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

A Low-Power DSP Architecture for a Fully Implantable Cochlear Implant System-on-a-Chip.

The National Science Foundation Wireless Integrated Microsystems (WIMS) Engineering Research Center at the University of Michigan developed Systems-on-a-Chip to achieve biomedical implant and environmental monitoring functionality in low-milliwatt power consumption and 1-2 cm3 volume. The focus of this work is implantable electronics for cochlear implants (CIs), surgically implanted devices that utilize existing nerve connections between the brain and inner-ear in cases where degradation of the sensory hair cells in the cochlea has occurred. In the absence of functioning hair cells, a CI processes sound information and stimulates the nderlying nerve cells with currents from implanted electrodes, enabling the patient to understand speech. As the brain of the WIMS CI, the WIMS microcontroller unit (MCU) delivers the communication, signal processing, and storage capabilities required to satisfy the aggressive goals set forth. The 16-bit MCU implements a custom instruction set architecture focusing on power-efficient execution by providing separate data and address register windows, multi-word arithmetic, eight addressing modes, and interrupt and subroutine support. Along with 32KB of on-chip SRAM, a low-power 512-byte scratchpad memory is utilized by the WIMS custom compiler to obtain an average of 18% energy savings across benchmarks. A synthesizable dynamic frequency scaling circuit allows the chip to select a precision on-chip LC or ring oscillator, and perform clock scaling to minimize power dissipation; it provides glitch-free, software-controlled frequency shifting in 100ns, and dissipates only 480μW. A highly flexible and expandable 16-channel Continuous Interleaved Sampling Digital Signal Processor (DSP) is included as an MCU peripheral component. Modes are included to process data, stimulate through electrodes, and allow experimental stimulation or processing. The entire WIMS MCU occupies 9.18mm2 and consumes only 1.79mW from 1.2V in DSP mode. This is the lowest reported consumption for a cochlear DSP. Design methodologies were analyzed and a new top-down design flow is presented that encourages hardware and software co-design as well as cross-domain verification early in the design process. An O(n) technique for energy-per-instruction estimations both pre- and post-silicon is presented that achieves less than 4% error across benchmarks. This dissertation advances low-power system design while providing an improvement in hearing recovery devices.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91488/1/emarsman_1.pd

Application specific instruction set processor design for embedded application using the coware tool

An Application Specific Instruction Set Processor (ASIP) is widely used as a System on a Chip(SoC) Component. ASIPs possess an instruction set which is tai-lored to benefit a specific application. Such specialization allows ASIPs to serve as an intermediate between two dominant processor design styles- ASICs which has high processing abilities at the cost of limited programmability and Programmable solu-tions such as FPGAs that provide programming exibility at the cost of less energy eficiency. In this dissertation the goal is to design ASIP, keeping in mind a temper-ature sensor system. The platform used for processor design is LISA 2.0 description language and processor designing environment from CoWare. Coware processor de-signer allows processor architecture to be defined at an abstract level and automatic generation of chain of software tools like assembler, linker and simulator for functional verification followed by RTL level description. RTL level description is used to gen-erate synthesized report of the design using RTL compiler and finally the layout is created using Cadence encounter

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.The research leading to these results has received funding from the Spanish Government and European FEDER funds (DPI2012-32390), the Valencia Regional Government (PROMETEO/2013/085) and the University of Alicante (GRE12-17)

An Investigation towards Effectiveness in Image Enhancement Process in MPSoC

Image enhancement has a primitive role in the vision-based applications. It involves the processing of the input image by boosting its visualization for various applications. The primary objective is to filter the unwanted noises, clutters, sharpening or blur. The characteristics such as resolution and contrast are constructively altered to obtain an outcome of an enhanced image in the bio-medical field. The paper highlights the different techniques proposed for the digital enhancement of images. After surveying these methods that utilize Multiprocessor System-on-Chip (MPSoC), it is concluded that these methodologies have little accuracy and hence none of them are efficiently capable of enhancing the digital biomedical images