Using Rapid Prototyping in Computer Architecture Design Laboratories

This paper describes the undergraduate computer architecture courses and laboratories introduced at Georgia Tech during the past two years. A core sequence of six required courses for computer engineering students has been developed. In this paper, emphasis is placed upon the new core laboratories which utilize commercial CAD tools, FPGAs, hardware emulators, and a VHDL based rapid prototyping approach to simulate, synthesize, and implement prototype computer hardware

Aggressive undervolting of FPGAs : power & reliability trade-offs

In this work, we evaluate aggressive undervolting, i.e., voltage underscaling below the nominal level to reduce the energy consumption of Field Programmable Gate Arrays (FPGAs). Usually, voltage guardbands are added by chip vendors to ensure the worst-case process and environmental scenarios. Through experimenting on several FPGA architectures, we con¿rm a large voltage guardband for several FPGA components, which in turn, delivers signi¿cant power savings. However, further undervolting below the voltage guardband may cause reliability issues as the result of the circuit delay increase, and faults might start to appear. We extensively characterize the behavior of these faults in terms of the rate, location, type, as well as sensitivity to environmental temperature, primarily focusing on FPGA on-chip memories, or Block RAMs (BRAMs). Understanding this behavior can allow to deploy ef¿cient mitigation techniques, and in turn, FPGA-based designs can be improved for better energy, reliability, and performance trade-offs. Finally, as a case study, we evaluate a typical FPGA-based Neural Network (NN) accelerator when the FPGA voltage is underscaled. In consequence, the substantial NN energy savings come with the cost of NN accuracy loss. To attain power savings without NN accuracy loss below the voltage guardband gap, we proposed an application-aware technique and we also, evaluated the built-in Error-Correcting Code (ECC) mechanism. Hence, First, we developed an application-dependent BRAMs placement technique that relies on the deterministic behavior of undervolting faults, and mitigates these faults by mapping the most reliability sensitive NN parameters to BRAM blocks that are relatively more resistant to undervolting faults. Second, as a more general technique, we applied the built-in ECC of BRAMs and observed a signi¿cant fault coverage capability thanks to the behavior of undervolting faults, with a negligible power consumption overhead.En este trabajo, evaluamos el reducir el voltaje en forma agresiva, es decir, bajar la tensión por debajo del nivel nominal para reducir el consumo de energía en Field Programmable Gate Arrays (FPGA). Por lo general, los vendedores de chips establecen margen de seguridad al voltaje para garantizar el funcionamiento de los mismos en el peor de los casos y en los peores escenarios ambientales. Mediante la experimentación en varias arquitecturas FPGA, confirmamos que hay un margen de seguridad de voltaje grande en varios de los componentes de la FPGA, que a su vez, nos ofrece ahorros de energía significativos. Sin embargo, un trabajar a un voltaje por debajo del margen de seguridad del voltaje puede causar problemas de confiabilidad a medida ya que aumenta el retardo del circuito y pueden comenzar a aparecer fallos. Caracterizamos ampliamente el comportamiento de estos fallos en términos de velocidad, ubicación, tipo, así como la sensibilidad a la temperatura ambiental, centrándonos principalmente en memorias internas de la FPGA, o Block RAM (BRAM). Comprender este comportamiento puede permitir el desarrollo de técnicas eficientes de mitigación y, a su vez, mejorar los diseños basados en FPGA para obtener ahorros en energía, una mayor confiabilidad y un mayor rendimiento. Finalmente, como caso de estudio, evaluamos un acelerador típico de Redes Neuronales basado en FPGA cuando el voltaje de la FPGA esta por debajo del nivel mínimo de seguridad. En consecuencia, los considerables ahorros de energía de la red neuronal vienen asociados con la pérdida de precisión de la red neuronal. Para obtener ahorros de energía sin una pérdida de precisión en la red neuronal por debajo del margen de seguridad del voltaje, proponemos una técnica que tiene en cuenta la aplicación, asi mismo, evaluamos el mecanismo integrado en las BRAMs de Error Correction Code (ECC). Por lo tanto, en primer lugar, desarrollamos una técnica de colocación de BRAM dependiente de la aplicación que se basa en el comportamiento determinista de las fallos cuando la FPGA funciona por debajo del margen de seguridad, y se mitigan estos fallos asignando los parámetros de la red neuronal más sensibles a producir fallos a los bloques BRAM que son relativamente más resistentes a los fallos. En segundo lugar, como técnica más general, aplicamos el ECC incorporado de los BRAM y observamos una capacidad de cobertura de fallos significativo gracias a las características de comportamiento de fallos, con una sobrecoste de consumo de energía insignificantePostprint (published version

Teaching Hardware Reverse Engineering: Educational Guidelines and Practical Insights

Since underlying hardware components form the basis of trust in virtually any computing system, security failures in hardware pose a devastating threat to our daily lives. Hardware reverse engineering is commonly employed by security engineers in order to identify security vulnerabilities, to detect IP violations, or to conduct very-large-scale integration (VLSI) failure analysis. Even though industry and the scientific community demand experts with expertise in hardware reverse engineering, there is a lack of educational offerings, and existing training is almost entirely unstructured and on the job. To the best of our knowledge, we have developed the first course to systematically teach students hardware reverse engineering based on insights from the fields of educational research, cognitive science, and hardware security. The contribution of our work is threefold: (1) we propose underlying educational guidelines for practice-oriented courses which teach hardware reverse engineering; (2) we develop such a lab course with a special focus on gate-level netlist reverse engineering and provide the required tools to support it; (3) we conduct an educational evaluation of our pilot course. Based on our results, we provide valuable insights on the structure and content necessary to design and teach future courses on hardware reverse engineering

FPGA in image processing supported by IOPT-Flow

Image processing is widely used in the most diverse industries. One of the tools widely used to perform image processing is the OpenCV library. Although the implementation of image processing algorithms can be made in software, it is also possible to implement image processing algorithms in hardware. In some cases, the execution time can be smaller than the execution time achieved in software. This work main goal is to evaluate the use of VHDL, DS-Pnets, and IOPT-Flow to develop image processing systems in hardware, in FPGA-based platforms. To enable it, a validation platform was developed. A set of image processing algorithms were specified, during this work, in VHDL and/or in DS-Pnets. These were validated using the IOPT-Flow validation tool and/or the Xilinx ISE Simulator. The automatic VHDL code generator from IOPT-Flow framework was used to translate DS-Pnet models into the implementation code. The FPGA-based implementations were compared with software implementations, supported by the OpenCV library. The created DS-Pnet models were added into a folder of the IOPT-Flow editor, to create an image processing library. It was possible to conclude that the DS-Pnets and their associated tools, IOPT-Flow tools, support the development of image processing systems. These tools, which simplify the development of image processing systems, are available online at http://gres.uninova.pt/iopt-flow/

Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

Efficient FPGA implementation and power modelling of image and signal processing IP cores

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Field Programmable Gate Arrays (FPGAs) are the technology of choice in a number ofimage and signal processing application areas such as consumer electronics, instrumentation, medical data processing and avionics due to their reasonable energy consumption, high performance, security, low design-turnaround time and reconfigurability. Low power FPGA devices are also emerging as competitive solutions for mobile and thermally constrained platforms. Most computationally intensive image and signal processing algorithms also consume a lot of power leading to a number of issues including reduced mobility, reliability concerns and increased design cost among others. Power dissipation has become one of the most important challenges, particularly for FPGAs. Addressing this problem requires optimisation and awareness at all levels in the design flow. The key achievements of the work presented in this thesis are summarised here. Behavioural level optimisation strategies have been used for implementing matrix product and inner product through the use of mathematical techniques such as Distributed Arithmetic (DA) and its variations including offset binary coding, sparse factorisation and novel vector level transformations. Applications to test the impact of these algorithmic and arithmetic transformations include the fast Hadamard/Walsh transforms and Gaussian mixture models. Complete design space exploration has been performed on these cores, and where appropriate, they have been shown to clearly outperform comparable existing implementations. At the architectural level, strategies such as parallelism, pipelining and systolisation have been successfully applied for the design and optimisation of a number of cores including colour space conversion, finite Radon transform, finite ridgelet transform and circular convolution. A pioneering study into the influence of supply voltage scaling for FPGA based designs, used in conjunction with performance enhancing strategies such as parallelism and pipelining has been performed. Initial results are very promising and indicated significant potential for future research in this area. A key contribution of this work includes the development of a novel high level power macromodelling technique for design space exploration and characterisation of custom IP cores for FPGAs, called Functional Level Power Analysis and Modelling (FLPAM). FLPAM is scalable, platform independent and compares favourably with existing approaches. A hybrid, top-down design flow paradigm integrating FLPAM with commercially available design tools for systematic optimisation of IP cores has also been developed

CAD Techniques for Robust FPGA Design Under Variability

The imperfections in the semiconductor fabrication process and uncertainty in operating environment of VLSI circuits have emerged as critical challenges for the semiconductor industry. These are generally termed as process and environment variations, which lead to uncertainty in performance and unreliable operation of the circuits. These problems have been further aggravated in scaled nanometer technologies due to increased process variations and reduced operating voltage. Several techniques have been proposed recently for designing digital VLSI circuits under variability. However, most of them have targeted ASICs and custom designs. The flexibility of reconfiguration and unknown end application in FPGAs make design under variability different for FPGAs compared to ASICs and custom designs, and the techniques proposed for ASICs and custom designs cannot be directly applied to FPGAs. An important design consideration is to minimize the modifications in architecture and circuit to reduce the cost of changing the existing FPGA architecture and circuit. The focus of this work can be divided into three principal categories, which are, improving timing yield under process variations, improving power yield under process variations and improving the voltage profile in the FPGA power grid. The work on timing yield improvement proposes routing architecture enhancements along with CAD techniques to improve the timing yield of FPGA designs. The work on power yield improvement for FPGAs selects a low power dual-Vdd FPGA design as the baseline FPGA architecture for developing power yield enhancement techniques. It proposes CAD techniques to improve the power yield of FPGAs. A mathematical programming technique is proposed to determine the parameters of the buffers in the interconnect such as the sizes of the transistors and threshold voltage of the transistors, all within constraints, such that the leakage variability is minimized under delay constraints. Two CAD techniques are investigated and proposed to improve the supply voltage profile of the power grids in FPGAs. The first technique is a place and route technique and the second technique is a logic clustering technique to reduce IR-drops and spatial variation of supply voltage in the power grid