A low-cost high-speed twin-prefetching DSP-based shared-memory system for real-time image processing applications

This dissertation introduces, investigates, and evaluates a low-cost high-speed twin-prefetching DSP-based bus-interconnected shared-memory system for real-time image processing applications. The proposed architecture can effectively support 32 DSPs in contrast to a maximum of 4 DSPs supported by existing DSP-based bus- interconnected systems. This significant enhancement is achieved by introducing two small programmable fast memories (Twins) between the processor and the shared bus interconnect. While one memory is transferring data from/to the shared memory, the other is supplying the core processor with data. The elimination of the traditional direct linkage of the shared bus and processor data bus makes feasible the utilization of a wider shared bus i.e., shared bus width becomes independent of the data bus width of the processors. The fast prefetching memories and the wider shared bus provide additional bus bandwidth into the system, which eliminates large memory latencies; such memory latencies constitute the major drawback for the performance of shared-memory multiprocessors. Furthermore, in contrast to existing DSP-based uniprocessor or multiprocessor systems the proposed architecture does not require all data to be placed on on-chip or off-chip expensive fast memory in order to reach or maintain peak performance. Further, it can maintain peak performance regardless of whether the processed image is small or large. The performance of the proposed architecture has been extensively investigated executing computationally intensive applications such as real-time high-resolution image processing. The effect of a wide variety of hardware design parameters on performance has been examined. More specifically tables and graphs comprehensively analyze the performance of 1, 2, 4, 8, 16, 32 and 64 DSP-based systems, for a wide variety of shared data interconnect widths such as 32, 64, 128, 256 and 512. In addition, the effect of the wide variance of temporal and spatial locality (present in different applications) on the multiprocessor\u27s execution time is investigated and analyzed. Finally, the prefetching cache-size was varied from a few kilobytes to 4 Mbytes and the corresponding effect on the execution time was investigated. Our performance analysis has clearly showed that the execution time converges to a shallow minimum i.e., it is not sensitive to the size of the prefetching cache. The significance of this observation is that near optimum performance can be achieved with a small (16 to 300 Kbytes) amount of prefetching cache

Towards secure cyber-physical systems for autonomous vehicles

Cyber-Physical systems have become ubiquitous. These systems integrate different functionalities to satisfy the performance requirements and take advantage of the available processing power of multi-core systems. Safety critical applications such as autonomous vehicles or medical devices rely not only on proving correct functionality of cyber-physical systems as essential certification criteria but they must also satisfy other design constraints such as energy efficiency, low power consumption and reliability. Their need to connect to the internet have created new challenges which means addressing the security vulnerabilities has become as the first-class design concern. In this talk, first a hardware/software co-design approach for two critical tasks, real-time pedestrian and vehicle detections, which are essential in advanced driving assistance systems (ADAS) and autonomous driving systems (ADS) is presented. We use partial dynamic reconfiguration on FPGA for adaptive vehicle detection. In the second part of this talk, a system-level security-aware design approach is presented to avoid or confine the impact of security compromises on the critical components of the cyber-physical systems implemented in multiprocessor systems on chip. Our system-level security approach considers the described system architecture for a specific application and analyzes its security vulnerability based on the specified security rules to generate an impact analysis report. Then, it creates a new system architecture configuration to protect the critical components of the system by providing isolation of tasks without the need to trust a central authority at run-time for heterogeneous multiprocessor system. This approach allows safe use of shared IP with direct memory access, as well as shared libraries by regulating memory accesses and the communications between the system components

Predictable embedded multiprocessor architecture for streaming applications

The focus of this thesis is on embedded media systems that execute applications from the application domain car infotainment. These applications, which we refer to as jobs, typically fall in the class of streaming, i.e. they process on a stream of data. The jobs are executed on heterogeneous multiprocessor platforms, for performance and power efficiency reasons. Most of these jobs have firm real-time requirements, like throughput and end-to-end latency. Car-infotainment systems become increasingly more complex, due to an increase in the supported number of jobs and an increase of resource sharing. Therefore, it is hard to verify, for each job, that the realtime requirements are satisfied. To reduce the verification effort, we elaborate on an architecture for a predictable system from which we can verify, at design time, that the job’s throughput and end-to-end latency requirements are satisfied. This thesis introduces a network-based multiprocessor system that is predictable. This is achieved by starting with an architecture where processors have private local memories and execute tasks in a static order, so that the uncertainty in the temporal behaviour is minimised. As an interconnect, we use a network that supports guaranteed communication services so that it is guaranteed that data is delivered in time. The architecture is extended with shared local memories, run-time scheduling of tasks, and a memory hierarchy. Dataflow modelling and analysis techniques are used for verification, because they allow cyclic data dependencies that influence the job’s performance. Shown is how to construct a dataflow model from a job that is mapped onto our predictable multiprocessor platforms. This dataflow model takes into account: computation of tasks, communication between tasks, buffer capacities, and scheduling of shared resources. The job’s throughput and end-to-end latency bounds are derived from a self-timed execution of the dataflow graph, by making use of existing dataflow-analysis techniques. It is shown that the derived bounds are tight, e.g. for our channel equaliser job, the accuracy of the derived throughput bound is within 10.1%. Furthermore, it is shown that the dataflow modelling and analysis techniques can be used despite the use of shared memories, run-time scheduling of tasks, and caches

Performance Analysis of a Novel GPU Computation-to-core Mapping Scheme for Robust Facet Image Modeling

Though the GPGPU concept is well-known in image processing, much more work remains to be done to fully exploit GPUs as an alternative computation engine. This paper investigates the computation-to-core mapping strategies to probe the efficiency and scalability of the robust facet image modeling algorithm on GPUs. Our fine-grained computation-to-core mapping scheme shows a significant performance gain over the standard pixel-wise mapping scheme. With in-depth performance comparisons across the two different mapping schemes, we analyze the impact of the level of parallelism on the GPU computation and suggest two principles for optimizing future image processing applications on the GPU platform

Development and evaluation of a fault-tolerant multiprocessor (FTMP) computer. Volume 4: FTMP executive summary

The FTMP architecture is a high reliability computer concept modeled after a homogeneous multiprocessor architecture. Elements of the FTMP are operated in tight synchronism with one another and hardware fault-detection and fault-masking is provided which is transparent to the software. Operating system design and user software design is thus greatly simplified. Performance of the FTMP is also comparable to that of a simplex equivalent due to the efficiency of fault handling hardware. The FTMP project constructed an engineering module of the FTMP, programmed the machine and extensively tested the architecture through fault injection and other stress testing. This testing confirmed the soundness of the FTMP concepts