigation for the requirements of cycle cutting while preserving timing paths is presented with an algorithm to automate the process of generating them. A large set of designs for 4 phase handshake protocol circuit implementations with early and late data validity are characterized for area, power and performance. Benchmark circuits with automated scripts to generate various configurations for better understanding of the designs are proposed and analyzed. Extension to the methodology like addition of scan insertion using automatic test pattern generation (ATPG) tools to add testability of datapath in bundled data asynchronous circuit implementations and timing closure approaches are also described. Energy, area, and performance of purely asynchronous circuits and circuits with mixed synchronous and asynchronous blocks are explored. Results indicate the benefits that can be derived by generating circuits with asynchronous components using this methodology

Event-based feature extraction using adaptive selection thresholds

Unsupervised feature extraction algorithms form one of the most important building blocks in machine learning systems. These algorithms are often adapted to the event-based domain to perform online learning in neuromorphic hardware. However, not designed for the purpose, such algorithms typically require significant simplification during implementation to meet hardware constraints, creating trade offs with performance. Furthermore, conventional feature extraction algorithms are not designed to generate useful intermediary signals which are valuable only in the context of neuromorphic hardware limitations. In this work a novel event-based feature extraction method is proposed that focuses on these issues. The algorithm operates via simple adaptive selection thresholds which allow a simpler implementation of network homeostasis than previous works by trading off a small amount of information loss in the form of missed events that fall outside the selection thresholds. The behavior of the selection thresholds and the output of the network as a whole are shown to provide uniquely useful signals indicating network weight convergence without the need to access network weights. A novel heuristic method for network size selection is proposed which makes use of noise events and their feature representations. The use of selection thresholds is shown to produce network activation patterns that predict classification accuracy allowing rapid evaluation and optimization of system parameters without the need to run back-end classifiers. The feature extraction method is tested on both the N-MNIST (Neuromorphic-MNIST) benchmarking dataset and a dataset of airplanes passing through the field of view. Multiple configurations with different classifiers are tested with the results quantifying the resultant performance gains at each processing stage