Imagen de Portada

DNA: Differentiable Network-Accelerator Co-Search

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhang, Yongan, Fu, Yonggan, Jiang, Weiwen, Li, Chaojian, You, Haoran, Li, Meng, Chandra, Vikas, Lin, Yingyan Celine
Formato:	Preprint
Publicado:	2020
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning
por: Fu, Yonggan, et al.
Publicado: (2021)

Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
por: Fu, Yonggan, et al.
Publicado: (2021)

HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark
por: Li, Chaojian, et al.
Publicado: (2021)

GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design
por: You, Haoran, et al.
Publicado: (2021)

Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search
por: Fu, Yonggan, et al.
Publicado: (2020)

ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
por: You, Haoran, et al.
Publicado: (2022)

GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models
por: Fu, Yonggan, et al.
Publicado: (2023)

2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
por: Fu, Yonggan, et al.
Publicado: (2021)

InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks
por: Fu, Yonggan, et al.
Publicado: (2021)

ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design
por: You, Haoran, et al.
Publicado: (2022)

ShiftAddNet: A Hardware-Inspired Deep Network
por: You, Haoran, et al.
Publicado: (2020)

CPT: Efficient Deep Neural Network Training via Cyclic Precision
por: Fu, Yonggan, et al.
Publicado: (2021)

DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference
por: Li, Chaojian, et al.
Publicado: (2021)

Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets
por: You, Haoran, et al.
Publicado: (2021)

MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation
por: Zhang, Yongan, et al.
Publicado: (2024)

Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks
por: You, Haoran, et al.
Publicado: (2019)

AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
por: Fu, Yonggan, et al.
Publicado: (2020)

DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
por: Fu, Yonggan, et al.
Publicado: (2022)

ERSAM: Neural Architecture Search For Energy-Efficient and Real-Time Social Ambiance Measurement
por: Li, Chaojian, et al.
Publicado: (2023)

AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment
por: Fu, Yonggan, et al.
Publicado: (2024)

Robust Tickets Can Transfer Better: Drawing More Transferable Subnetworks in Transfer Learning
por: Fu, Yonggan, et al.
Publicado: (2023)

EyeCoD: Eye Tracking System Acceleration via FlatCam-based Algorithm & Accelerator Co-Design
por: You, Haoran, et al.
Publicado: (2022)

SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning
por: You, Haoran, et al.
Publicado: (2022)

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
por: Fu, Yonggan, et al.
Publicado: (2021)

ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
por: You, Haoran, et al.
Publicado: (2023)

Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
por: Yu, Zhongzhi, et al.
Publicado: (2024)

When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
por: You, Haoran, et al.
Publicado: (2024)

Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling
por: Li, Chaojian, et al.
Publicado: (2025)

ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
por: You, Haoran, et al.
Publicado: (2024)

FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training
por: Fu, Yonggan, et al.
Publicado: (2020)

From Inference Efficiency to Embodied Efficiency: Revisiting Efficiency Metrics for Vision-Language-Action Models
por: Li, Zhuofan, et al.
Publicado: (2026)

Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing
por: Fu, Yonggan, et al.
Publicado: (2022)

Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance Fields
por: Fu, Yonggan, et al.
Publicado: (2024)

LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
por: Shi, Dachuan, et al.
Publicado: (2025)

i-FlatCam: A 253 FPS, 91.49 $μ$J/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR
por: Zhao, Yang, et al.
Publicado: (2022)

Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design
por: Fu, Yonggan, et al.
Publicado: (2023)

Uni-Render: A Unified Accelerator for Real-Time Rendering Across Diverse Neural Renderers
por: Li, Chaojian, et al.
Publicado: (2025)

Max-Affine Spline Insights Into Deep Network Pruning
por: You, Haoran, et al.
Publicado: (2021)

$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
por: Du, Zhenbang, et al.
Publicado: (2026)

Gaussian Blending Unit: An Edge GPU Plug-in for Real-Time Gaussian-Based Rendering in AR/VR
por: Ye, Zhifan, et al.
Publicado: (2025)