Cover Image

AIRES: Accelerating Out-of-Core GCNs via Algorithm-System Co-Design

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jayakody, Shakya, Zhao, Youpeng, Wang, Jun
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching
by: Zhao, Youpeng, et al.
Published: (2024)

GhostServe: A Lightweight Checkpointing System in the Shadow for Fault-Tolerant LLM Serving
by: Jayakody, Shakya, et al.
Published: (2026)

Thinking in Groups: Permutation Tests Reveal Near-Out-of-Distribution
by: Jayawardana, Yasith, et al.
Published: (2024)

PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs
by: Ji, Shengwei, et al.
Published: (2024)

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

Laplacian-LoRA: Delaying Oversmoothing in Deep GCNs via Spectral Low-Rank Adaptation
by: Alisetti, Sai Vamsi
Published: (2026)

Merino: Entropy-driven Design for Generative Language Models on IoT Devices
by: Zhao, Youpeng, et al.
Published: (2024)

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

GCN-TULHOR: Trajectory-User Linking Leveraging GCNs and Higher-Order Spatial Representations
by: Tran, Khoa, et al.
Published: (2025)

Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs
by: Fiorini, Stefano, et al.
Published: (2023)

MC$^2$A: Enabling Algorithm-Hardware Co-Design for Efficient Markov Chain Monte Carlo Acceleration
by: Zhao, Shirui, et al.
Published: (2025)

Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions
by: Reichmann, Luca, et al.
Published: (2024)

RsGCN: Subgraph-Based Rescaling Enhances Generalization of GCNs for Solving Traveling Salesman Problems
by: Huang, Junquan, et al.
Published: (2025)

Few-shot Multispectral Segmentation with Representations Generated by Reinforcement Learning
by: Jayakody, Dilith, et al.
Published: (2023)

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

AccLLM: Accelerating Long-Context LLM Inference Via Algorithm-Hardware Co-Design
by: Liang, Yanbiao, et al.
Published: (2025)

Reducing Latency of LLM Search Agent via Speculation-based Algorithm-System Co-Design
by: Huang, Zixiao, et al.
Published: (2025)

FlexQ: Efficient Post-training INT6 Quantization for LLM Serving via Algorithm-System Co-Design
by: Zhang, Hao, et al.
Published: (2025)

SentimentLens: Reconciling Sentiment and Ratings via Dual-Modality in the Hospitality Sector
by: Jayakody, Dineth, et al.
Published: (2026)

Scalable Generative Game Engine: Breaking the Resolution Wall via Hardware-Algorithm Co-Design
by: Zeng, Wei, et al.
Published: (2026)

COBRA: Algorithm-Architecture Co-optimized Binary Transformer Accelerator for Edge Inference
by: Qiao, Ye, et al.
Published: (2025)

A Comparative Analysis of Machine Learning Models for DDoS Detection in IoT Networks
by: Shakya, Sushil, et al.
Published: (2024)

CuDA2: An approach for Incorporating Traitor Agents into Cooperative Multi-Agent Systems
by: Chen, Zhen, et al.
Published: (2024)

LMSeg: Unleashing the Power of Large-Scale Models for Open-Vocabulary Semantic Segmentation
by: Tang, Huadong, et al.
Published: (2024)

Towards Understanding the Role of Sharpness-Aware Minimization Algorithms for Out-of-Distribution Generalization
by: Schapiro, Samuel, et al.
Published: (2024)

Next Word Suggestion using Graph Neural Network
by: Magar, Abisha Thapa, et al.
Published: (2025)

Co-Designing Binarized Transformer and Hardware Accelerator for Efficient End-to-End Edge Deployment
by: Ji, Yuhao, et al.
Published: (2024)

RAGPulse: An Open-Source RAG Workload Trace to Optimize RAG Serving Systems
by: Wang, Zhengchao, et al.
Published: (2025)

CoreSPECT: Enhancing Clustering Algorithms via an Interplay of Density and Geometry
by: Mukherjee, Chandra Sekhar, et al.
Published: (2025)

Accelerated Bayesian Optimal Experimental Design via Conditional Density Estimation and Informative Data
by: Huang, Miao, et al.
Published: (2025)

DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training
by: Liu, Renjie, et al.
Published: (2024)

MultiSense-Pneumo: A Multimodal Learning Framework for Pneumonia Screening in Resource-Constrained Settings
by: Jayakody, Dineth, et al.
Published: (2026)

Accelerating Benchmarking of Functional Connectivity Modeling via Structure-aware Core-set Selection
by: Zhan, Ling, et al.
Published: (2026)

Privacy-Preserving EHR Data Transformation via Geometric Operators: A Human-AI Co-Design Technical Report
by: Wang, Maolin, et al.
Published: (2026)

Causal Negative Sampling via Diffusion Model for Out-of-Distribution Recommendation
by: Zhao, Chu, et al.
Published: (2025)

AuToMATo: An Out-Of-The-Box Persistence-Based Clustering Algorithm
by: Huber, Marius, et al.
Published: (2024)

Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels
by: Ahmad, Tamim El, et al.
Published: (2023)

Toward Highly Efficient and Private Submodular Maximization via Matrix-Based Acceleration
by: Liu, Boyu, et al.
Published: (2023)

FedCAP: Robust Federated Learning via Customized Aggregation and Personalization
by: Li, Youpeng, et al.
Published: (2024)

Algorithm and Hardware Co-Design for Efficient Complex-Valued Uncertainty Estimation
by: Zhang, Zehuan, et al.
Published: (2026)