137 research outputs found

    A Test Vector Minimization Algorithm Based On Delta Debugging For Post-Silicon Validation Of Pcie Rootport

    Get PDF
    In silicon hardware design, such as designing PCIe devices, design verification is an essential part of the design process, whereby the devices are subjected to a series of tests that verify the functionality. However, manual debugging is still widely used in post-silicon validation and is a major bottleneck in the validation process. The reason is a large number of tests vectors have to be analyzed, and this slows process down. To solve the problem, a test vector minimizer algorithm is proposed to eliminate redundant test vectors that do not contribute to reproduction of a test failure, hence, improving the debug throughput. The proposed methodology is inspired by the Delta Debugging algorithm which is has been used in automated software debugging but not in post-silicon hardware debugging. The minimizer operates on the principle of binary partitioning of the test vectors, and iteratively testing each subset (or complement of set) on a post-silicon System-Under-Test (SUT), to identify and eliminate redundant test vectors. Test results using test vector sets containing deliberately introduced erroneous test vectors show that the minimizer is able to isolate the erroneous test vectors. In test cases containing up to 10,000 test vectors, the minimizer requires about 16ns per test vector in the test case when only one erroneous test vector is present. In a test case with 1000 vectors including erroneous vectors, the same minimizer requires about 140μs per erroneous test vector that is injected. Thus, the minimizer’s CPU consumption is significantly smaller than the typical amount of time of a test running on SUT. The factors that significantly impact the performance of the algorithm are number of erroneous test vectors and distribution (spacing) of the erroneous vectors. The effect of total number of test vectors and position of the erroneous vectors are relatively minor compared to the other two. The minimization algorithm therefore was most effective for cases where there are only a few erroneous test vectors, with large number of test vectors in the set

    Heterogeneous Acceleration for 5G New Radio Channel Modelling Using FPGAs and GPUs

    Get PDF
    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Continuous Integration for Fast SoC Algorithm Development

    Get PDF
    Digital systems have become advanced, hard to design and optimize due to ever-growing technology. Integrated Circuits (ICs) have become more complicated due to complex computations in latest technologies. Communication systems such as mobile networks have evolved and become a part of our daily lives with the advancement in technology over the years. Hence, need of efficient, reusable and automated processes for System-on-a-Chip (SoC) development has been increased. Purpose of this thesis is to study and evaluate currently used SoC development processes and presents guidelines on how these processes can be streamlined. The thesis starts by evaluating currently used SoC development flows and their advantages and disadvantages. One important aspect is to identify step which cause duplication of work and unnecessary idle times in SoC development teams. A study is conducted and input from SoC development experts is taken in order to optimize SoC flows and use of Continuous Integration (CI) system. An algorithm model is implemented that can be used in multiple stages of SoC development at adequate complexity and is “easy enough” to be used for a person not mastering the topic. The thesis outcome is proposal for CI system in SoC development for accelerating the speed and reliability of implementing algorithms to RTL code and finally into product. CI system tool is also implemented to automate and test the model design so that it also remains up to date

    A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research

    Full text link
    With traditional networking, users can configure control plane protocols to match the specific network configuration, but without the ability to fundamentally change the underlying algorithms. With SDN, the users may provide their own control plane, that can control network devices through their data plane APIs. Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane APIs which may be leveraged by user-defined SDN control. Thus, programmable data planes and SDN offer great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community and it is supported by various software and hardware platforms. In this paper, we survey the literature from 2015 to 2020 on data plane programming with P4. Our survey covers 497 references of which 367 are scientific publications. We organize our work into two parts. In the first part, we give an overview of data plane programming models, the programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we analyze a large body of literature considering P4-based applied research. We categorize 241 research papers into different application domains, summarize their contributions, and extract prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on 2021-01-2

    Efficient Real-Time Architectures and FPGA Implementations of Histogram-Based Median Filters for High Definition Videos

    Get PDF
    Digital filtering plays an important role in many signal processing applications. Filtering is performed to recover the original signal from its corrupted version. Median filter is a non-linear digital filter that replaces a sample in a given window by the median value of the samples in the window. For images corrupted with impulse noise, median filter provides a very high quality of filtered images. Several modifications of median filters have been proposed and implemented to achieve high image quality compared to that provided by conventional median filters. When these filters are implemented on hardware platforms such as FPGAs, the performance parameters, namely, the area, power and operating frequency should be taken into consideration in addition to the quality of the filtered image. Therefore, efficient implementation of median filters on FPGAs for image and video processing algorithms has been a topic of much interest. The existing hardware-based median filters for high definition video formats do not always satisfy the real-time throughput requirements or are inefficient with respect to hardware performance parameters, such as the area and frequency. This is due to the fact that most of the existing techniques use sorting-based median calculation, which results in a low hardware performance. In this thesis, architectures that use histogram-based median computation, which is a non-sorting-based operation, are designed with a view of efficient hardware implementation. This is carried out in two parts. We design and implement efficient architectures that satisfy the real-time throughput requirements of full high definition (FHD) videos in the first part and that of ultra high definition (UHD) videos in the second part. In the first part, an efficient real-time histogram-based median filter that uses the concept of bit-plane-slicing and adaptive switching median filter (ASMF) is designed and implemented on FPGAs. We term this architecture as hybrid architecture for median filtering (HAMF). The proposed HAMF computes an approximate median, since it uses only the most significant B-bits of the pixel values for median calculation. As a result, the algorithmic level implementation of the proposed HAMF results in a slight degradation in the filtered image quality compared to that provided by ASMF. The proposed HAMF provides a significant improvement over ASMF in terms of the area and operating frequency, when implemented on different generation FPGAs. Analysis of the different parameters, such as the number of bit-planes used in the computation of the median and the number of pipelining stages, is carried out to study the trade-off between the quality of the filtered image and hardware performance. Although the FPGA implementation of the proposed HAMF provides a very high operating frequency, the quality of the images filtered by its algorithmic level implementation decreases with increasing window size and noise density. This filter may be suitable for applications that require FHD filtering with cost constraints, but not for applications where the output image quality is as important as the hardware performance. Hence, in the second part, we design an efficient and real-time architecture of the hierarchical histogram-based median filter (HHMF). The proposed architecture is designed using a full synchronous pipeline, a synchronous accumulate-and-compare unit, and is scalable. The FPGA implementation of the proposed architecture of HHMF can perform real-time filtering of 4K and 8K UHD videos. The quality of the image filtered by HHMF is not compromised as in the case of HAMF, since HHMF uses all the bit-planes and computes the actual median. Although the FPGA implementation of HHMF results in more area utilization, the proposed implementation is more economical than a GPU-based HHMF implementation and provides a better throughput
    corecore