Content addressable memory (CAM)

Denim: Heterogeneous Compute-in-Memory Accelerator Exploiting Denoising–Similarity for Diffusion Models

Denim: Heterogeneous Compute-in-Memory Accelerator Exploiting Denoising–Similarity for Diffusion Models 150 150

Abstract:

Diffusion models have recently revolutionized the field of image synthesis due to their ability to generate photorealistic images. However, one of the main drawbacks of diffusion models is that the image generation process is expensive. Large image-to-image networks have to be applied multiple times in order to iteratively optimize the …

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A SPICE-Compatible Compact Model of Ferroelectric Diode

A SPICE-Compatible Compact Model of Ferroelectric Diode 150 150

Abstract:

In this work, for the first time, we present a SPICE-compatible compact model of ferroelectric (FE) diodes to enable their design exploration for diverse applications, including memory and unconventional computing paradigms. We propose modified Schottky barrier and hopping models for capturing the on- and off-mode operations of the FE diode, …

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A 28-nm Computing-in-Memory Processor With Zig-Zag Backbone-Systolic CIM and Block-/Self-Gating CAM for NN/Recommendation Applications

A 28-nm Computing-in-Memory Processor With Zig-Zag Backbone-Systolic CIM and Block-/Self-Gating CAM for NN/Recommendation Applications 150 150

Abstract:

Computing-in-memory (CIM) chips have demonstrated promising energy efficiency for artificial intelligence (AI) applications such as neural networks (NNs), Transformer, and recommendation system (RecSys). However, several challenges still exist. First, a large gap between the macro and system-level CIM energy efficiency is observed. Second, several memory-dominate operations, such as embedding in …

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A 128-kbit Approximate Search-Capable Content-Addressable Memory (CAM) With Tunable Hamming Distance

A 128-kbit Approximate Search-Capable Content-Addressable Memory (CAM) With Tunable Hamming Distance 150 150

Abstract:

The growing need for approximate matching in data-intensive applications, such as data analytics, machine learning, deep learning, and computational genomics has driven the proposal of our Hamming distance (HD) tolerant content-addressable memory (HD-CAM). HD-CAM features a modified NOR-type associative memory cell that leverages the discharge speed of the matchline (ML) …

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