Functional Test Generation at the RTL Using Swarm Intelligence and Bounded Model Checking

Deep State Sequence-based (DSS) equivalence checking and path-based equivalence checking have been successfully applied for verification of digital designs between System Level Model (SLM) and Register Transfer Level (RTL). The DSS-based equivalence checking method can validate designs without mapping information, but the query size for each DSS is large compared with path-based verification. The query size for path-based methods is small, but the number of comparisons is large. In this work, we combine the advantages of DSS-based methods and path-based methods. We use DSS-based methods to find the corresponding paths and use cut-points like in path-based methods to split the DSS to reduce the query size. Finite State Machine with Datapath (FSMD) is used to represent the SLM and RTL models. Experimental results demonstrate that our method can effectively validate the designs and reduce the query size for DSS-based equivalence checking method.

In order to reduce the time-to-market and simplify gate-level test generation for digital integrated circuits, GA-based functional test generation techniques are proposed for behavioral and register transfer level designs. The functional tests generated can be used for design verification, and they can also be reused at lower levels (i.e. register transfer and logic gate levels) for testability analysis and development. Experimental results demonstrate the effectiveness of the method in reducing the overall test generation time and increasing the gate-level fault coverage.

Transaction-level modeling (TLM) is the leading design style to deal with the increasing complexity of modern embedded systems. TLM provides designers with high-level interfaces and communication protocols for abstract modeling and efficient simulation of system platforms. The Open SystemC Initiative (OSCI) has recently released the TLM-2.0 standard for facilitating the interchange of models between suppliers and users, and thus encouraging the use of virtual platforms for fast simulation prior to the availability of register-transfer level (RTL) code. On the other hand, verification of TLM IPs still relies on simulation-based techniques since formal verification methodologies (such as model checking) and tools are not mature enough to be applied at TLM level. In this paper, we propose a methodology to apply existing RTL model checkers for verifying TLM IPs. The methodology relies on the automatic synthesis of the TLM IP models into equivalent RTL descriptions, in order to verify the TLM properties through the equivalent RTL model of the IPs.

Using RTL (Register Transfer Level) models for the verification of complex hardware designs involves reducing the state space of designs using various abstraction techniques. In this paper, we propose faster and earlier verification of hardware designs at a level of abstraction above RTL. We consider a high-level (above RTL) hardware model that uses atomic rules to describe the behavior of a design, which can then be synthesized to RTL code. Bluespec System Verilog (BSV) is an example of such a high-level specification language. We propose a methodology for verification of BSV models using Spin, which is a Model Checking tool. Verification of high-level BSV models may avoid the need for using abstraction techniques since such models already ignore various low-level details that are irrelevant for verifying a design's behavioral properties. Moreover, using our proposed methodology different behaviors of BSV models can be efficiently verified at high-level aiding in faster verification.

Simulation is widely used for validation of Register-Transfer-Level (RTL) models. While simulating with millions of random or constrained-random tests can cover majority of the functional scenarios, the number of remaining scenarios can still be huge (hundreds or thousands) in case of today's industrial designs. Hard-to-activate branches are one of the major contributors for such remaining/untested scenarios. While directed test generation techniques using formal methods are promising in activating branches, it is infeasible to apply them on large designs due to state space explosion. In this article, we propose a fully automated and scalable approach to cover the hard-to-activate branches using concolic testing of RTL models. While application of concolic testing on hardware designs has shown some promising results in improving the overall coverage, they are not designed to activate specific targets such as uncovered corner cases and rare scenarios. In other words, existing concolic testing approaches address state space explosion problem but leads to path explosion problem while searching for the uncovered targets. Our proposed approach maps directed test generation problem to target search problem while avoiding overlapping searches involving multiple targets. This article makes two important contributions. (1) We propose a directed test generation technique to activate a target by effective utilization of concolic testing on RTL models. (2) We develop efficient learning and clustering techniques to minimize the overlapping searches across targets to drastically reduce the overall test generation effort. Experimental results demonstrate that our approach significantly outperforms the state-of-the-art methods in terms of test generation time (up to 205X, 69X on average) as well as memory requirements (up to 31X, 7X on average).

Transaction level (TL) models are key to early design exploration, performance estimation and virtual prototyping. Their speed and accuracy enable early and rapid System-on-Chip (SoC) design evaluation and software development. Most devices have only register transfer level (RTL) models that are too complex for SoC simulation. Abstracting these models to TL ones, however, is a challenging task, especially when the RTL description is too obscure or not accessible. This work presents a methodology for automatically creating a TL model of an RTL memory controller component. The device is treated as a black box and a multitude of simulations is used to obtain results, showing its timing behavior. The results are classified into conditional probability distributions, which are reused within a TL model to approximate the RTL timing behavior. The presented method is very fast and highly accurate. The resulting TL model executes approximately 1200 times faster, with a maximum measured average timing offset error of 7.66%.

Early RTL delay prediction using neural networks

A digital circuit usually comprises a controller and datapath. The time spent for determining a valid controller behavior to detect a fault usually dominates test generation time. A validation test set is used to verify controller behavior and, hence, it activates various controller behaviors. In this paper, we present a methodology wherein the controller behaviors exercised by test sequences in a validation test set are reused for detecting faults in the datapath. A heuristic is used to identify controller behaviors that can justify/propagate pre-computed test vectors/responses of datapath register-transfer level (RTL) modules. Such controller behaviors are said to be compatible with the corresponding pre-computed test vectors/responses. The heuristic is fairly accurate, resulting in the detection of a majority of stuck-at faults in the datapath RTL modules. Also, since test generation is performed at the RTL and the controller behavior is predetermined, test generation time is reduced. For microprocessors, if the validation test set consists of instruction sequences then the proposed methodology also generates instruction-level test sequences

We present a technique for extracting functional (control/dataflow) information from register transfer level (RTL) controller/data path circuits and illustrate its use in design for hierarchical testability of these circuits. This testing procedure and design for testability (DFT) technique is general enough to handle RTL control flow intensive circuits like protocol handlers as well as data flow intensive circuits like digital filters. It makes the combined controller-data path highly testable and does not require any external behavioral information. This scheme has the advantages of low area/delay/power overheads (average of 3.2%, 0.9% and 4.1%, respectively, for benchmarks), high fault coverage (over 99% for most cases), very low test generation times (because it is independent of bit-width), and the advantage of at-speed testing. Experiments show a 2-to-4 (1-to-3) orders of magnitude test generation time advantage over an efficient gate-level sequential test generator (combinational test generator that assumes full scan).

System-on-Chip (SoC) security is vital in designing trustworthy systems. Detecting and fixing a vulnerability in the early stages is easier and cost-effective. Assertion-based verification is widely used for functional validation of Register-Transfer Level (RTL) designs. Assertions can improve the controllability and observability that can lead to faster error detection and localization. Although assertions are widely used for functional validation of RTL models, there is limited effort in applying assertions to detect SoC security vulnerabilities. Specifically, a fundamental challenge in SoC security and trust validation is how to develop high-quality security assertions. In this article, we perform automated vulnerability analysis of RTL models to generate security assertions for six classes of vulnerabilities. Experimental results show that the generated security assertions can detect a wide variety of vulnerabilities. Our automated framework can drastically reduce the overall security validation effort compared to the manual development of security assertions. Automated generation of security assertions will enable assertion-based verification to be one of the most promising pre-silicon security sign-off solutions.

This paper proposes a technique that mixes simulation and an analytical method to evaluate the characteristics of Networks-on-Chips (NoCs). The advantage of this technique is to reduce the simulation time by reducing the complexity of the NoC model while still obtaining accurate results for latency and throughput. The basis of this technique is: (i) to send the whole payload data at once in the packet header; (ii) to reduce the NoC simulation complexity by omitting the flit by flit payload forwarding; (iii) to use an algorithm for controlling the release of the packet trailer in order to close the connection at the right time. For the evaluation of this technique, an actor-oriented model of a NoC, JOSELITO, was created. Simulation results show that JOSELITO is in average 2.3 times faster in 88% of the executed case studies than the implementation without using the proposed technique. The worst case simulation results for latency and throughput have, respectively, 5.26% and 0.1% error compared to the corresponding Register Transfer Level (RTL) model.

The authors present a methodology for designing a CMOS very large scale integration (VLSI) controller for AC motor control. Step-by-step, top-down methodology based on hardware description languages (HDL) with mixed simulation was used to study digital adaptation and architecture implementation of the control algorithm. An application using the proposed methodology was studied: the direct torque control (DTC) of an AC motor. The DTC is described and VLSI examined. Analogue and digital models were used to describe the algorithm implementation, specific binary format and architecture. The register transfer level (RTL) model for the DTC controller was validated by mixed simulation. The ASIC layout was created using Austria Mikro System standard cell library for 0.8 μm CMOS. Finally, the authors compared this VLSI approach with software implementation and co-design methodology.

The paper proposes a hierarchical untestable stuck-at fault identification method for non-scan synchronous sequential circuits. The method is based on deriving, minimizing and solving test path constraints for modules embedded into Register-Transfer Level (RTL) designs. First, an RTL test pattern generator is applied in order to extract the set of all possible test path constraints for a module under test. Then, the constraints are minimized using an SMT solver Z3 and a logic minimization tool ESPRESSO. Finally, a constraint-driven deterministic test pattern generator is run providing hierarchical test generation and untestability proof in sequential circuits. We show by experiments that the method is capable of quickly proving a large number of untestable faults obtaining higher fault efficiency than achievable by a state-of-the-art commercial ATPG. As a side effect, our study shows that traditional bottom-up test generation based on symbolic test environment generation at RTL is too optimistic due to the fact that propagation constraints are ignored.

Simulation is the most widely used form of validation using billions of random and pseudo-random tests in the traditional design flow. A critical problem in post-silicon debug is to generate efficient tests that both activate requisite coverage goal on the target hardware as well as produce results that are observable through a given on-chip design-for-debug architecture. Unfortunately, such tests cannot be generated directly from register-transfer level (RTL) models, both due to design complexity and due to bugs in the design itself. In this chapter, we discuss a directed test generation approach which facilities the observation of expected outputs of the generated tests using the traced signals. The proposed approach uses transaction-level models (TLM) for post-silicon test generation. The basic idea is to transform an RTL assertion as well as observability constraints to create a TLM assertion with observability constraints. The TLM assertion/property would be used to enable TLM analysis to generate post-silicon tests. Finally, the TLM test would be translated to an RTL test that is debug-friendly. In this chapter, we provide case studies from a number of different design classes to demonstrate the flexibility and effectiveness of the approach.

The paper compares the application of two stochastic search techniques for the solution of two typical problems in modelling nonlinear systems using a multi-modelling approach: interpolation function determination; linear model structure determination. It is shown that the two candidate stochastic search techniques employed, genetic algorithms and swarm intelligence, show different advantages for each of the problems considered.