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07/20/2023
Approximate Computing Survey, Part II: Application-Specific Architectural Approximation Techniques and Applications
The challenging deployment of compute-intensive applications from domain...
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07/20/2023
Approximate Computing Survey, Part I: Terminology and Software Hardware Approximation Techniques
The rapid growth of demanding applications in domains applying multimedi...
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05/02/2023
The Unexpected Efficiency of Bin Packing Algorithms for Dynamic Storage Allocation in the Wild: An Intellectual Abstract
Recent work has shown that viewing allocators as black-box 2DBP solvers ...
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04/21/2023
Viewing Allocators as Bin Packing Solvers Demystifies Fragmentation
This paper presents a trace-based simulation methodology for constructin...
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04/03/2023
Energy Consumption Evaluation of Optane DC Persistent Memory for Indexing Data Structures
The Intel Optane DC Persistent Memory (DCPM) is an attractive novel tech...
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03/14/2023
Model-to-Circuit Cross-Approximation For Printed Machine Learning Classifiers
Printed electronics (PE) promises on-demand fabrication, low non-recurri...
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02/28/2023
Co-Design of Approximate Multilayer Perceptron for Ultra-Resource Constrained Printed Circuits
Printed Electronics (PE) exhibits on-demand, extremely low-cost hardware...
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08/30/2022
Towards making the most of NLP-based device mapping optimization for OpenCL kernels
Nowadays, we are living in an era of extreme device heterogeneity. Despi...
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03/16/2022
Hardware Approximate Techniques for Deep Neural Network Accelerators: A Survey
Deep Neural Networks (DNNs) are very popular because of their high perfo...
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03/11/2022
Cross-Layer Approximation For Printed Machine Learning Circuits
Printed electronics (PE) feature low non-recurring engineering costs and...
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03/08/2022
AdaPT: Fast Emulation of Approximate DNN Accelerators in PyTorch
Current state-of-the-art employs approximate multipliers to address the ...
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12/05/2016
