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06/29/2023
Performance Analysis of DNN Inference/Training with Convolution and non-Convolution Operations
Today's performance analysis frameworks for deep learning accelerators s...
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06/15/2023
Towards Sustainable Computing: Assessing the Carbon Footprint of Heterogeneous Systems
Decades of progress in energy-efficient and low-power design have succes...
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12/26/2021
A Linear-Time Algorithm for Steady-State Analysis of Electromigration in General Interconnects
Electromigration (EM) is a key reliability issue in deeply scaled techno...
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10/27/2021
Encoder-Decoder Networks for Analyzing Thermal and Power Delivery Networks
Power delivery network (PDN) analysis and thermal analysis are computati...
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10/27/2021
OpeNPDN: A Neural-network-based Framework for Power Delivery Network Synthesis
Power delivery network (PDN) design is a nontrivial, time-intensive, and...
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06/15/2021
Exploring the Feasibility of Using 3D XPoint as an In-Memory Computing Accelerator
This paper describes how 3D XPoint memory arrays can be used as in-memor...
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05/21/2021
GNNIE: GNN Inference Engine with Load-balancing and Graph-Specific Caching
Graph neural networks (GNN) analysis engines are vital for real-world pr...
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05/18/2021
A New, Computationally Efficient "Blech Criterion" for Immortality in General Interconnects
Traditional methodologies for analyzing electromigration (EM) in VLSI ci...
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12/19/2020
MAVIREC: ML-Aided Vectored IR-DropEstimation and Classification
Vectored IR drop analysis is a critical step in chip signoff that checks...
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09/30/2020
A general approach for identifying hierarchical symmetry constraints for analog circuit layout
Analog layout synthesis requires some elements in the circuit netlist to...
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09/18/2020
Thermal and IR Drop Analysis Using Convolutional Encoder-Decoder Networks
Computationally expensive temperature and power grid analyses are requir...
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08/24/2020
ALIGN: A System for Automating Analog Layout
ALIGN ("Analog Layout, Intelligently Generated from Netlists") is an ope...
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08/29/2019
A Machine Learning Accelerator In-Memory for Energy Harvesting
There is increasing demand to bring machine learning capabilities to low...
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05/09/2019