A Tool for the Automatic Generation and Analysis of Regular Analog Layout Modules

This paper describes the characteristics of a new CAD tool that enables the creation of layout libraries of selected analog modules. This Analog Modules Generator (AMG) automatically creates multiple layout versions of two commonly used analog structures: the differential pair and arrays of series-connected or stacked devices, for the subsequent generation of layout libraries. Based on the number of devices and rows defined by the user for the layout implementation, the tool validates all possible implementations, which are later saved in a database with their corresponding characteristics, such as area and parasitics information. Additionally, an extraction process can be optionally executed over all the layout views saved in the database. The AMG generates several reports with all the characteristics of the implemented layouts, including area and parasitic components, facilitating further statistical processing. We describe the features and capabilities of the proposed AMG tool, and several test cases are presented. Results show that optimal layout implementations can be achieved by layout and circuit designers in a reduced amount of time

Digital-to-Analog Converter Interface for Computer Assisted Biologically Inspired Systems

In today\u27s integrated circuit technology, system interfaces play an important role of enabling fast, reliable data communications. A key feature of this work is the exploration and development of ultra-low power data converters. Data converters are present in some form in almost all mixed-signal systems; in particular, digital-to-analog converters present the opportunity for digitally controlled analog signal sources. Such signal sources are used in a variety of applications such as neuromorphic systems and analog signal processing. Multi-dimensional systems, such as biologically inspired neuromorphic systems, require vectors of analog signals. To use a microprocessor to control these analog systems, we must ultimately convert the digital control signal to an analog control signal and deliver it to the system. Integrating such capabilities of a converter on chip can yield significant power and chip area constraints. Special attention is paid to the power efficiency of the data converter, the data converter design discussed in this thesis yields the lowest power consumption to date. The need for a converter with these properties leads us to the concept of a scalable array of power-efficient digital-to-analog converters; the channels of which are time-domain multiplexed so that chip-area is minimized while preserving performance. To take further advantage of microprocessor capabilities, an analog-to- digital design is proposed to return the analog system\u27s outputs to the microprocessor in a digital form. A current-steering digital-to-analog converter was chosen as a candidate for the conversion process because of its natural speed and voltage-to-current translation properties. This choice is nevertheless unusual, because current-steering digital- to-analog converters have a reputation for high performance with high power consumption. A time domain multiplexing scheme is presented such that a digital data set of any size is synchronously multiplexed through a finite array of converters, minimizing the total area and power consumption. I demonstrate the suitability of current-steering digital-to-analog converters for ultra low-power operation with a proof-of-concept design in a widely available 130 nm CMOS technology. In statistical simulation, the proposed digital-to-analog converter was capable of 8-bit, 100 kSps operation while consuming 231 nW of power from a 1 V supply

A framework for fine-grain synthesis optimization of operational amplifiers

This thesis presents a cell-level framework for Operational Amplifiers Synthesis (OASYN) coupling both circuit design and layout. For circuit design, the tool applies a corner-driven optimization, accounting for on-chip performance variations. By exploring the process, voltage, and temperature variations space, the tool extracts design worst case solution. The tool undergoes sensitivity analysis along with Pareto-optimality to achieve required specifications. For layout phase, OASYN generates a DRC proved automated layout based on a sized circuit-level description. Morata et al. (1996) introduced an elegant representation of block placement called sequence pair for general floorplans (SP). Like TCG and BSG, but unlike O-tree, B*tree, and CBL, SP is P-admissible. Unlike SP, TCG supports incremental update during operation and keeps the information of the boundary modules as well as their relative positions in the representation. Block placement algorithms that are based on SP use heuristic optimization algorithms, e.g., simulated annealing where generation of large number of sequence pairs are required. Therefore a fast algorithm is needed to generate sequence pairs after each solution perturbation. The thesis presents a new simple and efficient O(n) runtime algorithm for fast realization of incremental update for cost evaluation. The algorithm integrates sequence pair and transitive closure graph advantages into TCG-S* a superior topology update scheme which facilitates the search for optimum desired floorplan. Experiments show that TCG-S* is better than existing works in terms of area utilization and convergence speed. Routing-aware placement is implemented in OASYN, handling symmetry constraints, e.g., interdigitization, common centroid, along with congestion elimination and the enhancement of placement routability

A Bio-Inspired Two-Layer Mixed-Signal Flexible Programmable Chip for Early Vision

A bio-inspired model for an analog programmable array processor (APAP), based on studies on the vertebrate retina, has permitted the realization of complex programmable spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the visual pathway, what renders a feasible alternative for the implementation of early vision tasks in standard technologies. A prototype chip has been designed and fabricated in 0.5 μm CMOS. It renders a computing power per silicon area and power consumption that is amongst the highest reported for a single chip. The details of the bio-inspired network model, the analog building block design challenges and trade-offs and some functional tests results are presented in this paper.Office of Naval Research (USA) N-000140210884European Commission IST-1999-19007Ministerio de Ciencia y Tecnología TIC1999-082

Secrecy Energy Efficiency of MIMOME Wiretap Channels with Full-Duplex Jamming

Full-duplex (FD) jamming transceivers are recently shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this work, we investigate if FD jamming can also improve the systems secrecy energy efficiency (SEE) in terms of securely communicated bits-per- Joule, when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high Signal-to-noise ratio (SNR), or for a bidirectional FD communication setup.Comment: IEEE Transactions on Communication

A Multi-objective Perspective for Operator Scheduling using Fine-grained DVS Architecture

The stringent power budget of fine grained power managed digital integrated circuits have driven chip designers to optimize power at the cost of area and delay, which were the traditional cost criteria for circuit optimization. The emerging scenario motivates us to revisit the classical operator scheduling problem under the availability of DVFS enabled functional units that can trade-off cycles with power. We study the design space defined due to this trade-off and present a branch-and-bound(B/B) algorithm to explore this state space and report the pareto-optimal front with respect to area and power. The scheduling also aims at maximum resource sharing and is able to attain sufficient area and power gains for complex benchmarks when timing constraints are relaxed by sufficient amount. Experimental results show that the algorithm that operates without any user constraint(area/power) is able to solve the problem for most available benchmarks, and the use of power budget or area budget constraints leads to significant performance gain.Comment: 18 pages, 6 figures, International journal of VLSI design & Communication Systems (VLSICS

Modern FPGA placement techniques with hardware acceleration

In deep sub-micron technology nodes, Application-Specific Integrated Circuits (ASICs) are becoming expensive to design and manufacture. For this reason, Field Programmable Gate Arrays (FPGAs), which are general purpose and flexible programmable hardware, are gaining more design wins in low volume and fast evolving applications. Modern FPGAs are becoming popular in high performance data analytics, search engines, autonomous cars, communication and networking applications. FPGAs are also accompanied with a complete Computer-Aided Design (CAD) toolchain, that is used to optimally map and fit the design applications or workloads onto the underlying target FPGA device. These design applications mapped onto the FPGA demand high maximum achievable clock frequency (Fmax) and low power consumption while maintaining a low compilation time, which is a major hindrance in widespread adoption of FPGAs. The focus of this Ph.D. dissertation is the placement problem for FPGAs, which takes a major portion of the FPGA CAD tool runtime. A new algorithm for spreading cells during FPGA global placement is proposed, which achieves better wirelength and routing congestion and takes less runtime than the algorithm used in the state-of-the-art academic FPGA placer. We also propose FPGA acceleration of various subsystems of an analytic global placement algorithm, including wirelength gradient computation and spreading, which achieves significant speedup over the multi-threaded CPU version. A new detailed placement algorithm is proposed, which offers better tradeoff between quality and runtime compared to existing methods. This algorithm is also accelerated on a GPU and an FPGA, achieving significant speedup over multi-threaded CPU implementation. Another detailed placement algorithm is also proposed which physically re-aligns timing critical paths and improves Fmax with minimal runtime overhead. Both of these algorithms for detailed placement have shown good results on industrial benchmarks and have been integrated into an industrial FPGA CAD tool flowElectrical and Computer Engineerin

3D Global Router: a Study to Optimize Congestion, Wirelength and Via for Circuit Layout

The increasing size of integrated circuits and aggressive shrinking process feature size for IC manufacturing process poses signicant challenges on traditional physical design problems. Various design rules signicantly complicate the physical design problems and large problem size abides nothing but extremely e cient techniques. Leading physical design tools have to be powerful enough to handle complex design demands and be nimble enough to waste no runtime. This thesis studies the challenges faced by global routing problem, one of the traditional physical design problems that needs to be pushed to its new limit. This work proposes three e ective tools to tackle congestion, wire and via optimization in global routing process, from three di erent aspects. The number of vias generated during the global routing stage is a critical factor for the yield of integrated circuits. However, most global routers only approach the problem by charging a cost for vias in the maze routing cost function. The first work of this thesis, FastRoute 4.0 presents a global router that addresses the via number optimization problem throughout the entire global routing ow. It introduces the via aware Steiner tree generation, 3-bend routing and layer assignment with careful ordering to reduce via count. The integration of these three techniques with existing academic global routers achieves signicant reduction in via count without any sacrice in runtime. Despite of the recent development for popular rip-up and reroute framework, the congestion elimination process remains arbitrary and requires signicant tuning. Global routing has congestion elimination as the first and foremost priority and congestion issue becomes increasingly severe due to timing requirements, design for manufacturability. The second work of this thesis, an auction algorithm based pre-processing framework (APF) for global routing focuses on how to eliminate congestion e ectively. In order to achieve more consistent congestion elimination, the framework uses auction based detour techniques to alleviate the impacts of greedy sequential manner of maze routing, which remains as a major drawback in the most popular global routing framework. In the framework, APF first identies the most congested global routing locations by an interval over ow lower bound technique. Then APF uses auction based detour algorithm to compute which nets to detour and where to detour. The framework can be applied to any global routers and would help them to achieve signicant improvement in both solution quality and runtime. The third work in this thesis combines the advantage of the two framework used to minimize via usage in global routing: 3D routers with good solution quality and e cient 2D routers with layer assignment process. It results in a new multi-level 3D global router called MGR (multi-level global router) that combines the advantage of both kinds. MGR resorts to an e cient multi-level framework to reroute nets in the congested region on the 3D grid graph. Routing on the coarsened grid graph speeds up the global router while 3D routing introduces less vias. The powerful multi-level rerouting framework wraps three innovative routing techniques together: an adaptive resource reservation technique in coarsening process, a new 3-terminal maze routing algorithm and a network flow based solution propagation method in uncoarsening process. As a result, MGR can achieve the solution quality close to 3D routers with comparable runtime of 2D routers