Image de couverture de livre

MetaDSE: A Few-shot Meta-learning Framework for Cross-workload CPU Design Space Exploration

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Xue, Runzhen, Wu, Hao, Yan, Mingyu, Xiao, Ziheng, Ye, Xiaochun, Fan, Dongrui
Format:	Preprint
Publié:	2025
Sujets:	Hardware Architecture Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Multi-objective Optimization in CPU Design Space Exploration: Attention is All You Need
par: Xue, Runzhen, et autres
Publié: (2024)

ADE-HGNN: Accelerating HGNNs through Attention Disparity Exploitation
par: Han, Dengke, et autres
Publié: (2024)

GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator Frontend with Graph Decoupling and Recoupling
par: Xue, Runzhen, et autres
Publié: (2024)

Accelerating GNN Training through Locality-aware Dropout and Merge
par: Sun, Gongjian, et autres
Publié: (2025)

SiHGNN: Leveraging Properties of Semantic Graphs for Efficient HGNN Acceleration
par: Xue, Runzhen, et autres
Publié: (2024)

HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation
par: Xue, Runzhen, et autres
Publié: (2023)

TLV-HGNN: Thinking Like a Vertex for Memory-efficient HGNN Inference
par: Han, Dengke, et autres
Publié: (2025)

OneDSE: A Unified Microprocessor Metric Prediction and Design Space Exploration Framework
par: Raj, Ritik, et autres
Publié: (2025)

SoberDSE: Sample-Efficient Design Space Exploration via Learning-Based Algorithm Selection
par: Xu, Lei, et autres
Publié: (2026)

Survey on Characterizing and Understanding GNNs from a Computer Architecture Perspective
par: Wu, Meng, et autres
Publié: (2024)

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs
par: Li, Runkai, et autres
Publié: (2025)

FIFOAdvisor: A DSE Framework for Automated FIFO Sizing of High-Level Synthesis Designs
par: Abi-Karam, Stefan, et autres
Publié: (2025)

StreamDCIM: A Tile-based Streaming Digital CIM Accelerator with Mixed-stationary Cross-forwarding Dataflow for Multimodal Transformer
par: Qin, Shantian, et autres
Publié: (2025)

Intelligent4DSE: Optimizing High-Level Synthesis Design Space Exploration with Graph Neural Networks and Large Language Models
par: Xu, Lei, et autres
Publié: (2025)

Characterizing and Understanding HGNN Training on GPUs
par: Han, Dengke, et autres
Publié: (2024)

Accelerating Mini-batch HGNN Training by Reducing CUDA Kernels
par: Wu, Meng, et autres
Publié: (2024)

MPM-LLM4DSE: Reaching the Pareto Frontier in HLS with Multimodal Learning and LLM-Driven Exploration
par: Xu, Lei, et autres
Publié: (2026)

Cool-3D: An End-to-End Thermal-Aware Framework for Early-Phase Design Space Exploration of Microfluidic-Cooled 3DICs
par: Wang, Runxi, et autres
Publié: (2025)

DiffuSE: Cross-Layer Design Space Exploration of DNN Accelerator via Diffusion-Driven Optimization
par: Ren, Yi, et autres
Publié: (2025)

Voyager: An End-to-End Framework for Design-Space Exploration and Generation of DNN Accelerators
par: Prabhu, Kartik, et autres
Publié: (2025)

LLM-DSE: Searching Accelerator Parameters with LLM Agents
par: Wang, Hanyu, et autres
Publié: (2025)

QiMeng-CPU-v2: Automated Superscalar Processor Design by Learning Data Dependencies
par: Cheng, Shuyao, et autres
Publié: (2025)

Anatomy of the gem5 Simulator: AtomicSimpleCPU, TimingSimpleCPU, O3CPU, and Their Interaction with the Ruby Memory System
par: Söderström, Johan, et autres
Publié: (2025)

Processing-in-memory for genomics workloads
par: Simon, William Andrew, et autres
Publié: (2025)

MetaML-Pro: Cross-Stage Design Flow Automation for Efficient Deep Learning Acceleration
par: Que, Zhiqiang, et autres
Publié: (2025)

Multilayer Dataflow: Orchestrate Butterfly Sparsity to Accelerate Attention Computation
par: Wu, Haibin, et autres
Publié: (2024)

SPEC CPU2026: Characterization, Representativeness, and Cross-Suite Comparison
par: Li, Ruihao, et autres
Publié: (2026)

Polaris: Multi-Fidelity Design Space Exploration of Deep Learning Accelerators
par: Sakhuja, Chirag, et autres
Publié: (2024)

Efficient Task Transfer for HLS DSE
par: Ding, Zijian, et autres
Publié: (2024)

Stream: Design Space Exploration of Layer-Fused DNNs on Heterogeneous Dataflow Accelerators
par: Symons, Arne, et autres
Publié: (2022)

RapidChiplet: A Toolchain for Rapid Design Space Exploration of Chiplet Architectures
par: Iff, Patrick, et autres
Publié: (2023)

ACALSim: A Scalable Parallel Simulation Framework for High-Performance System Design Space Exploration
par: Lin, Wei-Fen, et autres
Publié: (2026)

gem5 Co-Pilot: AI Assistant Agent for Architectural Design Space Exploration
par: Fu, Zuoming, et autres
Publié: (2025)

DiffAxE: Diffusion-driven Hardware Accelerator Generation and Design Space Exploration
par: Ghosh, Arkapravo, et autres
Publié: (2025)

EdgeMM: Multi-Core CPU with Heterogeneous AI-Extension and Activation-aware Weight Pruning for Multimodal LLMs at Edge
par: Bai, Kangbo, et autres
Publié: (2025)

HOPE: Holistic STT-RAM Architecture Exploration Framework for Future Cross-Platform Analysis
par: SeyedFaraji, Saeed, et autres
Publié: (2024)

ApproxGNN: A Pretrained GNN for Parameter Prediction in Design Space Exploration for Approximate Computing
par: Vlcek, Ondrej, et autres
Publié: (2025)

A Systematic Characterization of LLM Inference on GPUs
par: Wang, Haonan, et autres
Publié: (2025)

ADOR: A Design Exploration Framework for LLM Serving with Enhanced Latency and Throughput
par: Kim, Junsoo, et autres
Publié: (2025)

Kugelblitz: Executable, Cost-Aware Design-Space Exploration for Programmable Packet Pipelines
par: Ageev, Artem, et autres
Publié: (2023)