Imagen de Portada

Coflex: Enhancing HW-NAS with Sparse Gaussian Processes for Efficient and Scalable DNN Accelerator Design

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ma, Yinhui, Yamasaki, Tomomasa, Wang, Zhehui, Luo, Tao, Wang, Bo
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning I.2.6; C.1.3; C.3
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

OpenEye: A Scalable Open-Source Hardware Accelerator for DNNs
por: Lebold, Denis, et al.
Publicado: (2026)

FPGA-Accelerated RISC-V ISA Extensions for Efficient Neural Network Inference on Edge Devices
por: Parameshwara, Arya, et al.
Publicado: (2025)

BMR and BWR: Two simple metaphor-free optimization algorithms for solving real-life non-convex constrained and unconstrained problems
por: Rao, Ravipudi Venkata, et al.
Publicado: (2024)

SynapticCore-X: A Modular Neural Processing Architecture for Low-Cost FPGA Acceleration
por: Parameshwara, Arya
Publicado: (2025)

What Scalable Second-Order Information Knows for Pruning at Initialization
por: Navarrete, Ivo Gollini, et al.
Publicado: (2025)

XFP: Quality-Targeted Adaptive Codebook Quantization with Sparse Outlier Separation for LLM Inference
por: Witt, Thomas
Publicado: (2026)

Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers
por: Yuan, Xinzhe, et al.
Publicado: (2026)

GraphPerf-RT: A Graph-Driven Performance Model for Hardware-Aware Scheduling of OpenMP Codes
por: Pivezhandi, Mohammad, et al.
Publicado: (2025)

FlexiBit: Fully Flexible Precision Bit-parallel Accelerator Architecture for Arbitrary Mixed Precision AI
por: Tahmasebi, Faraz, et al.
Publicado: (2024)

BurTorch: Revisiting Training from First Principles by Coupling Autodiff, Math Optimization, and Systems
por: Burlachenko, Konstantin, et al.
Publicado: (2025)

Biological Intuition on Digital Hardware: An RTL Implementation of Poisson-Encoded SNNs for Static Image Classification
por: Das, Debabrata, et al.
Publicado: (2026)

Programmable Optical Spectrum Shapers as Computing Primitives for Accelerating Convolutional Neural Networks
por: Moustakas, Georgios, et al.
Publicado: (2025)

SPARTA: Advancing Sparse Attention in Spiking Neural Networks via Spike-Timing-Based Prioritization
por: Jang, Minsuk, et al.
Publicado: (2025)

MEDEA: A Design-Time Multi-Objective Manager for Energy-Efficient DNN Inference on Heterogeneous Ultra-Low Power Platforms
por: Taji, Hossein, et al.
Publicado: (2025)

An Energy-Efficient Spiking Neural Network Architecture for Predictive Insulin Delivery
por: Shrivastava, Sahil
Publicado: (2026)

Spiking Neural Network Architecture Search: A Survey
por: Svoboda, Kama, et al.
Publicado: (2025)

Design and Implementation of a RISC-V SoC with Custom DSP Accelerators for Edge Computing
por: Yadav, Priyanshu
Publicado: (2025)

Eventprop training for efficient neuromorphic applications
por: Shoesmith, Thomas, et al.
Publicado: (2025)

Toward Thermodynamic Reservoir Computing: Exploring SHA-256 ASICs as Potential Physical Substrates
por: de Lafuente, Francisco Angulo, et al.
Publicado: (2026)

The Native Spiking Microarchitecture: From Iontronic Primitives to Bit-Exact FP8 Arithmetic
por: Tang, Zhengzheng
Publicado: (2025)

PI-TTA: Physics-Informed Source-Free Test-Time Adaptation for Robust Human Activity Recognition on Mobile Devices
por: Li, Changyu, et al.
Publicado: (2026)

ReMoE: Boosting Expert Reuse through Router Fine-Tuning in Memory-Constrained MoE LLM Inference
por: Zhu, Xiongwei, et al.
Publicado: (2026)

Energy-Efficient Neuromorphic Computing for Edge AI: A Framework with Adaptive Spiking Neural Networks and Hardware-Aware Optimization
por: Imanov, Olaf Yunus Laitinen, et al.
Publicado: (2026)

Nonvolatile Charge-Domain Attention with HZO Ferroelectric Capacitors: A Simulation-Based Device-to-System Evaluation
por: Abouagour, Faris
Publicado: (2026)

Scalable Transit Delay Prediction at City Scale: A Systematic Approach with Multi-Resolution Feature Engineering and Deep Learning
por: Boudabbous, Emna, et al.
Publicado: (2026)

Towards the Detection of Building Occupancy with Synthetic Environmental Data
por: Weber, Manuel, et al.
Publicado: (2020)

CORE: Constraint-Aware One-Step Reinforcement Learning for Simulation-Guided Neural Network Accelerator Design
por: Xiao, Yifeng, et al.
Publicado: (2025)

Economic Causal Inference Based on DML Framework: Python Implementation of Binary and Continuous Treatment Variables
por: Yao, Shunxin
Publicado: (2025)

PARD-SSM: Probabilistic Cyber-Attack Regime Detection via Variational Switching State-Space Models
por: Hiremath, Prakul Sunil, et al.
Publicado: (2026)

AI-Enhanced IoT Systems for Predictive Maintenance and Affordability Optimization in Smart Microgrids: A Digital Twin Approach
por: Kushal, Koushik Ahmed, et al.
Publicado: (2025)

CoSense-LLM: Semantics at the Edge with Cost- and Uncertainty-Aware Cloud-Edge Cooperation
por: Akgul, Hasan, et al.
Publicado: (2025)

The Configuration Wall: Characterization and Elimination of Accelerator Configuration Overhead
por: Van Delm, Josse, et al.
Publicado: (2025)

A Survey of TinyML Applications in Beekeeping for Hive Monitoring and Management
por: Sucipto, Willy, et al.
Publicado: (2025)

Lightweight LLMs for Network Attack Detection in IoT Networks
por: Sudasinghe, Piyumi Bhagya, et al.
Publicado: (2026)

Ultra-Fast Device-Free Visible Light Sensing and Localization via Reflection-Based ΔRSS and Deep Learning
por: Serpi, Helena, et al.
Publicado: (2026)

Machine Learning based Radio Environment Map Estimation for Indoor Visible Light Communication
por: Serpi, Helena, et al.
Publicado: (2025)

MoPFormer: Motion-Primitive Transformer for Wearable-Sensor Activity Recognition
por: Zhang, Hao, et al.
Publicado: (2025)

Federated Learning over Human-Body Communication for On-Body Edge Intelligence: A Survey, Taxonomy, and BODYFED-HBC Scheduling Vignette
por: Khan, Koffka
Publicado: (2026)

Making Logic a First-Class Citizen in Generative ML for Networking
por: Hè, Hongyu, et al.
Publicado: (2025)

LLM-Driven Large-Scale Spectrum Access
por: Yang, Ning, et al.
Publicado: (2026)