Core Interface Optimization for Multi-core Neuromorphic Processors

Hardware implementations of Spiking Neural Networks (SNNs) represent a promising approach to edge-computing for applications that require low-power and low-latency, and which cannot resort to external cloud-based computing services. However, most solutions proposed so far either support only relatively small networks, or take up significant hardware resources, to implement large networks. To realize large-scale and scalable SNNs it is necessary to develop an efficient asynchronous communication and routing fabric that enables the design of multi-core architectures. In particular the core interface that manages inter-core spike communication is a crucial component as it represents the bottleneck of Power-Performance-Area (PPA) especially for the arbitration architecture and the routing memory. In this paper we present an arbitration mechanism with the corresponding asynchronous encoding pipeline circuits, based on hierarchical arbiter trees. The proposed scheme reduces the latency by more than 70% in sparse-event mode, compared to the state-of-the-art arbitration architectures, with lower area cost. The routing memory makes use of asynchronous Content Addressable Memory (CAM) with Current Sensing Completion Detection (CSCD), which saves approximately 46% energy, and achieves a 40% increase in throughput against conventional asynchronous CAM using configurable delay lines, at the cost of only a slight increase in area. In addition as it radically reduces the core interface resources in multi-core neuromorphic processors, the arbitration architecture and CAM architecture we propose can be also applied to a wide range of general asynchronous circuits and systems

Dynamic effects in the scattering of electrons by small clusters of atoms

Dynamic scattering corrections were calculated for 40 kV electrons diffracted by randomly oriented fcc clusters of argon and of gold atoms ranging in size from 13 to 135 atoms. Computations were carried out according to several variants of two limiting theoretical approaches, namely, the direct summing up of atomic contributions calculated through single–single and single–double scattered waves by modifications of Glauber theory, and the extrapolation to limitingly small crystallites of conventional dynamic theory in the Blackman and Fujimoto formulations. For the small clusters studied, integrated intensities of diffraction rings (through single–double scatterings) calculated for three dimensional crystallites differ insignificantly from Glauber theory intensities calculated by projecting atomic potential energies onto a plane perpendicular to the mean direction of the incident and scattered wave vectors. The fractional dynamic correction increases with cluster size very nearly as N2/3 in both the Glauber and Blackman–Fujimoto limiting treatments. For crystalline clusters 8–20 Å in diameter, the dynamic effect calculated by summing single–double scatterings is an order of magnitude larger than that according to Blackman–Fujimoto theory. For argon clusters the dynamic effect is not serious; but according to our direct sums, dynamic corrections for 16 Å spheres of gold are surprisingly large, exceeding 25% for 111 reflections. Since the direct sums have been verified experimentally for several vapor‐phase molecules, the present work indicates that, in the limit of very small scatterers, extrapolations from conventional two‐beam dynamic theory may seriously underestimate the magnitude of dynamic effects.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71250/2/JCPSA6-66-12-5387-1.pd

Core interface optimization for multi-core neuromorphic processors

Hardware implementations of Spiking Neural Networks (SNNs) represent a promising approach to edge-computing for applications that require low-power and low-latency, and which cannot resort to external cloud-based computing services. However, most solutions proposed so far either support only relatively small networks, or take up significant hardware resources, to implement large networks. To realize large-scale and scalable SNNs it is necessary to develop an efficient asynchronous communication and routing fabric that enables the design of multi-core architectures. In particular the core interface that manages inter-core spike communication is a crucial component as it represents the bottleneck of Power-Performance-Area (PPA) especially for the arbitration architecture and the routing memory. In this paper we present an arbitration mechanism with the corresponding asynchronous encoding pipeline circuits, based on hierarchical arbiter trees. The proposed scheme reduces the latency by more than 70% in sparse-event mode, compared to the state-of-the-art arbitration architectures, with lower area cost. The routing memory makes use of asynchronous Content Addressable Memory (CAM) with Current Sensing Completion Detection (CSCD), which saves approximately 46% energy, and achieves a 40% increase in throughput against conventional asynchronous CAM using configurable delay lines, at the cost of only a slight increase in area. In addition as it radically reduces the core interface resources in multi-core neuromorphic processors, the arbitration architecture and CAM architecture we propose can be also applied to a wide range of general asynchronous circuits and systems

Training in communication skills for PhD students : report of innovation

Un stage de formation à la communication est proposé depuis plusieurs années aux moniteurs scientifiques du Centre d'Initiation à l'Enseignement Supérieur (CIES) de l'académie de Versailles. Divers types de communication scientifique sont abordés par le biais de conférences-débats, mais la majeure partie du stage est consacrée à l'élaboration, par chaque moniteur, d'une affiche présentant son sujet de thèse. Ces affiches, qui doivent être compréhensibles par les moniteurs de toutes les disciplines, sont finalement commentées oralement suivant la pratique des congrès (poster sessions)

Microarray detection of novel nuclear RNA substrates for the exosome

Microarray analyses were performed on yeast strains mutant for the nuclear-specific exosome components Rrp6p and Rrp47p/Lrp1p or the core component Rrp41p/Ski6p, at permissive temperature and following transfer to 37 degrees C. 339 mRNAs showed clearly altered expression levels, with an unexpectedly high degree of heterogeneity in the different exosome mutants. In contrast, no clear alterations were seen in strains lacking the cytoplasmic exosome component Ski7p. 27 mRNAs that were overexpressed in each strain defective in the nuclear exosome are good candidates for regulation by nuclear turnover. These included the mRNA for the autoregulated RNA-binding protein Nrd1p. Northern and primer extension analyses confirmed the elevated NRD1 mRNA levels in exosome mutants, and revealed the accumulation of truncated 5' fragments of the mRNA. These contain a predicted Nrd1p-binding site, potentially sequestering the protein and disrupting its autoregulation. Several genes located immediately downstream of independently transcribed snoRNA genes were overexpressed in exosome mutants, presumably due to stabilization of the products of transcription termination read-through. Further analyses indicated that many snoRNA and snRNA genes are inefficiently terminated, but read-through transcripts into downstream ORFs are normally rapidly degraded by the exosome. Copyright (c) 2006 John Wiley & Sons, Ltd

DenRAM: Neuromorphic Dendritic Architecture with RRAM for Efficient Temporal Processing with Delays

An increasing number of neuroscience studies are highlighting the importance of spatial dendritic branching in pyramidal neurons in the brain for supporting non-linear computation through localized synaptic integration. In particular, dendritic branches play a key role in temporal signal processing and feature detection, using coincidence detection (CD) mechanisms, made possible by the presence of synaptic delays that align temporally disparate inputs for effective integration. Computational studies on spiking neural networks further highlight the significance of delays for CD operations, enabling spatio-temporal pattern recognition within feed-forward neural networks without the need for recurrent architectures. In this work, we present DenRAM, the first realization of a spiking neural network with analog dendritic circuits, integrated into a 130nm technology node coupled with resistive memory (RRAM) technology. DenRAM's dendritic circuits use the RRAM devices to implement both delays and synaptic weights in the network. By configuring the RRAM devices to reproduce bio-realistic timescales, and through exploiting their heterogeneity, we experimentally demonstrate DenRAM's capability to replicate synaptic delay profiles, and efficiently implement CD for spatio-temporal pattern recognition. To validate the architecture, we conduct comprehensive system-level simulations on two representative temporal benchmarks, highlighting DenRAM's resilience to analog hardware noise, and its superior accuracy compared to recurrent architectures with an equivalent number of parameters. DenRAM not only brings rich temporal processing capabilities to neuromorphic architectures, but also reduces the memory footprint of edge devices, provides high accuracy on temporal benchmarks, and represents a significant step-forward in low-power real-time signal processing technologies

Entropic effects on the structure of Lennard-Jones clusters

We examine in detail the causes of the structural transitions that occur for those small Lennard-Jones clusters that have a non-icosahedral global minima. Based on the principles learned from these examples we develop a method to construct structural phase diagrams that show in a coarse-grained manner how the equilibrium structure of large clusters depends on both size and temperature. The method can be augmented to account for anharmonicity and quantum effects. Our results illustrate that the vibrational entropy can play a crucial role in determining the equilibrium structure of a cluster.Comment: 13 pages, 9 figure

Entropic effects on the Size Evolution of Cluster Structure

We show that the vibrational entropy can play a crucial role in determining the equilibrium structure of clusters by constructing structural phase diagrams showing how the structure depends upon both size and temperature. These phase diagrams are obtained for example rare gas and metal clusters.Comment: 5 pages, 3 figure

A role for SSU72 in balancing RNA polymerase II transcription elongation and termination

Interactions of pre-mRNA 3&prime;end factors and the CTD of RNA polymerase II (RNAP II) are required for transcription termination and 3&prime;end processing. Here, we demonstrate that Ssu72p is stably associated with yeast cleavage and polyadenylation factor CPF and provide evidence that it bridges the CPF subunits Pta1p and Ydh1p/Cft2p, the general transcription factor TFIIB, and RNAP II via Rpb2p. Analyses of ssu72-2 mutant cells in the absence and presence of the nuclear exosome component Rrp6p revealed defects in RNAP II transcription elongation and termination. 6-azauracil, that reduces transcription elongation rates, suppressed the ssu72-2 growth defect at 33&deg;C. The sum of our analyses suggests a negative influence of Ssu72p on RNAP II during transcription that affects the commitment to either elongation or termination.<br /

The mRNA encoding the yeast ARE-binding protein Cth2 is generated by a novel 3′ processing pathway

Microarray analyses of mRNAs over-expressed in strains lacking the nuclear exosome component Rrp6 identified the transcript encoding the ARE-binding protein Cth2, which functions in cytoplasmic mRNA stability. Subsequent northern analyses revealed that exosome mutants accumulate a 3′-extended transcript at the expense of the mature CTH2 mRNA. The 3′ ends of the CTH2 mRNA were mapped to a [GU3–5]5 repeat, unlike any previously characterized polyadenylation site. CTH2 mRNA accumulation was not inhibited by mutations in 3′-cleavage and polyadenylation factors, Rna14, Rna15 and Pap1, which block accumulation of other mRNAs. The 3′-extended CTH2 pre-mRNA strongly accumulated in strains with mutations in the TRAMP4 polyadenylation complex or the Nrd1/Nab3/Sen1 complex, and contains multiple Nrd1 and Nab3 binding sites. CTH2 carries a consensus ARE element and levels of the pre-mRNA and mRNA were elevated by mutation of the ARE or inactivation of the nuclear 5′-exonuclease Rat1. We propose that CTH2 mRNA is processed from a 3′-extended primary transcript by the exosome, TRAMP and Nrd1/Nab3/Sen1 complexes. This unusual pathway may allow time for nuclear, ARE-mediated regulation of CTH2 levels involving Rat1