Digital VLSI Implementation of Piecewise-Affine Controllers Based on Lattice Approach

This paper presents a small, fast, low-power consumption solution for piecewise-affine (PWA) controllers. To achieve this goal, a digital architecture for very-large-scale integration (VLSI) circuits is proposed. The implementation is based on the simplest lattice form, which eliminates the point location problem of other PWA representations and is able to provide continuous PWA controllers defined over generic partitions of the input domain. The architecture is parameterized in terms of number of inputs, outputs, signal resolution, and features of the controller to be generated. The design flows for field-programmable gate arrays and application-specific integrated circuits are detailed. Several application examples of explicit model predictive controllers (such as an adaptive cruise control and the control of a buck-boost dc-dc converter) are included to illustrate the performance of the VLSI solution obtained with the proposed lattice-based architecture

Empowering parallel computing with field programmable gate arrays

After more than 30 years, reconfigurable computing has grown from a concept to a mature field of science and technology. The cornerstone of this evolution is the field programmable gate array, a building block enabling the configuration of a custom hardware architecture. The departure from static von Neumannlike architectures opens the way to eliminate the instruction overhead and to optimize the execution speed and power consumption. FPGAs now live in a growing ecosystem of development tools, enabling software programmers to map algorithms directly onto hardware. Applications abound in many directions, including data centers, IoT, AI, image processing and space exploration. The increasing success of FPGAs is largely due to an improved toolchain with solid high-level synthesis support as well as a better integration with processor and memory systems. On the other hand, long compile times and complex design exploration remain areas for improvement. In this paper we address the evolution of FPGAs towards advanced multi-functional accelerators, discuss different programming models and their HLS language implementations, as well as high-performance tuning of FPGAs integrated into a heterogeneous platform. We pinpoint fallacies and pitfalls, and identify opportunities for language enhancements and architectural refinements

A Micro Power Hardware Fabric for Embedded Computing

Field Programmable Gate Arrays (FPGAs) mitigate many of the problemsencountered with the development of ASICs by offering flexibility, faster time-to-market, and amortized NRE costs, among other benefits. While FPGAs are increasingly being used for complex computational applications such as signal and image processing, networking, and cryptology, they are far from ideal for these tasks due to relatively high power consumption and silicon usage overheads compared to direct ASIC implementation. A reconfigurable device that exhibits ASIC-like power characteristics and FPGA-like costs and tool support is desirable to fill this void. In this research, a parameterized, reconfigurable fabric model named as domain specific fabric (DSF) is developed that exhibits ASIC-like power characteristics for Digital Signal Processing (DSP) style applications. Using this model, the impact of varying different design parameters on power and performance has been studied. Different optimization techniques like local search and simulated annealing are used to determine the appropriate interconnect for a specific set of applications. A design space exploration tool has been developed to automate and generate a tailored architectural instance of the fabric.The fabric has been synthesized on 160 nm cell-based ASIC fabrication process from OKI and 130 nm from IBM. A detailed power-performance analysis has been completed using signal and image processing benchmarks from the MediaBench benchmark suite and elsewhere with comparisons to other hardware and software implementations. The optimized fabric implemented using the 130 nm process yields energy within 3X of a direct ASIC implementation, 330X better than a Virtex-II Pro FPGA and 2016X better than an Intel XScale processor

Array-based architecture for FET-based, nanoscale electronics

Advances in our basic scientific understanding at the molecular and atomic level place us on the verge of engineering designer structures with key features at the single nanometer scale. This offers us the opportunity to design computing systems at what may be the ultimate limits on device size. At this scale, we are faced with new challenges and a new cost structure which motivates different computing architectures than we found efficient and appropriate in conventional very large scale integration (VLSI). We sketch a basic architecture for nanoscale electronics based on carbon nanotubes, silicon nanowires, and nano-scale FETs. This architecture can provide universal logic functionality with all logic and signal restoration operating at the nanoscale. The key properties of this architecture are its minimalism, defect tolerance, and compatibility with emerging bottom-up nanoscale fabrication techniques. The architecture further supports micro-to-nanoscale interfacing for communication with conventional integrated circuits and bootstrap loading

Digital VLSI Implementation of Piecewise-Affine Controllers Based on Lattice Approach

This paper presents a small, fast, low-power consumption solution for piecewise-affine (PWA) controllers. To achieve this goal, a digital architecture for very-large-scale integration (VLSI) circuits is proposed. The implementation is based on the simplest lattice form, which eliminates the point location problem of other PWA representations and is able to provide continuous PWA controllers defined over generic partitions of the input domain. The architecture is parameterized in terms of number of inputs, outputs, signal resolution, and features of the controller to be generated. The design flows for field-programmable gate arrays and application-specific integrated circuits are detailed. Several application examples of explicit model predictive controllers (such as an adaptive cruise control and the control of a buck-boost dc-dc converter) are included to illustrate the performance of the VLSI solution obtained with the proposed lattice-based architecture.Peer reviewe

OPTIMAL AREA AND PERFORMANCE MAPPING OF K-LUT BASED FPGAS

FPGA circuits are increasingly used in many fields: for rapid prototyping of new products (including fast ASIC implementation), for logic emulation, for producing a small number of a device, or if a device should be reconfigurable in use (reconfigurable computing). Determining if an arbitrary, given wide, function can be implemented by a programmable logic block, unfortunately, it is generally, a very difficult problem. This problem is called the Boolean matching problem. This paper introduces a new implemented algorithm able to map, both for area and performance, combinational networks using k-LUT based FPGAs.k-LUT based FPGAs, combinational circuits, performance-driven mapping.

Seven strategies for tolerating highly defective fabrication

In this article we present an architecture that supports fine-grained sparing and resource matching. The base logic structure is a set of interconnected PLAs. The PLAs and their interconnections consist of large arrays of interchangeable nanowires, which serve as programmable product and sum terms and as programmable interconnect links. Each nanowire can have several defective programmable junctions. We can test nanowires for functionality and use only the subset that provides appropriate conductivity and electrical characteristics. We then perform a matching between nanowire junction programmability and application logic needs to use almost all the nanowires even though most of them have defective junctions. We employ seven high-level strategies to achieve this level of defect tolerance