14133000
Software-based diagnosis for processors
Software-based self-test (SBST) is emerging as a promising technology for enabling at-speed test of high-speed microprocessors using low-cost testers. We explore the fault diagnosis capability of SBST, in which functional information can be used to guide and facilitate the generation of diagnostic tests. By using a large number of carefully constructed diagnostic test programs, the fault universe can be divided into fine-grained partitions, each corresponding to a unique pass/fail pattern. We evaluate the quality of diagnosis by constructing diagnostic-tree-based fault dictionaries. We demonstrate the feasibility of the proposed method by applying it to a processor example. Experimental results show its potential as an effective method for diagnosing larger processors.
8887048
Using a Soft Core in a SoC Design: Experiences with picoJava
Through our experience in synthesis, validation, test, and integration of the picoJava processor core in a system-on-chip (SoC) design we point out the challenges faced and issues to address in efficient reuse of a soft core.
12599093
A scalable software-based self-test methodology for programmable processors
Software-based self-test (SBST) is an emerging approach to address the challenges of high-quality, at-speed test for complex programmable processors and systems-on chips (SoCs) that contain them. While early work on SBST has proposed several promising ideas, many challenges remain in applying SBST to realistic embedded processors. We propose a systematic scalable methodology for SBST that automates several key steps. The proposed methodology consists of (i) identifying test program templates that are well suited for test delivery to each module within the processor, (ii) extracting input/output mapping functions that capture the controllability/observability constraints imposed by a test program template for a specific module-under-test, (iii) generating module-level tests by representing the input/output mapping functions as virtual constraint circuits, and (iv) automatic synthesis of a software self-test program from the module-level tests. We propose novel RTL simulation-based techniques for template ranking and selection, and techniques based on the theory of statistical regression for extraction of input/output mapping functions. An important advantage of the proposed techniques is their scalability, which is necessitated by the significant and growing complexity of embedded processors.To demonstrate the utility of the proposed methodology, we have applied it to a commercial state-of-the-art embedded processor (Xtensa™ from Tensilica Inc.). We believe this is the first practical demonstration of software-based self-test on a processor of such complexity. Experimental results demonstrate that software self-test programs generated using the proposed methodology are able to detect most (95.2%) of the functionally testable faults, and achieve significant simultaneous improvements in fault coverage and test length compared with conventional functional test.
5124709
Embedded hardware and software self-testing methodologies for processor cores
At-speed testing of GHz processors using external testers may not be technically and economically feasible. Hence, there is an emerging need for low-cost, high-quality self-test methodologies, which can be used by processors to test themselves at-speed. Currently, Built-In Self-Test (BIST) is the primary self-test methodology available and is widely used for testing embedded memory cores. In this paper, we report our experiences in applying a commercial BIST methodology to two processor cores and analyze the problems associated with the current hardware-based BIST methodologies. We propose a new software-based self-testing methodology for processors, which uses a software tester embedded in the processor memory as a vehicle for applying structural tests. The software tester consists of programs for test generation and test application. Prior to the test, structural tests are prepared for processor components in the form of self-test signatures. During the process of self-test, the test generation program expands the self-test signatures into test sets, and the test application program applies the tests to the components-under-test at the speed of the processor. Application of the novel software-based self-test method demonstrates its significant cost/fault coverage benefits and its ability to apply at-speed test while alleviating the need for high-speed testers.
8098811
Embedded software-based self-testing for SoC design
At-speed testing of high-speed circuits is becoming increasingly difficult with external testers due to the growing gap between design and tester performance, growing cost of high-performance testers and increasing yield loss caused by inherent tester inaccuracy. Therefore, empowering the chip to test itself seems like a natural solution. Hardware-based self-testing techniques have limitations due to performance and area overhead and problems caused by the application of non-functional patterns.Embedded software-based self-testing has recently become focus of intense research. In this methodology, the programmable cores are used for on-chip test generation, measurement, response analysis and even diagnosis. After the programmable core on a System-on-Chip (SoC) has been self-tested, it can be reused for testing on-chip buses, interfaces and other non-programmable cores. The advantages of this methodology include at-speed testing, low design-for-testability overhead and application of functional patterns in the functional environment. In this paper, we give a survey and outline the roadmap and challenges of this emerging embedded software-based self-testing paradigm.
43431226
Wavelet-based optical flow estimation
A new algorithm for accurate optical flow (OF) estimation using discrete wavelet approximation is proposed. The computation of OF depends on minimizing the image and smoothness constraints. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately approximate any function. OF vectors and image functions are represented by means of linear combinations of scaling basis functions. Based on such wavelet-based approximation, the leading coefficients of these basis functions carry global information about the approximated functions. The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of scaling coefficients. Once all the corresponding coefficients are determined, the flow vectors can be obtained accordingly. Experiments have been conducted on both synthetic and real image sequences. In terms of accuracy, the results show that our approach outperforms the existing methods which adopted the same objective function as ours.
6401713
Stability Analysis of Regional and National Voting Schemes by a Continuous Model
The previous discrete-model-based stability analysis of regional and national voting has been extended to a continuous-model-based analysis in the simultaneous presence of white and concentrated components of noise, reconfirming the previous conclusion that regional voting with smaller sized regions always demonstrates an improved stability over those with larger sized regions, including the national voting in its limiting case in particular. The conclusion remains valid as long as the weak distribution assumption is valid.
13928372
VRules: an effective association-based classifier for videos
Video classification is an important step towards multimedia understanding. Most state-of-the-art approaches which apply HMM to capture the temporal information of videos have the limitation by assuming that the current state of a video depends only on the immediate previous state. Nevertheless, this assumption may not hold for videos of various categories. In this paper, we present an effective video classifier which employs the association rule mining technique to discover the actual dependence relationship between video states. The discriminatory state transition patterns mined from different video categories are then used to perform classification. Besides capturing the association between states in the time space, we also capture the association between low-level features in spatial dimension to further distinguish the semantics of videos. Experimental results show that the performance of our association rule based classifier is quite promising.
9822806
Wavelet-based optical flow estimation
In this paper, a new algorithm for accurate optical flow estimation using discrete wavelet approximation is proposed. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately represent "things", to model optical flow vectors and image related functions. Each flow vector and image function are represented by linear combinations of wavelet basis functions. From such wavelet-based approximation, the leading coefficients of these basis functions carry the global information of the approximated "things". The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of wavelet coefficients. Once all the corresponding coefficients are decided, the flow vectors can be determined accordingly. Experiments conducted on both synthetic and real image sequences show that our approach outperformed the existing methods in terms of accuracy.
4792658
Active Page Generation via Customizing XML for Data Beans in E-Commerce Applications
In this paper, we analyze enabling technologies for typical e-business applications in terms of their multi-tier system architecture and their Model-Control-View (MCV) programming model. Based on observed limitations of the JSP (Java Server Page) technique commonly adopted for dynamic page generation (the view logic), we instead propose an alternative solution approach, namely, a generic schema mapping strategy to generate XML documents and DTDs from enterprise data beans. First, we describe in detail the XML generation process for the content composition logic. We also outline the XSL processing for the transformation logic. The separation of these two logics results in a generic solution to the bean viewing problem. In particular, it improves the bean reusability via its XML representative compared to the rigid strategy of hard-coding logics into JSP. Our proposed XML mapping solution represents a potentially valuable addition to future versions of the enterprise data beans specification. The trade-off between performance and flexibility of these alternative solutions is discussed. Lastly, we survey the state-of-art research results and emerging stardards related to this XML model mapping approach.