Platform-based design, test and fast verification flow for mixed-signal systems on chip

This research is providing methodologies to enhance the design phase from architectural space exploration and system study to verification of the whole mixed-signal system. At the beginning of the work, some innovative digital IPs have been designed to develop efficient signal conditioning for sensor systems on-chip that has been included in commercial products. After this phase, the main focus has been addressed to the creation of a re-usable and versatile test of the device after the tape-out which is close to become one of the major cost factor for ICs companies, strongly linking it to model’s test-benches to avoid re-design phases and multi-environment scenarios, producing a very effective approach to a single, fast and reliable multi-level verification environment. All these works generated different publications in scientific literature. The compound scenario concerning the development of sensor systems is presented in Chapter 1, together with an overview of the related market with a particular focus on the latest MEMS and MOEMS technology devices, and their applications in various segments. Chapter 2 introduces the state of the art for sensor interfaces: the generic sensor interface concept (based on sharing the same electronics among similar applications achieving cost saving at the expense of area and performance loss) versus the Platform Based Design methodology, which overcomes the drawbacks of the classic solution by keeping the generality at the highest design layers and customizing the platform for a target sensor achieving optimized performances. An evolution of Platform Based Design achieved by implementation into silicon of the ISIF (Intelligent Sensor InterFace) platform is therefore presented. ISIF is a highly configurable mixed-signal chip which allows designers to perform an effective design space exploration and to evaluate directly on silicon the system performances avoiding the critical and time consuming analysis required by standard platform based approach. In chapter 3 we describe the design of a smart sensor interface for conditioning next generation MOEMS. The adoption of a new, high performance and high integrated technology allow us to integrate not only a versatile platform but also a powerful ARM processor and various IPs providing the possibility to use the platform not only as a conditioning platform but also as a processing unit for the application. In this chapter a description of the various blocks is given, with a particular emphasis on the IP developed in order to grant the highest grade of flexibility with the minimum area occupation. The architectural space evaluation and the application prototyping with ISIF has enabled an effective, rapid and low risk development of a new high performance platform achieving a flexible sensor system for MEMS and MOEMS monitoring and conditioning. The platform has been design to cover very challenging test-benches, like a laser-based projector device. In this way the platform will not only be able to effectively handle the sensor but also all the system that can be built around it, reducing the needed for further electronics and resulting in an efficient test bench for the algorithm developed to drive the system. The high costs in ASIC development are mainly related to re-design phases because of missing complete top-level tests. Analog and digital parts design flows are separately verified. Starting from these considerations, in the last chapter a complete test environment for complex mixed-signal chips is presented. A semi-automatic VHDL-AMS flow to provide totally matching top-level is described and then, an evolution for fast self-checking test development for both model and real chip verification is proposed. By the introduction of a Python interface, the designer can easily perform interactive tests to cover all the features verification (e.g. calibration and trimming) into the design phase and check them all with the same environment on the real chip after the tape-out. This strategy has been tested on a consumer 3D-gyro for consumer application, in collaboration with SensorDynamics AG

The camera of the fifth H.E.S.S. telescope. Part I: System description

In July 2012, as the four ground-based gamma-ray telescopes of the H.E.S.S. (High Energy Stereoscopic System) array reached their tenth year of operation in Khomas Highlands, Namibia, a fifth telescope took its first data as part of the system. This new Cherenkov detector, comprising a 614.5 m^2 reflector with a highly pixelized camera in its focal plane, improves the sensitivity of the current array by a factor two and extends its energy domain down to a few tens of GeV. The present part I of the paper gives a detailed description of the fifth H.E.S.S. telescope's camera, presenting the details of both the hardware and the software, emphasizing the main improvements as compared to previous H.E.S.S. camera technology.Comment: 16 pages, 13 figures, accepted for publication in NIM

Portable Ultrasound Imaging

This PhD project investigates hardware strategies and imaging methods for hand-held ultrasound systems. The overall idea is to use a wireless ultrasound probe linked to general-purpose mobile devices for the processing and visualization. The approach has the potential to reduce the upfront costs of the ultrasound system and, consequently, to allow for a wide-scale utilization of diagnostic ultrasound in any medical specialties and out of the radiology department. The first part of the contribution deals with the study of hardware solutions for the reduction of the system complexity. Analog and digital beamforming strategies are simulated from a system-level perspective. The quality of the B-mode image is evaluated and the minimum specifications are derived for the design of a portable probe with integrated electronics in-handle. The system is based on a synthetic aperture sequential beamforming approach that allows to significantly reduce the data rate between the probe and processing unit. The second part investigates the feasibility of vector flow imaging in a hand-held ultrasound system. Vector flow imaging overcomes the limitations of conventional imaging methods in terms of flow angle compensation. Furthermore, high frame rate can be obtained by using synthetic aperture focusing techniques. A method is developed combining synthetic aperture sequential beamforming and directional transverse oscillation to achieve the wireless transmission of the data along with a relatively inexpensive 2-D velocity estimation. The performance of the method is thoroughly assessed through simulations and measurements, and in vivo investigations are carried out to show its potential in presence of complex flow dynamics. A sufficient frame rate is achieved to allow for the visualization of vortices in the carotid bifurcation. Furthermore, the method is implemented on a commercially available tablet to evaluate the real-time processing performance in the built-in GPU with concurrent wireless transmission of the data. Based on the demonstrations in this thesis, a flexible framework can be implemented with performance that can be scaled to the needs of the user and according to the computing resources available. The integration of high-frame-rate vector flow imaging in a hand-held ultrasound scanner, in addition, has the potential to improve the operator’s workflow and opens the way to new possibilities in the clinical practice

Design of a novel X-section architecture for FX-correlator in large interferometers : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering at Massey University, Auckland, New Zealand

Figures 2-12 and 2-17 are re-used under CC BY-NC 4.0 International & CC 3.0 Unported Licences respectively.Published journal papers I-III in the Appendices were removed because they are subject to copyright restrictions.In large radio-interferometers it is considerably challenging to perform signal correlations at input data-rates of over 11 Tbps, which involves vast amount of storage, memory bandwidth and computational hardware. The primary objective of this research work is to focus on reducing the memory-access and design complexity in matrix architectural Big Data processing of the complex X-section of an FX-correlator employed in large array radio-telescopes. This thesis presents a dedicated correlator-system-multiplier-and -accumulator (CoSMAC) cell architecture based on the real input samples from antenna arrays which produces two 16-bit complex multiplications in the same clock cycle. The novel correlator cell optimization is achieved by utilizing the flipped mirror relationship between Discrete Fourier transform (DFT) samples owing to the symmetry and periodicity of the DFT coefficient vectors. The proposed CoSMAC structure is extended to build a new processing element (PE) which calculates both cross- correlation visibilities and auto-correlation functions simultaneously. Further, a novel mathematical model and a hardware design is derived to calculate two visibilities per baseline for the Quadrature signals (IQ sampled signals, where I is In-phase signal and Q is the 90 degrees phase shifted signal) named as Processing Element for IQ sampled signals (PE_IQ). These three proposed dedicated correlator cells minimise the number of visibility calculations in a baseline. The design methodology also targets the optimisation of the multiplier size in order to reduce the power and area further in the CoSMAC, PE and PE_IQ. Various fast and efficient multiplier algorithms are compared and combined to achieve a novel multiplier named Modified-Booth-Wallace-Multiplier and implemented in the CoSMAC and PE cells. The dedicated multiplier is designed to mostly target the area and power optimisations without degrading the performance. The conventional complex-multiplier-and-accumulators (CMACs) employed to perform the complex multiplications are replaced with these dedicated ASIC correlator cells along with the optimized multipliers to reduce the overall power and area requirements in a matrix correlator architecture. The proposed architecture lowers the number of ASIC processor cells required to calculate the overall baselines in an interferometer by eliminating the redundant cells. Hence the new matrix architectural minimization is very effective in reducing the hardware complexity by nearly 50% without affecting the overall speed and performance of very large interferometers like the Square Kilometre Array (SKA)

Algorithm and Architecture Co-design for High-performance Digital Signal Processing.

CMOS scaling has been the driving force behind the revolution of digital signal processing (DSP) systems, but scaling is slowing down and the CMOS device is approaching its fundamental scaling limit. At the same time, DSP algorithms are continuing to evolve, so there is a growing gap between the increasing complexities of the algorithms and what is practically implementable. The gap can be bridged by exploring the synergy between algorithm and hardware design, using the so-called co-design techniques. In this thesis, algorithm and architecture co-design techniques are applied to X-ray computed tomography (CT) image reconstruction. Analysis of fixed-point quantization and CT geometry identifies an optimal word length and a mismatch between the object and projection grids. A water-filling buffer is designed to resolve the grid mismatch, and is combined with parallel fixed-point arithmetic units to improve the throughput. The analysis eventually leads to an out-of-order scheduling architecture that reduces the off-chip memory access by three orders of magnitude. The co-design techniques are further applied to the design of neural networks for sparse coding. Analysis of the neuron spiking dynamics leads to the optimal tuning of network size, spiking rate, and update step size to keep the spiking sparse. The resulting sparsity enables a bus-ring architecture to achieve both high throughput and scalability. A 65nm CMOS chip implementing the architecture demonstrates feature extraction at a throughput of 1.24G pixel/s at 1.0V and 310MHz. The error tolerance of sparse coding can be exploited to enhance the energy efficiency. As a natural next step after the sparse coding chip, a neural-inspired inference module (IM) is designed for object recognition. The object recognition chip consists of an IM based on sparse coding and an event-driven classifier. A learning co-processor is integrated on chip to enable on-chip learning. The throughput and energy efficiency are further improved using architectural techniques including sub-dividing the IM and classifier into modules and optimal pipelining. The result is a 65nm CMOS chip that performs sparse coding at 10.16G pixel/s at 1.0V and 635MHz. The co-design techniques can be applied to the design of other advanced DSP algorithms for emerging applications.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113344/1/jungkook_1.pd