Exploiting partial reconfiguration through PCIe for a microphone array network emulator

The current Microelectromechanical Systems (MEMS) technology enables the deployment of relatively low-cost wireless sensor networks composed of MEMS microphone arrays for accurate sound source localization. However, the evaluation and the selection of the most accurate and power-efficient network’s topology are not trivial when considering dynamic MEMS microphone arrays. Although software simulators are usually considered, they consist of high-computational intensive tasks, which require hours to days to be completed. In this paper, we present an FPGA-based platform to emulate a network of microphone arrays. Our platform provides a controlled simulated acoustic environment, able to evaluate the impact of different network configurations such as the number of microphones per array, the network’s topology, or the used detection method. Data fusion techniques, combining the data collected by each node, are used in this platform. The platform is designed to exploit the FPGA’s partial reconfiguration feature to increase the flexibility of the network emulator as well as to increase performance thanks to the use of the PCI-express high-bandwidth interface. On the one hand, the network emulator presents a higher flexibility by partially reconfiguring the nodes’ architecture in runtime. On the other hand, a set of strategies and heuristics to properly use partial reconfiguration allows the acceleration of the emulation by exploiting the execution parallelism. Several experiments are presented to demonstrate some of the capabilities of our platform and the benefits of using partial reconfiguration

Joint Optimization of Low-power DCT Architecture and Effcient Quantization Technique for Embedded Image Compression

International audienceThe Discrete Cosine Transform (DCT)-based image com- pression is widely used in today's communication systems. Signi cant research devoted to this domain has demonstrated that the optical com- pression methods can o er a higher speed but su er from bad image quality and a growing complexity. To meet the challenges of higher im- age quality and high speed processing, in this chapter, we present a joint system for DCT-based image compression by combining a VLSI archi- tecture of the DCT algorithm and an e cient quantization technique. Our approach is, rstly, based on a new granularity method in order to take advantage of the adjacent pixel correlation of the input blocks and to improve the visual quality of the reconstructed image. Second, a new architecture based on the Canonical Signed Digit and a novel Common Subexpression Elimination technique is proposed to replace the constant multipliers. Finally, a recon gurable quantization method is presented to e ectively save the computational complexity. Experimental results obtained with a prototype based on FPGA implementation and com- parisons with existing works corroborate the validity of the proposed optimizations in terms of power reduction, speed increase, silicon area saving and PSNR improvement

Analog Computing using 1T1R Crossbar Arrays

Memristor is a novel passive electronic device and a promising candidate for new generation non-volatile memory and analog computing. Analog computing based on memristors has been explored in this study. Due to the lack of commercial electrical testing instruments for those emerging devices and crossbar arrays, we have designed and built testing circuits to implement analog and parallel computing operations. With the setup developed in this study, we have successfully demonstrated image processing functions utilizing large memristor crossbar arrays. We further designed and experimentally demonstrated the first memristor based field programmable analog array (FPAA), which was successfully configured for audio equalizer and frequency classifier demonstration as exemplary applications of such memristive FPAA (memFPAA)

Efficient Architecture of Variable Size HEVC 2D-DCT for FPGA Platforms

This study presents a design of two-dimensional (2D) discrete cosine transform (DCT) hardware architecture dedicated for High Efficiency Video Coding (HEVC) in field programmable gate array (FPGA) platforms. The proposed methodology efficiently proceeds 2D-DCT computation to fit internal components and characteristics of FPGA resources. A four-stage circuit architecture is developed to implement the proposed methodology. This architecture supports variable size of DCT computation, including 4×4, 8×8, 16×16, and 32×32. The proposed architecture has been implemented in System Verilog and synthesized in various FPGA platforms. Compared with existing related works in literature, this proposed architecture demonstrates significant advantages in hardware cost and performance improvement. The proposed architecture is able to sustain 4K@30fps ultra high definition (UHD) TV real-time encoding applications with a reduction of 31-64% in hardware cost

Towards adaptive balanced computing (ABC) using reconfigurable functional caches (RFCs)

The general-purpose computing processor performs a wide range of functions. Although the performance of general-purpose processors has been steadily increasing, certain software technologies like multimedia and digital signal processing applications demand ever more computing power. Reconfigurable computing has emerged to combine the versatility of general-purpose processors with the customization ability of ASICs. The basic premise of reconfigurability is to provide better performance and higher computing density than fixed configuration processors. Most of the research in reconfigurable computing is dedicated to on-chip functional logic. If computing resources are adaptable to the computing requirement, the maximum performance can be achieved. To overcome the gap between processor and memory technology, the size of on-chip cache memory has been consistently increasing. The larger cache memory capacity, though beneficial in general, does not guarantee a higher performance for all the applications as they may not utilize all of the cache efficiently. To utilize on-chip resources effectively and to accelerate the performance of multimedia applications specifically, we propose a new architecture---Adaptive Balanced Computing (ABC). ABC uses dynamic resource configuration of on-chip cache memory by integrating Reconfigurable Functional Caches (RFC). RFC can work as a conventional cache or as a specialized computing unit when necessary. In order to convert a cache memory to a computing unit, we include additional logic to embed multi-bit output LUTs into the cache structure. We add the reconfigurability of cache memory to a conventional processor with minimal modification to the load/store microarchitecture and with minimal compiler assistance. ABC architecture utilizes resources more efficiently by reconfiguring the cache memory to computing units dynamically. The area penalty for this reconfiguration is about 50--60% of the memory cell cache array-only area with faster cache access time. In a base array cache (parallel decoding caches), the area penalty is 10--20% of the data array with 1--2% increase in the cache access time. However, we save 27% for FIR and 44% for DCT/IDCT in area with respect to memory cell array cache and about 80% for both applications with respect to base array cache if we were to implement all these units separately (such as ASICs). The simulations with multimedia and DSP applications (DCT/IDCT and FIR/IIR) show that the resource configuration with the RFC speedups ranging from 1.04X to 3.94X in overall applications and from 2.61X to 27.4X in the core computations. The simulations with various parameters indicate that the impact of reconfiguration can be minimized if an appropriate cache organization is selected

Fracturable DSP block for multi-context reconfigurable architectures

Multi-context architectures like NATURE enable low-power applications to leverage fast context switching for improved energy efficiency and lower area footprint. The NATURE architecture incorporates 16-bit reconfigurable DSP blocks for accelerating arithmetic computations, however, their fixed precision prevents efficient re-use in mixed-width arithmetic circuits. This paper presents an improved DSP block architecture for NATURE, with native support for temporal folding and run-time fracturability. The proposed DSP block can compute multiple sub-width operations in the same clock cycle and can dynamically switch between sub-width and full-width operations in different cycles. The NanoMap tool for mapping circuits onto NATURE is extended to exploit the fracturable multiplier unit incorporated in the DSP block. We demonstrate the efficiency of the proposed dynamically fracturable DSP block by implementing logic-intensive and compute-intensive benchmark applications. Our results illustrate that the fracturable DSP block can achieve a 53.7% reduction in DSP block utilization and a 42.5% reduction in area with a 122.5% reduction in power-delay product without exploiting logic folding. We also observe an average reduction of 6.43% in power-delay product for circuits that utilize NATURE’s temporal folding compared to the existing full precision DSP block in NATURE, leading to highly compact, energy efficient designs

Generic low power reconfigurable distributed arithmetic processor

Higher performance, lower cost, increasingly minimizing integrated circuit components, and higher packaging density of chips are ongoing goals of the microelectronic and computer industry. As these goals are being achieved, however, power consumption and flexibility are increasingly becoming bottlenecks that need to be addressed with the new technology in Very Large-Scale Integrated (VLSI) design. For modern systems, more energy is required to support the powerful computational capability which accords with the increasing requirements, and these requirements cause the change of standards not only in audio and video broadcasting but also in communication such as wireless connection and network protocols. Powerful flexibility and low consumption are repellent, but their combination in one system is the ultimate goal of designers. A generic domain-specific low-power reconfigurable processor for the distributed arithmetic algorithm is presented in this dissertation. This domain reconfigurable processor features high efficiency in terms of area, power and delay, which approaches the performance of an ASIC design, while retaining the flexibility of programmable platforms. The architecture not only supports typical distributed arithmetic algorithms which can be found in most still picture compression standards and video conferencing standards, but also offers implementation ability for other distributed arithmetic algorithms found in digital signal processing, telecommunication protocols and automatic control. In this processor, a simple reconfigurable low power control unit is implemented with good performance in area, power and timing. The generic characteristic of the architecture makes it applicable for any small and medium size finite state machines which can be used as control units to implement complex system behaviour and can be found in almost all engineering disciplines. Furthermore, to map target applications efficiently onto the proposed architecture, a new algorithm is introduced for searching for the best common sharing terms set and it keeps the area and power consumption of the implementation at low level. The software implementation of this algorithm is presented, which can be used not only for the proposed architecture in this dissertation but also for all the implementations with adder-based distributed arithmetic algorithms. In addition, some low power design techniques are applied in the architecture, such as unsymmetrical design style including unsymmetrical interconnection arranging, unsymmetrical PTBs selection and unsymmetrical mapping basic computing units. All these design techniques achieve extraordinary power consumption saving. It is believed that they can be extended to more low power designs and architectures. The processor presented in this dissertation can be used to implement complex, high performance distributed arithmetic algorithms for communication and image processing applications with low cost in area and power compared with the traditional methods

Large scale reconfigurable analog system design enabled through floating-gate transistors

This work is concerned with the implementation and implication of non-volatile charge storage on VLSI system design. To that end, the floating-gate pFET (fg-pFET) is considered in the context of large-scale arrays. The programming of the element in an efficient and predictable way is essential to the implementation of these systems, and is thus explored. The overhead of the control circuitry for the fg-pFET, a key scalability issue, is examined. A light-weight, trend-accurate model is absolutely necessary for VLSI system design and simulation, and is also provided. Finally, several reconfigurable and reprogrammable systems that were built are discussed.Ph.D.Committee Chair: Hasler, Paul E.; Committee Member: Anderson, David V.; Committee Member: Ayazi, Farrokh; Committee Member: Degertekin, F. Levent; Committee Member: Hunt, William D