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Synergistically Exploiting CNN Pruning and HLS Versioning for Adaptive Inference on Multi-FPGAs at the Edge

https://doi.org/10.1145/3476990
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-56258-2_23openalex-snapshot
An FPGA Realization of a Deep Convolutional Neural Network Using a Threshold Neuron Pruning
inferredcites →https://doi.org/10.1007/978-3-319-77610-1_23openalex-snapshot
A Flexible FPGA-Based Inference Architecture for Pruned Deep Neural Networks
inferredcites →https://doi.org/10.1007/s10462-020-09816-7openalex-snapshot
A comprehensive survey on model compression and acceleration
inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot
ImageNet Large Scale Visual Recognition Challenge
inferredcites →https://doi.org/10.1109/access.2019.2954546openalex-snapshot
DMS: Dynamic Model Scaling for Quality-Aware Deep Learning Inference in Mobile and Embedded Devices
inferredcites →https://doi.org/10.1109/iccv.2013.257openalex-snapshot
Joint Deep Learning for Pedestrian Detection
inferredcites →https://doi.org/10.1109/jproc.2019.2921977openalex-snapshot
Deep Learning With Edge Computing: A Review
inferredcites →https://doi.org/10.1109/mcom.2017.1700168openalex-snapshot
When Weather Matters: IoT-Based Electrical Load Forecasting for Smart Grid
inferredcites →https://doi.org/10.1109/tbc.2008.2001246openalex-snapshot
Temporal Aspect of Perceived Quality in Mobile Video Broadcasting
inferredcites →https://doi.org/10.1109/tii.2018.2842821openalex-snapshot
Deep Learning for Smart Industry: Efficient Manufacture Inspection System With Fog Computing
inferredcites →https://doi.org/10.1145/2024716.2024718openalex-snapshot
The gem5 simulator
inferredcites →https://doi.org/10.1145/2647868.2654889openalex-snapshot
Caffe
inferredcites →https://doi.org/10.1145/2684746.2689060openalex-snapshot
Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1145/2742647.2742663openalex-snapshot
Starfish
inferredcites →https://doi.org/10.1145/2789168.2790123openalex-snapshot
The Design and Implementation of a Wireless Video Surveillance System
inferredcites →https://doi.org/10.1145/2872887.2749472openalex-snapshot
DjiNN and Tonic
inferredcites →https://doi.org/10.1145/2897937.2898040openalex-snapshot
Lin-analyzer
inferredcites →https://doi.org/10.1145/3020078.3021740openalex-snapshot
Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?
inferredcites →https://doi.org/10.1145/3140659.3080215openalex-snapshot
Scalpel
inferredcites →https://doi.org/10.1145/3241539.3241559openalex-snapshot
NestDNN
inferredcites →https://doi.org/10.1145/3242897openalex-snapshot
FINN- R
inferredcites →https://doi.org/10.1145/3301418.3313946openalex-snapshot
A Reality Check on Inference at Mobile Networks Edge
inferredcites →https://doi.org/10.1145/3316781.3317829openalex-snapshot
FPGA/DNN Co-Design
inferredcites →https://doi.org/10.1145/3316781.3324696openalex-snapshot
ReForm
inferredcites →https://doi.org/10.1145/3358192openalex-snapshot
Achieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference
inferredcites →https://doi.org/10.1145/3366636openalex-snapshot
Design and Optimization of Energy-Accuracy Tradeoff Networks for Mobile Platforms via Pretrained Deep Models
inferredcites →https://doi.org/10.48550/arxiv.1608.04493openalex-snapshot
Dynamic Network Surgery for Efficient DNNs
inferredcites →https://doi.org/10.5555/2755753.2755788openalex-snapshot
Exploiting loop-array dependencies to accelerate the design space exploration with high level synthesis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-28451-9_12openalex-snapshot
Adaptive Inference on Reconfigurable SmartNICs for Traffic Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-29970-4_8openalex-snapshot
Adaptive Inference for FPGA-Based 5G Automatic Modulation Classification
inferred← citeshttps://doi.org/10.1007/978-3-032-35506-5_7openalex-snapshot
A Framework for the Automatic Deployment of Dependability Mechanisms on PyTorch-Based Models
inferred← citeshttps://doi.org/10.1016/j.vlsi.2025.102513openalex-snapshot
A systematic review of machine learning-driven design space exploration in high-level synthesis
inferred← citeshttps://doi.org/10.1109/dsd64264.2024.00034openalex-snapshot
Exploiting Virtual Layers and Pruning for FPGA-Based Adaptive Traffic Classification
inferred← citeshttps://doi.org/10.1109/dsd67783.2025.00026openalex-snapshot
Dynamic Multi-Accelerator Management for Deep Learning Applications on the FPGA Edge
inferred← citeshttps://doi.org/10.1109/iscas48785.2022.9937676openalex-snapshot
ConfAx: Exploiting Approximate Computing for Configurable FPGA CNN Acceleration at the Edge
inferred← citeshttps://doi.org/10.1109/isvlsi59464.2023.10238564openalex-snapshot
Dynamic Offloading for Improved Performance and Energy Efficiency in Heterogeneous IoT-Edge-Cloud Continuum
inferred← citeshttps://doi.org/10.1109/isvlsi59464.2023.10238644openalex-snapshot
Design Space Exploration for CNN Offloading to FPGAs at the Edge
inferred← citeshttps://doi.org/10.1109/lascas64004.2025.10966362openalex-snapshot
Heterogeneity-Aware Offloading for the IoT-Edge-Cloud Continuum
inferred← citeshttps://doi.org/10.1109/lciot64881.2025.11118528openalex-snapshot
Advances in AI Hardware Design in the Continuum: A Survey on Frameworks, Optimization, and Integration in Heterogeneous Systems
inferred← citeshttps://doi.org/10.1109/sbcci62366.2024.10704009openalex-snapshot
ADARE: Adaptive Resource Provisioning in Multi-FPGA Edge Environments
inferred← citeshttps://doi.org/10.1109/sbcci69725.2026.11706762openalex-snapshot
Stochastic Depth and Static Masks: A Deterministic Approach to Edge Layer Skipping
inferred← citeshttps://doi.org/10.1109/tcsii.2022.3223925openalex-snapshot
A Comprehensive Evaluation of Convolutional Hardware Accelerators
inferred← citeshttps://doi.org/10.1109/tsusc.2024.3382157openalex-snapshot
APPQ-CNN: An Adaptive CNNs Inference Accelerator for Synergistically Exploiting Pruning and Quantization Based on FPGA
inferred← citeshttps://doi.org/10.23919/date54114.2022.9774727openalex-snapshot
AdaFlow: A Framework for Adaptive Dataflow CNN Acceleration on FPGAs
inferred← citeshttps://doi.org/10.23919/date56975.2023.10137244openalex-snapshot
Pruning and Early-Exit Co-Optimization for CNN Acceleration on FPGAs
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