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09/12/2023
C4CAM: A Compiler for CAM-based In-memory Accelerators
Machine learning and data analytics applications increasingly suffer fro...
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08/04/2023
Privacy Preserving In-memory Computing Engine
Privacy has rapidly become a major concern/design consideration. Homomor...
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07/29/2023
Improving Realistic Worst-Case Performance of NVCiM DNN Accelerators through Training with Right-Censored Gaussian Noise
Compute-in-Memory (CiM), built upon non-volatile memory (NVM) devices, i...
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07/27/2023
Accelerating Polynomial Modular Multiplication with Crossbar-Based Compute-in-Memory
Lattice-based cryptographic algorithms built on ring learning with error...
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06/12/2023
On the Viability of using LLMs for SW/HW Co-Design: An Example in Designing CiM DNN Accelerators
Deep Neural Networks (DNNs) have demonstrated impressive performance acr...
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05/23/2023
Negative Feedback Training: A Novel Concept to Improve Robustness of NVCiM DNN Accelerators
Compute-in-Memory (CiM) utilizing non-volatile memory (NVM) devices pres...
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09/09/2022
ApproxTrain: Fast Simulation of Approximate Multipliers for DNN Training and Inference
Edge training of Deep Neural Networks (DNNs) is a desirable goal for con...
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07/25/2022
COSIME: FeFET based Associative Memory for In-Memory Cosine Similarity Search
In a number of machine learning models, an input query is searched acros...
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07/15/2022
Computing-In-Memory Neural Network Accelerators for Safety-Critical Systems: Can Small Device Variations Be Disastrous?
Computing-in-Memory (CiM) architectures based on emerging non-volatile m...
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05/25/2022
On the Reliability of Computing-in-Memory Accelerators for Deep Neural Networks
Computing-in-memory with emerging non-volatile memory (nvCiM) is shown t...
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02/18/2022
iMARS: An In-Memory-Computing Architecture for Recommendation Systems
Recommendation systems (RecSys) suggest items to users by predicting the...
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02/17/2022
SWIM: Selective Write-Verify for Computing-in-Memory Neural Accelerators
Computing-in-Memory architectures based on non-volatile emerging memorie...
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12/04/2021
IMCRYPTO: An In-Memory Computing Fabric for AES Encryption and Decryption
This paper proposes IMCRYPTO, an in-memory computing (IMC) fabric for ac...
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09/13/2021
RADARS: Memory Efficient Reinforcement Learning Aided Differentiable Neural Architecture Search
Differentiable neural architecture search (DNAS) is known for its capaci...
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07/06/2021
Uncertainty Modeling of Emerging Device-based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search
Emerging device-based Computing-in-memory (CiM) has been proved to be a ...
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05/05/2020
Computing-in-Memory for Performance and Energy Efficient Homomorphic Encryption
Homomorphic encryption (HE) allows direct computations on encrypted data...
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10/31/2019
Device-Circuit-Architecture Co-Exploration for Computing-in-Memory Neural Accelerators
Co-exploration of neural architectures and hardware design is promising ...
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02/06/2019
Fully Distributed Packet Scheduling Framework for Handling Disturbances in Lossy Real-Time Wireless Networks
Along with the rapid growth of Industrial Internet-of-Things (IIoT) appl...
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01/27/2019
Eva-CiM: A System-Level Performance and Energy Evaluation Framework for Computing-in-Memory Architectures
Computing-in-Memory (CiM) architectures aim to reduce costly data transf...
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01/27/2019
