DSN advanced receiver: Breadboard description and test results

A breadboard Advanced Receiver for use in the Deep Space Network was designed, built, and tested in the laboratory. Field testing was also performed during Voyager Uranus encounter at DSS-13. The development of the breadboard is intended to lead towards implementation of the new receiver throughout the network. The receiver is described on a functional level and then in terms of more specific hardware and software architecture. The results of performance tests in the laboratory and in the field are given. Finally, there is a discussion of suggested improvements for the next phase of development

Design of variability compensation architectures of digital circuits with adaptive body bias

The most critical concern in circuit is to achieve high level of performance with very tight power constraint. As the high performance circuits moved beyond 45nm technology one of the major issues is the parameter variation i.e. deviation in process, temperature and voltage (PVT) values from nominal specifications. A key process parameter subject to variation is the transistor threshold voltage (Vth) which impacts two important parameters: frequency and leakage power. Although the degradation can be compensated by the worstcase scenario based over-design approach, it induces remarkable power and performance overhead which is undesirable in tightly constrained designs. Dynamic voltage scaling (DVS) is a more power efficient approach, however its coarse granularity implies difficulty in handling fine grained variations. These factors have contributed to the growing interest in power aware robust circuit design. We propose a variability compensation architecture with adaptive body bias, for low power applications using 28nm FDSOI technology. The basic approach is based on a dynamic prediction and prevention of possible circuit timing errors. In our proposal we are using a Canary logic technique that enables the typical-case design. The body bias generation is based on a DLL type method which uses an external reference generator and voltage controlled delay line (VCDL) to generate the forward body bias (FBB) control signals. The adaptive technique is used for dynamic detection and correction of path failures in digital designs due to PVT variations. Instead of tuning the supply voltage, the key idea of the design approach is to tune the body bias voltage bymonitoring the error rate during operation. The FBB increases operating speed with an overhead in leakage power

Dynamic Energy Management for Chip Multi-processors under Performance Constraints

We introduce a novel algorithm for dynamic energy management (DEM) under performance constraints in chip multi-processors (CMPs). Using the novel concept of delayed instructions count, performance loss estimations are calculated at the end of each control period for each core. In addition, a Kalman filtering based approach is employed to predict workload in the next control period for which voltage-frequency pairs must be selected. This selection is done with a novel dynamic voltage and frequency scaling (DVFS) algorithm whose objective is to reduce energy consumption but without degrading performance beyond the user set threshold. Using our customized Sniper based CMP system simulation framework, we demonstrate the effectiveness of the proposed algorithm for a variety of benchmarks for 16 core and 64 core network-on-chip based CMP architectures. Simulation results show consistent energy savings across the board. We present our work as an investigation of the tradeoff between the achievable energy reduction via DVFS when predictions are done using the effective Kalman filter for different performance penalty thresholds

Online Timing Slack Measurement and its Application in Field-Programmable Gate Arrays

Reliability, power consumption and timing performance are key concerns for today's integrated circuits. Measurement techniques capable of quantifying the timing characteristics of a circuit, while it is operating, facilitate a range of benefits. Delay variation due to environmental and operational conditions, and degradation can be monitored by tracking changes in timing performance. Using the measurements in a closed-loop to control power supply voltage or clock frequency allows for the reduction of timing safety margins, leading to improvements in power consumption or throughput performance through the exploitation of better-than worst-case operation. This thesis describes a novel online timing slack measurement method which can directly measure the timing performance of a circuit, accurately and with minimal overhead. Enhancements allow for the improvement of absolute accuracy and resolution. A compilation flow is reported that can automatically instrument arbitrary circuits on FPGAs with the measurement circuitry. On its own this measurement method is able to track the "health" of an integrated circuit, from commissioning through its lifetime, warning of impending failure or instigating pre-emptive degradation mitigation techniques. The use of the measurement method in a closed-loop dynamic voltage and frequency scaling scheme has been demonstrated, achieving significant improvements in power consumption and throughput performance.Open Acces

the influence of auditory feedback and deep brain stimulation

Unintentional timing deviations during musical performance can be conceived of as timing errors. However, recent research on humanizing computer-generated music has demonstrated that timing fluctuations that exhibit long-range temporal correlations (LRTC) are preferred by human listeners. This preference can be accounted for by the ubiquitous presence of LRTC in human tapping and rhythmic performances. Interestingly, the manifestation of LRTC in tapping behavior seems to be driven in a subject-specific manner by the LRTC properties of resting-state background cortical oscillatory activity. In this framework, the current study aimed to investigate whether propagation of timing deviations during the skilled, memorized piano performance (without metronome) of 17 professional pianists exhibits LRTC and whether the structure of the correlations is influenced by the presence or absence of auditory feedback. As an additional goal, we set out to investigate the influence of altering the dynamics along the cortico-basal-ganglia-thalamo-cortical network via deep brain stimulation (DBS) on the LRTC properties of musical performance. Specifically, we investigated temporal deviations during the skilled piano performance of a non-professional pianist who was treated with subthalamic-deep brain stimulation (STN-DBS) due to severe Parkinson's disease, with predominant tremor affecting his right upper extremity. In the tremor-affected right hand, the timing fluctuations of the performance exhibited random correlations with DBS OFF. By contrast, DBS restored long- range dependency in the temporal fluctuations, corresponding with the general motor improvement on DBS. Overall, the present investigations demonstrate the presence of LRTC in skilled piano performances, indicating that unintentional temporal deviations are correlated over a wide range of time scales. This phenomenon is stable after removal of the auditory feedback, but is altered by STN-DBS, which suggests that cortico-basal ganglia-thalamocortical circuits play a role in the modulation of the serial correlations of timing fluctuations exhibited in skilled musical performance

Circuits and Systems Advances in Near Threshold Computing

Modern society is witnessing a sea change in ubiquitous computing, in which people have embraced computing systems as an indispensable part of day-to-day existence. Computation, storage, and communication abilities of smartphones, for example, have undergone monumental changes over the past decade. However, global emphasis on creating and sustaining green environments is leading to a rapid and ongoing proliferation of edge computing systems and applications. As a broad spectrum of healthcare, home, and transport applications shift to the edge of the network, near-threshold computing (NTC) is emerging as one of the promising low-power computing platforms. An NTC device sets its supply voltage close to its threshold voltage, dramatically reducing the energy consumption. Despite showing substantial promise in terms of energy efficiency, NTC is yet to see widescale commercial adoption. This is because circuits and systems operating with NTC suffer from several problems, including increased sensitivity to process variation, reliability problems, performance degradation, and security vulnerabilities, to name a few. To realize its potential, we need designs, techniques, and solutions to overcome these challenges associated with NTC circuits and systems. The readers of this book will be able to familiarize themselves with recent advances in electronics systems, focusing on near-threshold computing