2022 roadmap on neuromorphic computing and engineering

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Animals exhibit remarkable locomotion skills despite significant sensorimotor delays and operating in uncertain environments. Moreover, mammals acquire these skills within minutes of birth. From the Cambrian explosion to the present day, vertebrate motor c ...

Calibration between robots and cameras is critical in automated robot vision systems. However, conventional manually conducted image-based calibration techniques are often limited by their accuracy sensitivity and poor adaptability to dynamic or unstructur ...

Machine learning models (e.g., neural networks) achieve high accuracy in wind power forecasting, but they are usually regarded as black boxes that lack interpretability. To address this issue, the paper proposes a glass-box model that combines high accurac ...

Machine learning and artificial intelligence methods have achieved remarkable success, matching and even surpassing human capabilities in various complex tasks. However, many demonstrations have generally neglected a critical part of the intelligence that ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Memory devices have returned to the spotlight due to increasing interest in using in-memory computing architectures to make data-driven algorithms more energy-efficient. One of the main advantages of this architecture is the efficient performance of vector ...

As big strides were being made in many science fields in the 1970s and 80s, faster computation for solving problems in molecular biology, semiconductor technology, aeronautics, particle physics, etc., was at the forefront of research. Parallel and super-co ...

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

Most modern in-memory online transaction processing (OLTP) engines rely on multi-version concurrency control (MVCC) to provide data consistency guarantees in the presence of conflicting data accesses. MVCC improves concurrency by generating a new version o ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

Recent studies on memristive materials and technologies have expanded beyond conventional memory elements, driven by their potential application in novel information processing concepts. Among these materials, conductive domain walls in ferroics are especi ...

Ferroelectric materials are explored for numerous applications thanks to their properties associated with electrically switchable spontaneous polarization. Perovskites are an established class of ferroelectrics used for sensors and actuators. However, they ...

Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks. This is puzzling given that theoretical resul ...

A method of accessing a memory space of a memory device with a decoder, the memory space having faults, including the steps of performing a memory access operation by an electronic device to a access a logical memory space of the memory device, and randomi ...

Metal–oxide–semiconductor junctions are the building blocks of modern electronics and can provide a variety of functionalities, from memory to computing. The technology, however, faces constraints in terms of further miniaturization and compatibility with ...

The research presented in this article draws inspiration from previous efforts aimed at replicating the functions of various solid-state memristors using a variety of materials. The memristor circuit emulator serves as a cost-effective tool for circuit des ...

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

2022 roadmap on neuromorphic computing and engineering

Chattez avec Graph Search

A Bio-Inspired Learning and Control Framework for Cross-Embodiment and Cross-Task Locomotion

A data-efficient and general-purpose hand–eye calibration method for robotic systems using next best view

Explainable modeling for wind power forecasting: A Glass-Box model with high accuracy

Sequential Reasoning with Socially Caused Beliefs

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Rebooting Virtual Memory with Midgard

How to Achieve Large-Area Ultra-Fast Operation of MoS 2 Monolayer Flash Memories?

Nano-MOSFET - Foundation of Quantum Computing Part I

Overflow-free compute memories for edge AI acceleration

One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version Storage

EdgeAI-Aware Design of In-Memory Computing Architectures

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Secure Interface Design Leveraging Hardware/Software Support

Graphene-enhanced ferroelectric domain wall high-output memristor

Exploring negative capacitance and neuromorphic devices based on CMOS-compatible ferroelectric HfO2

High-performance deep spiking neural networks with 0.3 spikes per neuron

Method for reading and writing unreliable memories and a corresponding memory controller device and memory

Electrical control of glass-like dynamics in vanadium dioxide for data storage and processing

Emulating Multimemristive Behavior of Silicon Nanowire-Based Biosensors by Using CMOS-Based Implementations

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads