Processor Verification Using Efficient Reductions of the Logic of Uninterpreted Functions to Propositional Logic

The logic of equality with uninterpreted functions (EUF) provides a means of abstracting the manipulation of data by a processor when verifying the correctness of its control logic. By reducing formulas in this logic to propositional formulas, we can apply Boolean methods such as Ordered Binary Decision Diagrams (BDDs) and Boolean satisfiability checkers to perform the verification. We can exploit characteristics of the formulas describing the verification conditions to greatly simplify the propositional formulas generated. In particular, we exploit the property that many equations appear only in positive form. We can therefore reduce the set of interpretations of the function symbols that must be considered to prove that a formula is universally valid to those that are ``maximally diverse.'' We present experimental results demonstrating the efficiency of this approach when verifying pipelined processors using the method proposed by Burch and Dill.Comment: 46 page

Automatic verification of pipelined microprocessors

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (p. 71-72).by Vishal Lalit Bhagwati.M.S

Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles

The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking received support from the European Union’s Horizon 2020 research and innovation programme and Germany, Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy, Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL Joint Undertaking under grant agreement No. 692455-2

A proposed synthesis method for Application-Specific Instruction Set Processors

Due to the rapid technology advancement in integrated circuit era, the need for the high computation performance together with increasing complexity and manufacturing costs has raised the demand for high-performance con fi gurable designs; therefore, the Application-Speci fi c Instruction Set Processors (ASIPs) are widely used in SoC design. The automated generation of software tools for ASIPs is a commonly used technique, but the automated hardware model generation is less frequently applied in terms of fi nal RTL implementations. Contrary to this, the fi nal register-transfer level models are usually created, at least partly, manually. This paper presents a novel approach for automated hardware model generation for ASIPs. The new solution is based on a novel abstract ASIP model and a modeling language (Algorithmic Microarchitecture Description Language, AMDL) optimized for this architecture model. The proposed AMDL-based pre-synthesis method is based on a set of pre-de fi ned VHDL implementation schemes, which ensure the qualities of the automatically generated register-transfer level models in terms of resource requirement and operation frequency. The design framework implementing the algorithms required by the synthesis method is also presented

Guarded atomic actions and refinement in a system-on-chip development flow: bridging the specification gap with Event-B

Modern System-on-chip (SoC) hardware design puts considerable pressure on existing design and verification flows, languages and tools. The Register Transfer Level (RTL)description, which forms the input for synchronous, logic synthesis-driven design is at too low a level of abstraction for efficient architectural exploration and re-use. The existing methods for taking a high-level paper specification and refining this specification to an implementation that meets its performance criteria is largely manual and error-prone and as RTL descriptions get larger, a systematic design method is necessary to address explicitly the timing issues that arise when applying logic synthesis to such large blocks.Guarded Atomic Actions have been shown to offer a convenient notation for describing microarchitectures that is amenable to formal reasoning and high-level synthesis. Event-B is a language and method that supports the development of specifications with automatic proof and refinement, based on guarded atomic actions. Latency-insensitive design ensures that a design composed of functionally correct components will be independent of communication latency. A method has been developed which uses Event-B for latency-insensitive SoC component and sub-system design which can be combined with high-level, component synthesis to enable architectural exploration and re-use at the specification level and to close the specification gap in the SoC hardware flow

Configurable computer systems can support dataflow computing

This work presents a practical implementation of a uni-processor system design. This design, named D2-CPU, satisfies the pure data-driven paradigm, which is a radical alternative to the conventional von Neumann paradigm and exploits the instruction-level parallelism to its full extent. The D2-CPU uses the natural flow of the program, dataflow, by minimizing redundant instructions like fetch, store, and write back. This leads to a design with the better performance, lower power consumption and efficient use of the on-chip resources. This extraordinary performance is the result of a simple, pipelined and superscalar architecture with a very wide data bus and a completely out of order execution of instructions. This creates a program counter less, distributed controlled system design with the realization of intelligent memories. Upon the availability of data, the instructions advance further in the memory hierarchy and ultimately to the execution units by themselves, instead of having the CPU fetch the required instructions from the memory as in controlled flow processors. This application (data) oriented execution process is in contrast to application ignorant CPUs in conventional machines. The D2-CPU solves current architectural challenges and puts into practice a pure data-driven microprocessor. This work employs an FPGA implementation of the D2-CPU to prove the practicability of the data-driven computer paradigm using configurable logic. A relative analysis at the end confirms its superiority in performance, resource utilization and ease of programming over conventional CPUs

A New Hybrid Nonintrusive Error-Detection Technique Using Dual Control-Flow Monitoring

Hybrid error-detection techniques combine software techniques with an external hardware module that monitors the execution of a microprocessor. The external hardware module typically observes the control flow at the input or at the output of the microprocessor and compares it with the expected one. This paper proposes a new hybrid technique that monitors the control flow at both points and compares them to detect possible errors. The proposed approach does not require any software modification to detect control-flow errors. Fault-injection campaigns have been performed on an LEON3 microprocessor. The results show full control-flow error detection with no performance degradation and small area overhead. A complete solution can be obtained by complementing the proposed approach with software fault-tolerance techniques for data errors.This work was supported in part by the Spanish Government under Contract TEC2010-22095-C03-03