Synaptogen: A cross-domain generative device model for large-scale neuromorphic circuit design
We present a fast generative modeling approach for resistive memories that reproduces the complex statistical properties of real-world devices. To enable efficient modeling of analog circuits, the model is implemented in Verilog-A. By training on extensive measurement data of integrated 1T1R arrays (6,000 cycles of 512 devices), an autoregressive stochastic process accurately accounts for the cross-correlations between the switching parameters, while non-linear transformations ensure agreement with both cycle-to-cycle (C2C) and device-to-device (D2D) variability. Benchmarks show that this statistically comprehensive model achieves read/write throughputs exceeding those of even highly simplified and deterministic compact models.
Code (1)
Similar Papers 제목 키워드 기반
A Differentiable Model for Optimizing the Genetic Drivers of Synaptogenesis
There is a growing consensus among neuroscientists that many neural circuits critical for survival result from a process of genomic decompression, hence are constructed based on the information contained within the genom…
Adaptive Synaptogenesis Implemented on a Nanomagnetic Platform
The human brain functions very differently from artificial neural networks (ANN) and possesses unique features that are absent in ANN. An important one among them is "adaptive synaptogenesis" that modifies synaptic weigh…
Edge-computingHippocampusLifelong learningExploring the Imposition of Synaptic Precision Restrictions For Evolutionary Synthesis of Deep Neural Networks
A key contributing factor to incredible success of deep neural networks has been the significant rise on massively parallel computing devices allowing researchers to greatly increase the size and depth of deep neural net…
A Distributed Generative AI Approach for Heterogeneous Multi-Domain Environments under Data Sharing constraints
Federated Learning has gained increasing attention for its ability to enable multiple nodes to collaboratively train machine learning models without sharing their raw data. At the same time, Generative AI -- particularly…
Federated LearningImage GenerationSelf-building Neural Networks
During the first part of life, the brain develops while it learns through a process called synaptogenesis. The neurons, growing and interacting with each other, create synapses. However, eventually the brain prunes those…