A Study of Deep Learning Robustness Against Computation Failures

For many types of integrated circuits, accepting larger failure rates in computations can be used to improve energy efficiency. We study the performance of faulty implementations of certain deep neural networks based on pessimistic and optimistic models of the effect of hardware faults. After identifying the impact of hyperparameters such as the number of layers on robustness, we study the ability of the network to compensate for computational failures through an increase of the network size. We show that some networks can achieve equivalent performance under faulty implementations, and quantify the required increase in computational complexity

Voltage noise analysis with ring oscillator clocks

Voltage noise is the main source of dynamic variability in integrated circuits and a major concern for the design of Power Delivery Networks (PDNs). Ring Oscillators Clocks (ROCs) have been proposed as an alternative to mitigate the negative effects of voltage noise as technology scales down and power density increases. However, their effectiveness highly depends on the design parameters of the PDN, power consumption patterns of the system and spatial locality of the ROCs within the clock domains. This paper analyzes the impact of the PDN parameters and ROC location on the robustness to voltage noise. The capability of reacting instantaneously to unpredictable voltage droops makes ROCs an attractive solution, which allows to reduce the amount of decoupling capacitance without downgrading performance. Tolerance to voltage noise and related benefits can be increased by using multiple ROCs and reducing the size of the clock domains. The analysis shows that up to 83% of the margins for voltage noise and up to 27% of the leakage power can be reduced by using local ROCs.Peer ReviewedPostprint (author's final draft

A RISC-V Vector Processor With Simultaneous-Switching Switched-Capacitor DC-DC Converters in 28 nm FDSOI

This work demonstrates a RISC-V vector microprocessor implemented in 28 nm FDSOI with fully integrated simultaneous-switching switched-capacitor DC-DC (SC DC-DC) converters and adaptive clocking that generates four on-chip voltages between 0.45 and 1 V using only 1.0 V core and 1.8 V IO voltage inputs. The converters achieve high efficiency at the system level by switching simultaneously to avoid charge-sharing losses and by using an adaptive clock to maximize performance for the resulting voltage ripple. Details about the implementation of the DC-DC switches, DC-DC controller, and adaptive clock are provided, and the sources of conversion loss are analyzed based on measured results. This system pushes the capabilities of dynamic voltage scaling by enabling fast transitions (20 ns), simple packaging (no off-chip passives), low area overhead (16%), high conversion efficiency (80%-86%), and high energy efficiency (26.2 DP GFLOPS/W) for mobile devices

Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition

A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus eliminated most of the density advantages gained by the adoption of memristor synapses. Further, they used different waveforms for pre and post-synaptic spikes that added undesirable circuit overhead. Here we describe a hardware architecture that can feature a large number of memristor synapses to learn real-world patterns. We present a versatile CMOS neuron that combines integrate-and-fire behavior, drives passive memristors and implements competitive learning in a compact circuit module, and enables in-situ plasticity in the memristor synapses. We demonstrate handwritten-digits recognition using the proposed architecture using transistor-level circuit simulations. As the described neuromorphic architecture is homogeneous, it realizes a fundamental building block for large-scale energy-efficient brain-inspired silicon chips that could lead to next-generation cognitive computing.Comment: This is a preprint of an article accepted for publication in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol 5, no. 2, June 201

Ring oscillator clocks and margins

How much margin do we have to add to the delay lines of a bundled-data circuit? This paper is an attempt to give a methodical answer to this question, taking into account all sources of variability and the existing EDA machinery for timing analysis and sign-off. The paper is based on the study of the margins of a ring oscillator that substitutes a PLL as clock generator. A timing model is proposed that shows that a 12% margin for delay lines can be sufficient to cover variability in a 65nm technology. In a typical scenario, performance and energy improvements between 15% and 35% can be obtained by using a ring oscillator instead of a PLL. The paper concludes that a synchronous circuit with a ring oscillator clock shows similar benefits in performance and energy as those of bundled-data asynchronous circuits.Peer ReviewedPostprint (author's final draft

A review of advances in pixel detectors for experiments with high rate and radiation

The Large Hadron Collider (LHC) experiments ATLAS and CMS have established hybrid pixel detectors as the instrument of choice for particle tracking and vertexing in high rate and radiation environments, as they operate close to the LHC interaction points. With the High Luminosity-LHC upgrade now in sight, for which the tracking detectors will be completely replaced, new generations of pixel detectors are being devised. They have to address enormous challenges in terms of data throughput and radiation levels, ionizing and non-ionizing, that harm the sensing and readout parts of pixel detectors alike. Advances in microelectronics and microprocessing technologies now enable large scale detector designs with unprecedented performance in measurement precision (space and time), radiation hard sensors and readout chips, hybridization techniques, lightweight supports, and fully monolithic approaches to meet these challenges. This paper reviews the world-wide effort on these developments.Comment: 84 pages with 46 figures. Review article.For submission to Rep. Prog. Phy

Modeling and Energy Optimization of LDPC Decoder Circuits with Timing Violations

This paper proposes a "quasi-synchronous" design approach for signal processing circuits, in which timing violations are permitted, but without the need for a hardware compensation mechanism. The case of a low-density parity-check (LDPC) decoder is studied, and a method for accurately modeling the effect of timing violations at a high level of abstraction is presented. The error-correction performance of code ensembles is then evaluated using density evolution while taking into account the effect of timing faults. Following this, several quasi-synchronous LDPC decoder circuits based on the offset min-sum algorithm are optimized, providing a 23%-40% reduction in energy consumption or energy-delay product, while achieving the same performance and occupying the same area as conventional synchronous circuits.Comment: To appear in IEEE Transactions on Communication

Limits on Fundamental Limits to Computation

An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl