1,552 research outputs found
Scalable Energy-Recovery Architectures.
Energy efficiency is a critical challenge for today's integrated circuits, especially for high-end digital signal processing and communications that require both high throughput and low energy dissipation for extended battery life. Charge-recovery logic recovers and reuses charge using inductive elements and has the potential to achieve order-of-magnitude improvement in energy efficiency while maintaining high performance. However, the lack of large-scale high-speed silicon demonstrations and inductor area overheads are two major concerns.
This dissertation focuses on scalable charge-recovery designs. We present a semi-automated design flow to enable the design of large-scale charge-recovery chips. We also present a new architecture that uses in-package inductors, eliminating the area overheads caused by the use of integrated inductors in high-performance charge-recovery chips.
To demonstrate our semi-automated flow, which uses custom-designed standard-cell-like dynamic cells, we have designed a 576-bit charge-recovery low-density parity-check (LDPC) decoder chip. Functioning correctly at clock speeds above 1 GHz, this prototype is the first-ever demonstration of a GHz-speed charge-recovery chip of significant complexity. In terms of energy consumption, this chip improves over recent state-of-the-art LDPCs by at least 1.3 times with comparable or better area efficiency.
To demonstrate our architecture for eliminating inductor overheads, we have designed a charge-recovery LDPC decoder chip with in-package inductors. This test-chip has been fabricated in a 65nm CMOS flip-chip process. A custom 6-layer FC-BGA package substrate has been designed with 16 inductors embedded in the fifth layer of the package substrate, yielding higher Q and significantly improving area efficiency and energy efficiency compared to their on-chip counterparts. From measurements, this chip achieves at least 2.3 times lower energy consumption with better area efficiency over state-of-the-art published designs.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116653/1/terryou_1.pd
System-on-chip Computing and Interconnection Architectures for Telecommunications and Signal Processing
This dissertation proposes novel architectures and design techniques targeting SoC building blocks for telecommunications and signal processing applications.
Hardware implementation of Low-Density Parity-Check decoders is approached at both the algorithmic and the architecture level. Low-Density Parity-Check codes are a promising coding scheme for future communication standards due to their outstanding error correction performance.
This work proposes a methodology for analyzing effects of finite precision arithmetic on error correction performance and hardware complexity. The methodology is throughout employed for co-designing the decoder. First, a low-complexity check node based on the P-output decoding principle is designed and characterized on a CMOS standard-cells library. Results demonstrate implementation loss below 0.2 dB down to BER of 10^{-8} and a saving in complexity up to 59% with respect to other works in recent literature. High-throughput and low-latency issues are addressed with modified single-phase decoding schedules. A new "memory-aware" schedule is proposed requiring down to 20% of memory with respect to the traditional two-phase flooding decoding. Additionally, throughput is doubled and logic complexity reduced of 12%. These advantages are traded-off with error correction performance, thus making the solution attractive only for long codes, as those adopted in the DVB-S2 standard. The "layered decoding" principle is extended to those codes not specifically conceived for this technique. Proposed architectures exhibit complexity savings in the order of 40% for both area and power consumption figures, while implementation loss is smaller than 0.05 dB.
Most modern communication standards employ Orthogonal Frequency Division Multiplexing as part of their physical layer. The core of OFDM is the Fast Fourier Transform and its inverse in charge of symbols (de)modulation. Requirements on throughput and energy efficiency call for FFT hardware implementation, while ubiquity of FFT suggests the design of parametric, re-configurable and re-usable IP hardware macrocells. In this context, this thesis describes an FFT/IFFT core compiler particularly suited for implementation of OFDM communication systems. The tool employs an accuracy-driven configuration engine which automatically profiles the internal arithmetic and generates a core with minimum operands bit-width and thus minimum circuit complexity. The engine performs a closed-loop optimization over three different internal arithmetic models (fixed-point, block floating-point and convergent block floating-point) using the numerical accuracy budget given by the user as a reference point. The flexibility and re-usability of the proposed macrocell are illustrated through several case studies which encompass all current state-of-the-art OFDM communications standards (WLAN, WMAN, xDSL, DVB-T/H, DAB and UWB). Implementations results are presented for two deep sub-micron standard-cells libraries (65 and 90 nm) and commercially available FPGA devices. Compared with other FFT core compilers, the proposed environment produces macrocells with lower circuit complexity and same system level performance (throughput, transform size and numerical accuracy).
The final part of this dissertation focuses on the Network-on-Chip design paradigm whose goal is building scalable communication infrastructures connecting hundreds of core. A low-complexity link architecture for mesochronous on-chip communication is discussed. The link enables skew constraint looseness in the clock tree synthesis, frequency speed-up, power consumption reduction and faster back-end turnarounds. The proposed architecture reaches a maximum clock frequency of 1 GHz on 65 nm low-leakage CMOS standard-cells library. In a complex test case with a full-blown NoC infrastructure, the link overhead is only 3% of chip area and 0.5% of leakage power consumption.
Finally, a new methodology, named metacoding, is proposed. Metacoding generates correct-by-construction technology independent RTL codebases for NoC building blocks. The RTL coding phase is abstracted and modeled with an Object Oriented framework, integrated within a commercial tool for IP packaging (Synopsys CoreTools suite). Compared with traditional coding styles based on pre-processor directives, metacoding produces 65% smaller codebases and reduces the configurations to verify up to three orders of magnitude
Baseband analog front-end and digital back-end for reconfigurable multi-standard terminals
Multimedia applications are driving wireless network operators to add high-speed data services such as Edge (E-GPRS), WCDMA (UMTS) and WLAN (IEEE 802.11a,b,g) to the existing GSM network. This creates the need for multi-mode cellular handsets that support a wide range of communication standards, each with a different RF frequency, signal bandwidth, modulation scheme etc. This in turn generates several design challenges for the analog and digital building blocks of the physical layer. In addition to the above-mentioned protocols, mobile devices often include Bluetooth, GPS, FM-radio and TV services that can work concurrently with data and voice communication. Multi-mode, multi-band, and multi-standard mobile terminals must satisfy all these different requirements. Sharing and/or switching transceiver building blocks in these handsets is mandatory in order to extend battery life and/or reduce cost. Only adaptive circuits that are able to reconfigure themselves within the handover time can meet the design requirements of a single receiver or transmitter covering all the different standards while ensuring seamless inter-interoperability. This paper presents analog and digital base-band circuits that are able to support GSM (with Edge), WCDMA (UMTS), WLAN and Bluetooth using reconfigurable building blocks. The blocks can trade off power consumption for performance on the fly, depending on the standard to be supported and the required QoS (Quality of Service) leve
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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
Novel Front-end Electronics for Time Projection Chamber Detectors
Este trabajo ha sido realizado en la OrganizaciĆ³n Europea para la InvestigaciĆ³n Nuclear (CERN) y forma parte del proyecto de investigaciĆ³n Europeo para futuros aceleradores lineales (EUDET).
En fĆsica de partĆculas existen diferentes categorĆas de detectores de partĆculas. El diseƱo presentado esta centrado en un tipo particular de detector de trayectoria de partĆculas denominado TPC (Time Projection Chamber) que proporciona una imagen en tres dimensiones de las partĆculas elĆ©ctricamente cargadas que atraviesan su volumen gaseoso.
La tesis incluye un estudio de los objetivos para futuros detectores, resumiendo los parĆ”metros que un sistema de adquisiciĆ³n de datos debe cumplir en esos casos. AdemĆ”s, estos requisitos son comparados con los actuales sistemas de lectura utilizados en diferentes detectores TPC. Se concluye que ninguno de los sistemas cumple las restrictivas condiciones. Algunos de los principales objetivos para futuros detectores TPC son un altĆsimo nivel de integraciĆ³n, incremento del nĆŗmero de canales, electrĆ³nica mĆ”s rĆ”pida y muy baja potencia.
El principal inconveniente del estado del arte de los sistemas anteriores es la utilizaciĆ³n de varios circuitos integrados en la cadena de adquisiciĆ³n. Este hecho hace imposible alcanzar el altĆsimo nivel de integraciĆ³n requerido para futuros detectores. AdemĆ”s, un aumento del nĆŗmero de canales y frecuencia de muestreo harĆa incrementar hasta valores no permitidos la potencia utilizada. Y en consecuencia, incrementar la refrigeraciĆ³n necesaria (en caso de ser posible).
Una de las novedades presentadas es la integraciĆ³n de toda la cadena de adquisiciĆ³n (filtros analĆ³gicos de entrada, conversor analĆ³gico-digital (ADC) y procesado de seƱal digital) en un Ćŗnico circuito integrado en tecnologĆa de 130nm. Este chip es el primero que realiza esta altĆsima integraciĆ³n para detectores TPC.
Por otro lado, se presenta un anĆ”lisis detallado de los filtros de procesado de seƱal. Los objetivos mĆ”s importantes es la reducciĆ³GarcĆa GarcĆa, EJ. (2012). Novel Front-end Electronics for Time Projection Chamber Detectors [Tesis doctoral no publicada]. Universitat PolitĆØcnica de ValĆØncia. https://doi.org/10.4995/Thesis/10251/16980Palanci
FPGAs in Industrial Control Applications
The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs
Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
DNN accelerators are often developed and evaluated in isolation without
considering the cross-stack, system-level effects in real-world environments.
This makes it difficult to appreciate the impact of System-on-Chip (SoC)
resource contention, OS overheads, and programming-stack inefficiencies on
overall performance/energy-efficiency. To address this challenge, we present
Gemmini, an open-source*, full-stack DNN accelerator generator. Gemmini
generates a wide design-space of efficient ASIC accelerators from a flexible
architectural template, together with flexible programming stacks and full SoCs
with shared resources that capture system-level effects. Gemmini-generated
accelerators have also been fabricated, delivering up to three
orders-of-magnitude speedups over high-performance CPUs on various DNN
benchmarks.
* https://github.com/ucb-bar/gemminiComment: To appear at the 58th IEEE/ACM Design Automation Conference (DAC),
December 2021, San Francisco, CA, US
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Efficient architectures and power modelling of multiresolution analysis algorithms on FPGA
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In the past two decades, there has been huge amount of interest in Multiresolution Analysis Algorithms (MAAs) and their applications. Processing some of their applications such as medical imaging are computationally intensive, power hungry and requires large amount of memory which cause a high demand for efficient algorithm implementation, low power architecture and acceleration. Recently, some MAAs such as Finite Ridgelet Transform (FRIT) Haar Wavelet Transform (HWT) are became very popular and they are suitable for a number of image processing applications such as detection of line singularities and contiguous edges, edge detection (useful for compression and feature detection), medical image denoising and segmentation. Efficient hardware implementation and acceleration of these algorithms particularly when addressing large problems are becoming very chal-lenging and consume lot of power which leads to a number of issues including mobility, reliability concerns. To overcome the computation problems, Field Programmable Gate Arrays (FPGAs) are the technology of choice for accelerating computationally intensive applications due to their high performance. Addressing the power issue requires optimi- sation and awareness at all level of abstractions in the design flow.
The most important achievements of the work presented in this thesis are summarised
here.
Two factorisation methodologies for HWT which are called HWT Factorisation Method1 and (HWTFM1) and HWT Factorasation Method2 (HWTFM2) have been explored to increase number of zeros and reduce hardware resources. In addition, two novel efficient and optimised architectures for proposed methodologies based on Distributed Arithmetic (DA) principles have been proposed. The evaluation of the architectural results have shown that the proposed architectures results have reduced the arithmetics calculation (additions/subtractions) by 33% and 25% respectively compared to direct implementa-tion of HWT and outperformed existing results in place. The proposed HWTFM2 is implemented on advanced and low power FPGA devices using Handel-C language. The FPGAs implementation results have outperformed other existing results in terms of area and maximum frequency. In addition, a novel efficient architecture for Finite Radon Trans-form (FRAT) has also been proposed. The proposed architecture is integrated with the developed HWT architecture to build an optimised architecture for FRIT. Strategies such as parallelism and pipelining have been deployed at the architectural level for efficient im-plementation on different FPGA devices. The proposed FRIT architecture performance has been evaluated and the results outperformed some other existing architecture in place. Both FRAT and FRIT architectures have been implemented on FPGAs using Handel-C language. The evaluation of both architectures have shown that the obtained results out-performed existing results in place by almost 10% in terms of frequency and area. The proposed architectures are also applied on image data (256 Ā£ 256) and their Peak Signal to Noise Ratio (PSNR) is evaluated for quality purposes.
Two architectures for cyclic convolution based on systolic array using parallelism and pipelining which can be used as the main building block for the proposed FRIT architec-ture have been proposed. The first proposed architecture is a linear systolic array with pipelining process and the second architecture is a systolic array with parallel process. The second architecture reduces the number of registers by 42% compare to first architec-ture and both architectures outperformed other existing results in place. The proposed pipelined architecture has been implemented on different FPGA devices with vector size (N) 4,8,16,32 and word-length (W=8). The implementation results have shown a signifi-cant improvement and outperformed other existing results in place.
Ultimately, an in-depth evaluation of a high level power macromodelling technique for design space exploration and characterisation of custom IP cores for FPGAs, called func-tional level power modelling approach have been presented. The mathematical techniques that form the basis of the proposed power modeling has been validated by a range of custom IP cores. The proposed power modelling is scalable, platform independent and compares favorably with existing approaches. A hybrid, top-down design flow paradigm integrating functional level power modelling with commercially available design tools for systematic optimisation of IP cores has also been developed. The in-depth evaluation of this tool enables us to observe the behavior of different custom IP cores in terms of power consumption and accuracy using different design methodologies and arithmetic techniques on virous FPGA platforms. Based on the results achieved, the proposed model accuracy is almost 99% true for all IP core's Dynamic Power (DP) components.Thomas Gerald Gray Charitable Trus
High Peformance and Low Power On-Die Interconnect Fabrics.
Increasing power density with technology scaling has caused stagnation in operating frequency of modern day microprocessors. This has led designers to prefer multicore architectures over complex monolithic processors to keep up with the demand for rising computing throughput. Although processing units are getting smaller and simpler, the dramatic rise of their count on a single die has made the fabric that connects these processing units increasingly complex. These interconnect fabrics have become a bottleneck in improving overall system effciency. As a result, the design paradigm for multi-core chips is gradually shifting from a core-centric architecture towards an interconnect-centric architecture, where system efficiency is limited by the fabric rather than the processing ability of any individual core. This dissertation introduces three novel and synergistic circuit techniques to improve scalability of switch fabrics to make on-die integration of hundreds to thousands of cores feasible. 1) A matrix topology is proposed for designing a fully connected switch fabric that re-uses output buses for programming, and stores shue congurations at cross points. This significantly reduces routing congestion, lowers area/power, and improves per-
formance. Silicon measurements demonstrate 47% energy savings in a 64-lane SIMD processor fabricated in 65nm CMOS over a conventional implementation. 2) A novel approach to handle high radix arbitration along with data routing is proposed. It optimally uses existing cross-bar interconnect resources without requiring any additional overhead. Bandwidth exceeding 2Tb/s is recorded in a test prototype fabricated in 65nm. 3) Building on the later, a new circuit topology to manage and update priority adaptively within the switch fabric without incurring additional delay or area is then proposed. Several assist circuit techniques, such as a thyristor based sense amplifier and self regenerating bi-directional repeaters are proposed for high speed energy efficient signaling to and from the switch fabric to improve overall routing efficiency.
Using these techniques a 64 x 64 switch fabric with 128b data bus fabricated in 45nm achieves a throughput of 4.5Tb/s at single cycle latency while operating at 559MHz.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91506/1/sudhirks_1.pd
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