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03/10/2022
Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements
Neuromorphic hardware platforms can significantly lower the energy overh...
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08/27/2021
A Design Flow for Mapping Spiking Neural Networks to Many-Core Neuromorphic Hardware
The design of many-core neuromorphic hardware is getting more and more c...
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08/04/2021
DFSynthesizer: Dataflow-based Synthesis of Spiking Neural Networks to Neuromorphic Hardware
Spiking Neural Networks (SNN) are an emerging computation model, which u...
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05/05/2021
Dynamic Reliability Management in Neuromorphic Computing
Neuromorphic computing systems uses non-volatile memory (NVM) to impleme...
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05/04/2021
NeuroXplorer 1.0: An Extensible Framework for Architectural Exploration with Spiking Neural Networks
Recently, both industry and academia have proposed many different neurom...
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03/09/2021
Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware
Neuromorphic computing systems are embracing memristors to implement hig...
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11/30/2020
Aging-Aware Request Scheduling for Non-Volatile Main Memory
Modern computing systems are embracing non-volatile memory (NVM) to impl...
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10/06/2020
A Generalized Framework for Analytic Regularization of Uniform Cubic B-spline Displacement Fields
Image registration is an inherently ill-posed problem that lacks the con...
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09/19/2020
Enabling Resource-Aware Mapping of Spiking Neural Networks via Spatial Decomposition
With growing model complexity, mapping Spiking Neural Network (SNN)-base...
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06/10/2020
Improving Dependability of Neuromorphic Computing With Non-Volatile Memory
As process technology continues to scale aggressively, circuit aging in ...
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05/10/2020
Improving Phase Change Memory Performance with Data Content Aware Access
A prominent characteristic of write operation in Phase-Change Memory (PC...
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05/10/2020
Exploiting Inter- and Intra-Memory Asymmetries for Data Mapping in Hybrid Tiered-Memories
Modern computing systems are embracing hybrid memory comprising of DRAM ...
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04/07/2020
Compiling Spiking Neural Networks to Neuromorphic Hardware
Machine learning applications that are implemented with spike-based comp...
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11/01/2019
A Framework to Explore Workload-Specific Performance and Lifetime Trade-offs in Neuromorphic Computing
Neuromorphic hardware with non-volatile memory (NVM) can implement machi...
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08/21/2019