Design and analysis of an FPGA-based, multi-processor HW-SW system for SCC applications

The last 30 years have seen an increase in the complexity of embedded systems from a collection of simple circuits to systems consisting of multiple processors managing a wide variety of devices. This ever increasing complexity frequently requires that high assurance, fail-safe and secure design techniques be applied to protect against possible failures and breaches. To facilitate the implementation of these embedded systems in an efficient way, the FPGA industry recently created new families of devices. New features added to these devices include anti-tamper monitoring, bit stream encryption, and optimized routing architectures for physical and functional logic partition isolation. These devices have high capacities and are capable of implementing processors using their reprogrammable logic structures. This allows for an unprecedented level of hardware and software interaction within a single FPGA chip. High assurance and fail-safe systems can now be implemented within the reconfigurable hardware fabric of an FPGA, enabling these systems to maintain flexibility and achieve high performance while providing a high level of data security. The objective of this thesis was to design and analyze an FPGA-based system containing two isolated, softcore Nios processors that share data through two crypto-engines. FPGA-based single-chip cryptographic (SCC) techniques were employed to ensure proper component isolation when the design is placed on a device supporting the appropriate security primitives. Each crypto-engine is an implementation of the Advanced Encryption Standard (AES), operating in Galois/Counter Mode (GCM) for both encryption and authentication. The features of the microprocessors and architectures of the AES crypto-engines were varied with the goal of determining combinations which best target high performance, minimal hardware usage, or a combination of the two

FPGA based technical solutions for high throughput data processing and encryption for 5G communication: A review

The field programmable gate array (FPGA) devices are ideal solutions for high-speed processing applications, given their flexibility, parallel processing capability, and power efficiency. In this review paper, at first, an overview of the key applications of FPGA-based platforms in 5G networks/systems is presented, exploiting the improved performances offered by such devices. FPGA-based implementations of cloud radio access network (C-RAN) accelerators, network function virtualization (NFV)-based network slicers, cognitive radio systems, and multiple input multiple output (MIMO) channel characterizers are the main considered applications that can benefit from the high processing rate, power efficiency and flexibility of FPGAs. Furthermore, the implementations of encryption/decryption algorithms by employing the Xilinx Zynq Ultrascale+MPSoC ZCU102 FPGA platform are discussed, and then we introduce our high-speed and lightweight implementation of the well-known AES-128 algorithm, developed on the same FPGA platform, and comparing it with similar solutions already published in the literature. The comparison results indicate that our AES-128 implementation enables efficient hardware usage for a given data-rate (up to 28.16 Gbit/s), resulting in higher efficiency (8.64 Mbps/slice) than other considered solutions. Finally, the applications of the ZCU102 platform for high-speed processing are explored, such as image and signal processing, visual recognition, and hardware resource management

Customisable arithmetic hardware designs

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REAL-TIME ADAPTIVE PULSE COMPRESSION ON RECONFIGURABLE, SYSTEM-ON-CHIP (SOC) PLATFORMS

New radar applications need to perform complex algorithms and process a large quantity of data to generate useful information for the users. This situation has motivated the search for better processing solutions that include low-power high-performance processors, efficient algorithms, and high-speed interfaces. In this work, hardware implementation of adaptive pulse compression algorithms for real-time transceiver optimization is presented, and is based on a System-on-Chip architecture for reconfigurable hardware devices. This study also evaluates the performance of dedicated coprocessors as hardware accelerator units to speed up and improve the computation of computing-intensive tasks such matrix multiplication and matrix inversion, which are essential units to solve the covariance matrix. The tradeoffs between latency and hardware utilization are also presented. Moreover, the system architecture takes advantage of the embedded processor, which is interconnected with the logic resources through high-performance buses, to perform floating-point operations, control the processing blocks, and communicate with an external PC through a customized software interface. The overall system functionality is demonstrated and tested for real-time operations using a Ku-band testbed together with a low-cost channel emulator for different types of waveforms

Cryptoraptor : high throughput reconfigurable cryptographic processor for symmetric key encryption and cryptographic hash functions

textIn cryptographic processor design, the selection of functional primitives and connection structures between these primitives are extremely crucial to maximize throughput and flexibility. Hence, detailed analysis on the specifications and requirements of existing crypto-systems plays a crucial role in cryptographic processor design. This thesis provides the most comprehensive literature review that we are aware of on the widest range of existing cryptographic algorithms, their specifications, requirements, and hardware structures. In the light of this analysis, it also describes a high performance, low power, and highly flexible cryptographic processor, Cryptoraptor, that is designed to support both today's and tomorrow's encryption standards. To the best of our knowledge, the proposed cryptographic processor supports the widest range of cryptographic algorithms compared to other solutions in the literature and is the only crypto-specific processor targeting the future standards as well. Unlike previous work, we aim for maximum throughput for all known encryption standards, and to support future standards as well. Our 1GHz design achieves a peak throughput of 128Gbps for AES-128 which is competitive with ASIC designs and has 25X and 160X higher throughput per area than CPU and GPU solutions, respectively.Electrical and Computer Engineerin

Within-Die Delay Variation Measurement And Analysis For Emerging Technologies Using An Embedded Test Structure

Both random and systematic within-die process variations (PV) are growing more severe with shrinking geometries and increasing die size. Escalation in the variations in delay and power with reductions in feature size places higher demands on the accuracy of variation models. Their availability can be used to improve yield, and the corresponding profitability and product quality of the fabricated integrated circuits (ICs). Sources of within-die variations include optical source limitations, and layout-based systematic effects (pitch, line-width variability, and microscopic etch loading). Unfortunately, accurate models of within-die PVs are becoming more difficult to derive because of their increasingly sensitivity to design-context. Embedded test structures (ETS) continue to play an important role in the development of models of PVs and as a mechanism to improve correlations between hardware and models. Variations in path delays are increasing with scaling, and are increasingly affected by neighborhood\u27 interactions. In order to fully characterize within-die variations, delays must be measured in the context of actual core-logic macros. Doing so requires the use of an embedded test structure, as opposed to traditional scribe line test structures such as ring oscillators (RO). Accurate measurements of within-die variations can be used, e.g., to better tune models to actual hardware (model-to-hardware correlations). In this research project, I propose an embedded test structure called REBEL (Regional dELay BEhavior) that is designed to measure path delays in a minimally invasive fashion; and its architecture measures the path delays more accurately. Design for manufacture-ability (DFM) analysis is done on the on 90 nm ASIC chips and 28nm Zynq 7000 series FPGA boards. I present ASIC results on within-die path delay variations in a floating-point unit (FPU) fabricated in IBM\u27s 90 nm technology, with 5 pipeline stages, used as a test vehicle in chip experiments carried out at nine different temperature/voltage (TV) corners. Also experimental data has been analyzed for path delay variations in short vs long paths. FPGA results on within-die variation and die-to-die variations on Advanced Encryption System (AES) using single pipelined stage are also presented. Other analysis that have been performed on the calibrated path delays are Flip Flop propagation delays for both rising and falling edge (tpHL and tpLH), uncertainty analysis, path distribution analysis, short versus long path variations and mid-length path within-die variation. I also analyze the impact on delay when the chips are subjected to industrial-level temperature and voltage variations. From the experimental results, it has been established that the proposed REBEL provides capabilities similar to an off-chip logic analyzer, i.e., it is able to capture the temporal behavior of the signal over time, including any static and dynamic hazards that may occur on the tested path. The ASIC results further show that path delays are correlated to the launch-capture (LC) interval used to time them. Therefore, calibration as proposed in this work must be carried out in order to obtain an accurate analysis of within-die variations. Results on ASIC chips show that short paths can vary up to 35% on average, while long paths vary up to 20% at nominal temperature and voltage. A similar trend occurs for within-die variations of mid-length paths where magnitudes reduced to 20% and 5%, respectively. The magnitude of delay variations in both these analyses increase as temperature and voltage are changed to increase performance. The high level of within-die delay variations are undesirable from a design perspective, but they represent a rich source of entropy for applications that make use of \u27secrets\u27 such as authentication, hardware metering and encryption. Physical unclonable functions (PUFs) are a class of primitives that leverage within-die-variations as a means of generating random bit strings for these types of applications, including hardware security and trust. Zynq FPGAs Die-to-Die and within-die variation study shows that on average there is 5% of within-Die variation and the range of die-to-Die variation can go upto 3ns. The die-to-Die variations can be explored in much further detail to study the variations spatial dependance. Additionally, I also carried out research in the area data mining to cater for big data by focusing the work on decision tree classification (DTC) to speed-up the classification step in hardware implementation. For this purpose, I devised a pipelined architecture for the implementation of axis parallel binary decision tree classification for meeting up with the requirements of execution time and minimal resource usage in terms of area. The motivation for this work is that analyzing larger data-sets have created abundant opportunities for algorithmic and architectural developments, and data-mining innovations, thus creating a great demand for faster execution of these algorithms, leading towards improving execution time and resource utilization. Decision trees (DT) have since been implemented in software programs. Though, the software implementation of DTC is highly accurate, the execution times and the resource utilization still require improvement to meet the computational demands in the ever growing industry. On the other hand, hardware implementation of DT has not been thoroughly investigated or reported in detail. Therefore, I propose a hardware acceleration of pipelined architecture that incorporates the parallel approach in acquiring the data by having parallel engines working on different partitions of data independently. Also, each engine is processing the data in a pipelined fashion to utilize the resources more efficiently and reduce the time for processing all the data records/tuples. Experimental results show that our proposed hardware acceleration of classification algorithms has increased throughput, by reducing the number of clock cycles required to process the data and generate the results, and it requires minimal resources hence it is area efficient. This architecture also enables algorithms to scale with increasingly large and complex data sets. We developed the DTC algorithm in detail and explored techniques for adapting it to a hardware implementation successfully. This system is 3.5 times faster than the existing hardware implementation of classification.\u2

Cryptarray A Scalable And Reconfigurable Architecture For Cryptographic Applications

Cryptography is increasingly viewed as a critical technology to fulfill the requirements of security and authentication for information exchange between Internet applications. However, software implementations of cryptographic applications are unable to support the quality of service from a bandwidth perspective required by most Internet applications. As a result, various hardware implementations, from Application-Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), to programmable processors, were proposed to improve this inadequate quality of service. Although these implementations provide performances that are considered better than those produced by software implementations, they still fall short of addressing the bandwidth requirements of most cryptographic applications in the context of the Internet for two major reasons: (i) The majority of these architectures sacrifice flexibility for performance in order to reach the performance level needed for cryptographic applications. This lack of flexibility can be detrimental considering that cryptographic standards and algorithms are still evolving. (ii) These architectures do not consider the consequences of technology scaling in general, and particularly interconnect related problems. As a result, this thesis proposes an architecture that attempts to address the requirements of cryptographic applications by overcoming the obstacles described in (i) and (ii). To this end, we propose a new reconfigurable, two-dimensional, scalable architecture, called CRYPTARRAY, in which bus-based communication is replaced by distributed shared memory communication. At the physical level, the length of the wires will be kept to a minimum. CRYPTARRAY is organized as a chessboard in which the dark and light squares represent Processing Elements (PE) and memory blocks respectively. The granularity and resource composition of the PEs is specifically designed to support the computing operations encountered in cryptographic algorithms in general, and symmetric algorithms in particular. Communication can occur only between neighboring PEs through locally shared memory blocks. Because of the chessboard layout, the architecture can be reconfigured to allow computation to proceed as a pipelined wave in any direction. This organization offers a high computational density in terms of datapath resources and a large number of distributed storage resources that easily support a high degree of parallelism and pipelining. Experimental prototyping a small array on FPGA chips shows that this architecture can run at 80.9 MHz producing 26,968,716 outputs every second in static reconfiguration mode and 20,226,537 outputs every second in dynamic reconfiguration mode

Optimising and evaluating designs for reconfigurable hardware

Growing demand for computational performance, and the rising cost for chip design and manufacturing make reconfigurable hardware increasingly attractive for digital system implementation. Reconfigurable hardware, such as field-programmable gate arrays (FPGAs), can deliver performance through parallelism while also providing flexibility to enable application builders to reconfigure them. However, reconfigurable systems, particularly those involving run-time reconfiguration, are often developed in an ad-hoc manner. Such an approach usually results in low designer productivity and can lead to inefficient designs. This thesis covers three main achievements that address this situation. The first achievement is a model that captures design parameters of reconfigurable hardware and performance parameters of a given application domain. This model supports optimisations for several design metrics such as performance, area, and power consumption. The second achievement is a technique that enhances the relocatability of bitstreams for reconfigurable devices, taking into account heterogeneous resources. This method increases the flexibility of modules represented by these bitstreams while reducing configuration storage size and design compilation time. The third achievement is a technique to characterise the power consumption of FPGAs in different activity modes. This technique includes the evaluation of standby power and dedicated low-power modes, which are crucial in meeting the requirements for battery-based mobile devices