Imagen de Portada

A Flexible Precision Scaling Deep Neural Network Accelerator with Efficient Weight Combination

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhao, Liang, Shao, Kunming, Tian, Fengshi, Cheng, Tim Kwang-Ting, Tsui, Chi-Ying, Zou, Yi
Formato:	Preprint
Publicado:	2025
Materias:	Hardware Architecture Systems and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

DIRC-RAG: Accelerating Edge RAG with Robust High-Density and High-Loading-Bandwidth Digital In-ReRAM Computation
por: Shao, Kunming, et al.
Publicado: (2025)

Balancing FP8 Computation Accuracy and Efficiency on Digital CIM via Shift-Aware On-the-fly Aligned-Mantissa Bitwidth Prediction
por: Zhao, Liang, et al.
Publicado: (2026)

A Memory-Efficient Retrieval Architecture for RAG-Enabled Wearable Medical LLMs-Agents
por: Liao, Zhipeng, et al.
Publicado: (2025)

DS-CIM: Digital Stochastic Computing-In-Memory Featuring Accurate OR-Accumulation via Sample Region Remapping for Edge AI Models
por: Shao, Kunming, et al.
Publicado: (2026)

SynDCIM: A Performance-Aware Digital Computing-in-Memory Compiler with Multi-Spec-Oriented Subcircuit Synthesis
por: Shao, Kunming, et al.
Publicado: (2024)

A Hybrid-Domain Floating-Point Compute-in-Memory Architecture for Efficient Acceleration of High-Precision Deep Neural Networks
por: Yi, Zhiqiang, et al.
Publicado: (2025)

31.1 A 14.08-to-135.69Token/s ReRAM-on-Logic Stacked Outlier-Free Large-Language-Model Accelerator with Block-Clustered Weight-Compression and Adaptive Parallel-Speculative-Decoding
por: Dong, Pingcheng, et al.
Publicado: (2026)

FETTA: Flexible and Efficient Hardware Accelerator for Tensorized Neural Network Training
por: Lu, Jinming, et al.
Publicado: (2025)

High Utilization Energy-Aware Real-Time Inference Deep Convolutional Neural Network Accelerator
por: Lin, Kuan-Ting, et al.
Publicado: (2025)

Efficient Implementation of an Adaptive Transformer Accelerator for Massive MIMO Outdoor Localization
por: Yaman, Ilayda, et al.
Publicado: (2026)

FGMP: Fine-Grained Mixed-Precision Weight and Activation Quantization for Hardware-Accelerated LLM Inference
por: Hooper, Coleman, et al.
Publicado: (2025)

CIMPool: Scalable Neural Network Acceleration for Compute-In-Memory using Weight Pools
por: Li, Shurui, et al.
Publicado: (2025)

Layer-wise Weight Selection for Power-Efficient Neural Network Acceleration
por: Fang, Jiaxun, et al.
Publicado: (2025)

VitaLLM: A Versatile and Tiny Accelerator for Mixed-Precision LLM Inference on Edge Devices
por: Lin, Zi-Wei, et al.
Publicado: (2026)

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign
por: Wu, Michael, et al.
Publicado: (2025)

Aging Aware Adaptive Voltage Scaling for Reliable and Efficient AI Accelerators
por: Xie, Tong, et al.
Publicado: (2026)

A Low-Power Sparse Deep Learning Accelerator with Optimized Data Reuse
por: Hsu, Kai-Chieh, et al.
Publicado: (2025)

Reuse and Blend: Energy-Efficient Optical Neural Network Enabled by Weight Sharing
por: Xu, Bo, et al.
Publicado: (2024)

SeDA: Secure and Efficient DNN Accelerators with Hardware/Software Synergy
por: Xuan, Wei, et al.
Publicado: (2025)

Multilayer Dataflow: Orchestrate Butterfly Sparsity to Accelerate Attention Computation
por: Wu, Haibin, et al.
Publicado: (2024)

Hardware Efficient Accelerator for Spiking Transformer With Reconfigurable Parallel Time Step Computing
por: Chen, Bo-Yu, et al.
Publicado: (2025)

SIRA: Scaled-Integer Range Analysis for Optimizing FPGA Dataflow Neural Network Accelerators
por: Umuroglu, Yaman, et al.
Publicado: (2025)

Platinum: Path-Adaptable LUT-Based Accelerator Tailored for Low-Bit Weight Matrix Multiplication
por: Shan, Haoxuan, et al.
Publicado: (2025)

ONE-SA: Enabling Nonlinear Operations in Systolic Arrays for Efficient and Flexible Neural Network Inference
por: Sun, Ruiqi, et al.
Publicado: (2024)

Beehive: A Flexible Network Stack for Direct-Attached Accelerators
por: Lim, Katie, et al.
Publicado: (2024)

Special Session: Sustainable Deployment of Deep Neural Networks on Non-Volatile Compute-in-Memory Accelerators
por: Qin, Yifan, et al.
Publicado: (2025)

Analysis of Single Event Induced Bit Faults in a Deep Neural Network Accelerator Pipeline
por: Jonckers, Naïn, et al.
Publicado: (2025)

SiTe CiM: Signed Ternary Computing-in-Memory for Ultra-Low Precision Deep Neural Networks
por: Thakuria, Niharika, et al.
Publicado: (2024)

A PVT-Resilient Subthreshold SRAM-Based In-Memory Computing Accelerator with In-Situ Regulation for Energy-Efficient Spiking Neural Networks
por: Kao, Shih-Hang, et al.
Publicado: (2026)

Prosperity: Accelerating Spiking Neural Networks via Product Sparsity
por: Wei, Chiyue, et al.
Publicado: (2025)

Leveraging Application-Specific Knowledge for Energy-Efficient Deep Learning Accelerators on Resource-Constrained FPGAs
por: Qian, Chao
Publicado: (2025)

ADiP: Adaptive-Precision Systolic Array for Matrix Multiplication Acceleration
por: Abdelmaksoud, Ahmed J., et al.
Publicado: (2025)

Memory-Guided Unified Hardware Accelerator for Mixed-Precision Scientific Computing
por: Wang, Chuanzhen, et al.
Publicado: (2026)

FILCO: Flexible Composing Architecture with Real-Time Reconfigurability for DNN Acceleration
por: Chen, Xingzhen, et al.
Publicado: (2026)

Voxel-CIM: An Efficient Compute-in-Memory Accelerator for Voxel-based Point Cloud Neural Networks
por: Lin, Xipeng, et al.
Publicado: (2024)

LLMulator: Generalizable Cost Modeling for Dataflow Accelerators with Input-Adaptive Control Flow
por: Chang, Kaiyan, et al.
Publicado: (2025)

RCW-CIM: A Digital CIM-based LLM Accelerator with Read-Compute/Write
por: Guo, Yan-Cheng, et al.
Publicado: (2026)

A 10.60 $μ$W 150 GOPS Mixed-Bit-Width Sparse CNN Accelerator for Life-Threatening Ventricular Arrhythmia Detection
por: Qin, Yifan, et al.
Publicado: (2024)

TATAA: Programmable Mixed-Precision Transformer Acceleration with a Transformable Arithmetic Architecture
por: Wu, Jiajun, et al.
Publicado: (2024)

MASQ: Accelerating Masked Diffusion via Stage-Wise Multi-Precision Quantization
por: Kim, Seeyeon, et al.
Publicado: (2026)