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12/07/2022
SDRM3: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads
Emerging real-time multi-model ML (RTMM) workloads such as AR/VR and dro...
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11/16/2022
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse
Real-time multi-model multi-task (MMMT) workloads, a new form of deep le...
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11/02/2021
Low-Rank+Sparse Tensor Compression for Neural Networks
Low-rank tensor compression has been proposed as a promising approach to...
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11/01/2021
HRViT: Multi-Scale High-Resolution Vision Transformer
Vision transformers (ViTs) have attracted much attention for their super...
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02/13/2020
Improving Efficiency in Neural Network Accelerator Using Operands Hamming Distance optimization
Neural network accelerator is a key enabler for the on-device AI inferen...
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02/10/2020
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks
Neural Architecture Search (NAS) has demonstrated its power on various A...
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09/13/2019
HERALD: Optimizing Heterogeneous DNN Accelerators for Edge Devices
Recent advances in deep neural networks (DNNs) have made DNNs the backbo...
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06/20/2018
Rethinking Machine Learning Development and Deployment for Edge Devices
Machine learning (ML), especially deep learning is made possible by the ...
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06/02/2018
Federated Learning with Non-IID Data
Federated learning enables resource-constrained edge compute devices, su...
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01/19/2018
CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs
Deep Neural Networks are becoming increasingly popular in always-on IoT ...
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01/12/2018
Not All Ops Are Created Equal!
Efficient and compact neural network models are essential for enabling t...
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12/05/2017
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks
Hardware acceleration of Deep Neural Networks (DNNs) aims to tame their ...
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11/20/2017
Hello Edge: Keyword Spotting on Microcontrollers
Keyword spotting (KWS) is a critical component for enabling speech based...
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03/08/2017