Design of testbed and emulation tools

The research summarized was concerned with the design of testbed and emulation tools suitable to assist in projecting, with reasonable accuracy, the expected performance of highly concurrent computing systems on large, complete applications. Such testbed and emulation tools are intended for the eventual use of those exploring new concurrent system architectures and organizations, either as users or as designers of such systems. While a range of alternatives was considered, a software based set of hierarchical tools was chosen to provide maximum flexibility, to ease in moving to new computers as technology improves and to take advantage of the inherent reliability and availability of commercially available computing systems

IP Core for Timed Petri Nets

In this article, we present a Timed Petri Nets Processor which can be directly programmed using Petri Nets formalism vectors and matrixes. This processor can leverage the power of Petri Nets for modeling real-time systems and formally verify their properties, which prevent programming errors. The Petri Nets Processor was developed as an IP-core to be inserted in a Multi-Core system. Therefore, we can model the system requirements with Petri Nets, formally verifying all its properties and by using the IP-core to implement the system is possible to ensure that all properties will be met.http://www.sase.com.ar/2013/files/2013/09/CASE2013_ForoPoster_v5L.pdfFil: Micolini, Orlando. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Arquitectura de Computadoras; Argentina.Fil: Nonino, Julián. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Arquitectura de Computadoras; Argentina.Fil: Pisetta, Carlos R. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Arquitectura de Computadoras; Argentina.Ingeniería Eléctrica y Electrónic

A High Performance Fuzzy Logic Architecture for UAV Decision Making

The majority of Unmanned Aerial Vehicles (UAVs) in operation today are not truly autonomous, but are instead reliant on a remote human pilot. A high degree of autonomy can provide many advantages in terms of cost, operational resources and safety. However, one of the challenges involved in achieving autonomy is that of replicating the reasoning and decision making capabilities of a human pilot. One candidate method for providing this decision making capability is fuzzy logic. In this role, the fuzzy system must satisfy real-time constraints, process large quantities of data and relate to large knowledge bases. Consequently, there is a need for a generic, high performance fuzzy computation platform for UAV applications. Based on Lees’ [1] original work, a high performance fuzzy processing architecture, implemented in Field Programmable Gate Arrays (FPGAs), has been developed and is shown to outclass the performance of existing fuzzy processors

Simulator for concurrent processing data flow architectures

A software simulator capability of simulating execution of an algorithm graph on a given system under the Algorithm to Architecture Mapping Model (ATAMM) rules is presented. ATAMM is capable of modeling the execution of large-grained algorithms on distributed data flow architectures. Investigating the behavior and determining the performance of an ATAMM based system requires the aid of software tools. The ATAMM Simulator presented is capable of determining the performance of a system without having to build a hardware prototype. Case studies are performed on four algorithms to demonstrate the capabilities of the ATAMM Simulator. Simulated results are shown to be comparable to the experimental results of the Advanced Development Model System

An Adaptive Design Methodology for Reduction of Product Development Risk

Embedded systems interaction with environment inherently complicates understanding of requirements and their correct implementation. However, product uncertainty is highest during early stages of development. Design verification is an essential step in the development of any system, especially for Embedded System. This paper introduces a novel adaptive design methodology, which incorporates step-wise prototyping and verification. With each adaptive step product-realization level is enhanced while decreasing the level of product uncertainty, thereby reducing the overall costs. The back-bone of this frame-work is the development of Domain Specific Operational (DOP) Model and the associated Verification Instrumentation for Test and Evaluation, developed based on the DOP model. Together they generate functionally valid test-sequence for carrying out prototype evaluation. With the help of a case study 'Multimode Detection Subsystem' the application of this method is sketched. The design methodologies can be compared by defining and computing a generic performance criterion like Average design-cycle Risk. For the case study, by computing Average design-cycle Risk, it is shown that the adaptive method reduces the product development risk for a small increase in the total design cycle time.Comment: 21 pages, 9 figure

A comparison of modular self-timed design styles

technical reportState-machine sequencing methods in modular 2-phase and 4-phase asynchronous handshake control are compared. Design styles are discussed, and the sequencers are tested against each other using a medium-scale minicomputer test design implemented in FPGAs. Seven 4-phase sequencers are tested. In these comparisons, 2- phase control is faster than 4-phase. Within the 4-phase designs, speed is enhanced when work is overlapped with handshake restoration. Performance of asynchronous and synchronous designs is compared

Intrinsically Evolvable Artificial Neural Networks

Dedicated hardware implementations of neural networks promise to provide faster, lower power operation when compared to software implementations executing on processors. Unfortunately, most custom hardware implementations do not support intrinsic training of these networks on-chip. The training is typically done using offline software simulations and the obtained network is synthesized and targeted to the hardware offline. The FPGA design presented here facilitates on-chip intrinsic training of artificial neural networks. Block-based neural networks (BbNN), the type of artificial neural networks implemented here, are grid-based networks neuron blocks. These networks are trained using genetic algorithms to simultaneously optimize the network structure and the internal synaptic parameters. The design supports online structure and parameter updates, and is an intrinsically evolvable BbNN platform supporting functional-level hardware evolution. Functional-level evolvable hardware (EHW) uses evolutionary algorithms to evolve interconnections and internal parameters of functional modules in reconfigurable computing systems such as FPGAs. Functional modules can be any hardware modules such as multipliers, adders, and trigonometric functions. In the implementation presented, the functional module is a neuron block. The designed platform is suitable for applications in dynamic environments, and can be adapted and retrained online. The online training capability has been demonstrated using a case study. A performance characterization model for RC implementations of BbNNs has also been presented

Verification of timed circuits with failure-directed abstractions

Journal ArticleAbstract-This paper presents a method to address state explosion in timed-circuit verification by using abstraction directed by the failure model. This method allows us to decompose the verification problem into a set of subproblems, each of which proves that a specific failure condition does not occur. To each subproblem, abstraction is applied using safe transformations to reduce the complexity of verification. The abstraction preserves all essential behaviors conservatively for the specific failure model in the concrete description. Therefore, no violations of the given failure model are missed when only the abstract description is analyzed. An algorithm is also shown to examine the abstract error trace to either find a concrete error trace or report that it is a false negative. This paper presents results using the proposed failure-directed abstractions as applied to several large timed circuit designs