No Arabic abstract
In the last decade, the growing influence of open source software has necessitated the need to reduce the abstraction levels in hardware design. Open source hardware significantly reduces the development time, increasing the probability of first-pass success and enable developers to optimize software solutions based on hardware features, thereby reducing the design costs. The recent introduction of open source Process Development Kit (OpenPDK) by Skywater technologies in June 2020 has eliminated the barriers to Application-Specific Integrated Circuit (ASIC) design, which is otherwise considered expensive and not easily accessible. The OpenPDK is the first concrete step towards achieving the goal of open source circuit blocks that can be imported to reuse and modify in ASIC design. With process technologies scaling down for better performance, the need for entirely digital designs, which can be synthesized in any standard Automatic Place-and-Route (APR) tool, has increased considerably, for mapping physical design to the new process technology. This work presents the first open source all-digital Serializer/Deserializer (SerDes) for multi-GHz serial links designed using Skywater OpenPDK 130nm process node. To ensure that the design is fully synthesizable, the SerDes uses CMOS inverter-based drivers at the Tx, while the Rx front end comprises a resistive feedback inverter as a sensing element, followed by sampling elements. A fully digital oversampling CDR at the Rx recovers the Tx clock for proper decoding of data bits. The physical design flow utilizes OpenLANE, which is an end-to-end tool for generating GDS from RTL. Virtuoso has been used for extracting parasitics for post-layout simulations, which exhibit the SerDes functionality at 2 Gbps for 34 dB channel loss while consuming 438 mW power. The GDS and netlist files of the SerDes are uploaded in a GitHub repository for public access.
Networked dynamic systems are often abstracted as directed graphs, where the observed system processes form the vertex set and directed edges are used to represent non-zero transfer functions. Recovering the exact underlying graph structure of such a networked dynamic system, given only observational data, is a challenging task. Under relatively mild well-posedness assumptions on the network dynamics, there are state-of-the-art methods which can guarantee the absence of false positives. However, in this article we prove that under the same well-posedness assumptions, there are instances of networks for which any method is susceptible to inferring false negative edges or false positive edges. Borrowing a terminology from the theory of graphical models, we say those systems are unfaithful to their networks. We formalize a variant of faithfulness for dynamic systems, called Granger-faithfulness, and for a large class of dynamic networks, we show that Granger-unfaithful systems constitute a Lebesgue zero-measure set. For the same class of networks, under the Granger-faithfulness assumption, we provide an algorithm that reconstructs the network topology with guarantees for no false positive and no false negative edges in its output. We augment the topology reconstruction algorithm with orientation rules for some of the inferred edges, and we prove the rules are consistent under the Granger-faithfulness assumption.
Circadian and other physiological rhythms play a key role in both normal homeostasis and disease processes. Such is the case of circadian and infradian seizure patterns observed in epilepsy. In this paper we explore a new implantable stimulator that implements chronotherapy as a feedforward input to supplement both open-loop and closed-loop methods. This integrated algorithm allows for stimulation to be adjusted to the ultradian, circadian and infradian patterns observed in patients through slowly-varying temporal adjustments of stimulation and algorithm sub-components, while also enabling adaption of stimulation based on immediate physiological needs such as a breakthrough seizure or change of posture. Embedded physiological sensors in the stimulator can be used to refine the baseline stimulation circadian pattern as a digital zeitgeber. This approach is tested on a canine with severe drug-resistant idiopathic generalized epilepsy exhibiting a diurnal pattern correlated with sleep-wake cycles. Prior to implantation, the canines cluster seizures evolved to status epilepticus (SE) and required emergency pharmacological intervention. The cranially-mounted system was fully-implanted bilaterally into the centromedian nucleus of the thalamus. Using time-based modulation, thalamocortical rhythm-specific tuning of frequency parameters as well as fast-adaptive modes based on activity, the canine experienced no further SE events post-implant as of the time of writing (seven months). Importantly, no significant cluster seizures have been observed either, allowing the reduction of rescue medication. The use of chronotherapy as a feedforward signal to augment adaptive neurostimulators could prove a useful method in conditions where sensitivity to temporal patterns are characteristics of the disease state, providing a novel mechanism for tailoring a more patient-specific therapy approach.
This paper proposes an innovative approach for the advanced control of an industrial process via an automation cloud platform. Increased digital transformation and advances in Industrial Internet of Things (IIoT) technologies make it possible for multiple vendors to compete to control an industrial process. An industrial automation cloud platform facilitates the interaction between advanced process control (APC) vendors and the process. A selector, which forms part of the platform, is used to determine the best controller for a process for any given time period. The article starts with a general overview of platform businesses, platforms aimed at industry, and the steps required to build such platforms. Issues that need to be addressed to make APC via an automation platform practically viable are discussed including what process information to provide to APC vendors, continuous evaluation of controllers even when not in control of the process, bumpless transfer, closed-loop stability, constraint handling, and platform security and trust. A case study is given of competing APCs via an industrial automation cloud platform. The process used in the study is a surge tank from a bulk tailings treatment plant, the aim of which is to keep the density of the tank out flow constant while maintaining a steady tank level. A platform facilitates the competition of three vendors for control of this process. It is shown that the cloud platform approach can provide the plant access to a superior controller without the need for directly procuring the services of an exclusive vendor.
Approximately 18 percent of the 3.2 million smartphone applications rely on integrated graphics processing units (GPUs) to achieve competitive performance. Graphics performance, typically measured in frames per second, is a strong function of the GPU frequency, which in turn has a significant impact on mobile processor power consumption. Consequently, dynamic power management algorithms have to assess the performance sensitivity to the frequency accurately to choose the operating frequency of the GPU effectively. Since the impact of GPU frequency on performance varies rapidly over time, there is a need for online performance models that can adapt to varying workloads. This paper presents a light-weight adaptive runtime performance model that predicts the frame processing time of graphics workloads at runtime without apriori characterization. We employ this model to estimate the frame time sensitivity to the GPU frequency, i.e., the partial derivative of the frame time with respect to the GPU frequency. The proposed model does not rely on any parameter learned offline. Our experiments on commercial platforms with common GPU benchmarks show that the mean absolute percentage error in frame time and frame time sensitivity prediction are 4.2 and 6.7 percent, respectively.
We describe a general purpose digital servo optimized for feedback control of lasers in atomic, molecular, and optical (AMO) physics experiments. The servo is capable of feedback bandwidths up to roughly 1~MHz (limited by the 320~ns total latency); loop filter shapes up to fifth order; multiple-input, multiple-output control; and automatic lock acquisition. The configuration of the servo is controlled via a graphical user interface, which also provides a rudimentary software oscilloscope and tools for measurement of system transfer functions. We illustrate the functionality of the digital servo by describing its use in two example scenarios: frequency control of the laser used to probe the narrow clock transition of $^{27}$Al$^+$ in an optical atomic clock, and length control of a cavity used for resonant frequency doubling of a laser.