Memory Organization for Energy-Efficient Learning and Inference in Digital Neuromorphic Accelerators

The energy efficiency of neuromorphic hardware is greatly affected by the energy of storing, accessing, and updating synaptic parameters. Various methods of memory organisation targeting energy-efficient digital accelerators have been investigated in the past, however, they do not completely encapsulate the energy costs at a system level. To address this shortcoming and to account for various overheads, we synthesize the controller and memory for different encoding schemes and extract the energy costs from these synthesized blocks. Additionally, we introduce functional encoding for structured connectivity such as the connectivity in convolutional layers. Functional encoding offers a 58% reduction in the energy to implement a backward pass and weight update in such layers compared to existing index-based solutions. We show that for a 2 layer spiking neural network trained to retain a spatio-temporal pattern, bitmap (PB-BMP) based organization can encode the sparser networks more efficiently. This form of encoding delivers a 1.37x improvement in energy efficiency coming at the cost of a 4% degradation in network retention accuracy as measured by the van Rossum distance.Comment: submitted to ISCAS202

The challenging optics of XtremeD – a neutron diffractometer for high pressures and magnetic fields at ILL developed by Spain

6 páginas, 3 figuras.The Spanish community of neutron scatterers and the ILL are considering the construction of a CRG "extreme conditions Diffractometer (XtremeD)" for both single crystals and powders, operating at high pressures (up to 50 GPa) and high magnetic fields (up to 15 Tesla). High pressure studies require reduced sample volumes. This makes the focusing optics a crucial part of the instrument, in order to have increased flux and to avoid the scattering from the sample environment. The different solutions at different levels of the instrument, which are being studied, will be discussed in this paper.Peer reviewe

Совершенствование кадровой политики предприятия

Объектом исследования является ПАО Сбербанк России. Цель работы– анализ существующей кадровой политики предприятия и выработка рекомендаций по ее усовершенствованию. В процессе исследования проводились исследования кадрового состава, эффективности использования кадров предприятия, адекватности кадровой политики целям и задачам предприятия. В результате исследования выделены проблемы кадровой политики ПАО Сбербанк России, предложены рекомендации по ее совершенствованию, оценена экономическая эффективность потенциальных изменений.The object of this study is to PAO Sberbank of Russia. The purpose work- analysis of the existing personnel policy of the company and make recommendations for its improvement. The study conducted research personnel, effective use of the human resources, the adequacy of personnel policy goals and objectives of the enterprise. The study highlighted the problem of personnel policy PAT Sberbank of Russia, offered recommendations for its improvement, estimated cost-effectiveness of potential changes

Negotiating the modern cross-class ‘model home’:domestic experiences in Basil Spence’s Claremont Court

This article investigates the spatial articulation of architecture and home through the exploration of current domestic experiences in Basil Spence’s Claremont Court housing scheme (1959-1962), Edinburgh. How architecture and home are both idealized and lived is the backdrop for a discussion that draws on the concept of “model home,” or physical representation of a domestic ideal. The article reads Claremont Court as an architectural prototype of the modern domestic ideal, before exploring its reception by five of its households through the use of visual methods and semistructured interviews. Receiving the model home involves negotiating between ideal and lived homes. Building on this idea, the article contributes with a focus on the spatiality of such reception, showing how it is modulated according to the architectural affordances that the “model home” represents. The article expands on scholarship on architecture and home with empirical evidence that argues the reciprocal spatiality of home

Memory Organization for Energy-Efficient Learning and Inference in Digital Neuromorphic Accelerators

The energy efficiency of neuromorphic hardware is greatly affected by the energy of storing, accessing, and updating synaptic parameters. Various methods of memory organisation targeting energy-efficient digital accelerators have been investigated in the past, however, they do not completely encapsulate the energy costs at a system level. To address this shortcoming and to account for various overheads, we synthesize the controller and memory for different encoding schemes and extract the energy costs from these synthesized blocks. Additionally, we introduce functional encoding for structured connectivity such as the connectivity in convolutional layers. Functional encoding offers a 58% reduction in the energy to implement a backward pass and weight update in such layers compared to existing index-based solutions. We show that for a 2 layer spiking neural network trained to retain a spatio-temporal pattern, bitmap (PB-BMP) based organization can encode the sparser networks more efficiently. This form of encoding delivers a 1.37x improvement in energy efficiency coming at the cost of a 4% degradation in network retention accuracy as measured by the van Rossum distance

Integration Issues of Graphoepitaxial High-Tc SQUIDs Into Multichannel MEG Systems

We have analyzed the possibility to construct multichannel magnetoencephalography (MEG) systems based on high-Tc direct current superconducting quantum interference devices (DC SQUIDs) with graphoepitaxial step edge Josephson junctions. A new layout of multilayer high-Tc superconducting flux transformers was tested and a new type of high-Tc DC SQUID magnetometer intended for MEG systems was realized. These magnetometers have a vacuum-tight capsule of outer diameter 24 mm and a magnetic field resolution of ∼4 fT/√Hz at 77 K. Crosstalk between adjacent sensors was estimated and measured for in-plane and axial configurations. The vibration-free cooling of sensors, minimization of the sensor-to-object distance and optimization of the sensor positions as well as the gantry design are discussed. Our findings may have implications for the next generation of non-invasive imaging techniques that will be used to understand human brain function