tag: neuromorphic computing

Seven Hardware Advances We Need to Enable The AI Revolution
By Remy Pottier - 10 Mar, 2022 - Comments: 1

The potential, positive impact AI will have on society at large is impossible to overestimate. Pervasive AI, however, remains a challenge. Training algorithms can take inordinate amounts of power, time, and computing capacity. Inference will also become more taxing with applications such as medical imaging and robotics. Applied Materials estimates that AI could consume up to 25% of global elect... » read more

Reservoir Computing based on Mutually Injected Phase Modulated Semiconductor Lasers as a Monolithic Integrated Hardware Accelerator
By Technical Paper Link - 08 Feb, 2022 - Comments: 0

Abstract: "In this paper we propose and numerically study a neuromorphic computing scheme that applies delay-based reservoir computing in a laser system consisting of two mutually coupled phase modulated lasers. The scheme can be monolithic integrated in a straightforward manner and alleviates the need for external optical injection, as the data can be directly applied on the on-chip phase m... » read more

An Event-Driven and Fully Synthesizable Architecture for Spiking Neural Networks
By Technical Paper Link - 20 Dec, 2021 - Comments: 0

Abstract:  "The development of brain-inspired neuromorphic computing architectures as a paradigm for Artificial Intelligence (AI) at the edge is a candidate solution that can meet strict energy and cost reduction constraints in the Internet of Things (IoT) application areas. Toward this goal, we present μBrain: the first digital yet fully event-driven without clock architecture, with co-lo... » read more

Energy-efficient memcapacitor devices for neuromorphic computing
By Technical Paper Link - 03 Nov, 2021 - Comments: 0

Abstract Data-intensive computing operations, such as training neural networks, are essential for applications in artificial intelligence but are energy intensive. One solution is to develop specialized hardware onto which neural networks can be directly mapped, and arrays of memristive devices can, for example, be trained to enable parallel multiply–accumulate operations. Here we show that ... » read more

Nanoporous Dielectric Resistive Memories Using Sequential Infiltration Synthesis
By Technical Paper Link - 06 Oct, 2021 - Comments: 0

Abstract "Resistance switching in metal–insulator–metal structures has been extensively studied in recent years for use as synaptic elements for neuromorphic computing and as nonvolatile memory elements. However, high switching power requirements, device variabilities, and considerable trade-offs between low operating voltages, high on/off ratios, and low leakage have limited their utility... » read more

Making Sense Of New Edge-Inference Architectures
By Bryon Moyer - 04 Mar, 2021 - Comments: 0

New edge-inference machine-learning architectures have been arriving at an astounding rate over the last year. Making sense of them all is a challenge. To begin with, not all ML architectures are alike. One of the complicating factors in understanding the different machine-learning architectures is the nomenclature used to describe them. You’ll see terms like “sea-of-MACs,” “systolic... » read more

FeFETs Bring Promise And Challenges
By Bryon Moyer - 17 Feb, 2021 - Comments: 3

Ferroelectric FETs (FeFETs) and memory (FeRAM) are generating high levels of interest in the research community. Based on a physical mechanism that hasn’t yet been commercially exploited, they join the other interesting new physics ideas that are in various stages of commercialization. “FeRAM is very promising, but it's like all promising memory technologies — it takes a while to get b... » read more

Power/Performance Bits: Dec. 7
By Jesse Allen - 07 Dec, 2020 - Comments: 0

Logic-in-memory with MoS2 Engineers at École Polytechnique Fédérale de Lausanne (EPFL) built a logic-in-memory device using molybdenum disulfide (MoS2) as the channel material. MoS2 is a three-atom-thick 2D material and excellent semiconductor. The new chip is based on floating-gate field-effect transistors (FGFETs) that can hold electric charges for long periods. MoS2 is particularly se... » read more

Cerfe Labs: Spin-On Memory
By Ed Sperling - 05 Oct, 2020 - Comments: 0

Arm has spun off one of its more intriguing semiconductor research projects, a new non-volatile memory type called correlated electron materials RAM (CeRAM) that holds the potential to substantially reduce the cost of memory in everything from edge devices to high-performance computing. Headed by two former Arm Research insiders — Eric Hennenhoefer, who will serve as CEO and Greg Yeric, wh... » read more

Neuromorphic Computing Drives The Landscape Of Emerging Memories For Artificial Intelligence SoCs
By Synopsys - 03 Jun, 2020 - Comments: 0

The pace of deep machine learning and artificial intelligence (AI) is changing the world of computing at all levels of hardware architecture, software, chip manufacturing, and system packaging. Two major developments have opened the doors to implementing new techniques in machine learning. First, vast amounts of data, i.e., “Big Data,” are available for systems to process. Second, advanced ... » read more

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