Scalable Distributed Vector Search via Accuracy Preserving Index Construction

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xu, Yuming, Zhang, Qianxi, Chen, Qi, Lu, Baotong, Li, Menghao, Adams, Philip, Li, Mingqin, Li, Zengzhong, Liu, Jing, Li, Cheng, Yang, Fan
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Towards Efficient and Scalable Distributed Vector Search with RDMA
di: Zhi, Xiangyu, et al.
Pubblicazione: (2025)

DISTRIBUTEDANN: Efficient Scaling of a Single DISKANN Graph Across Thousands of Computers
di: Adams, Philip, et al.
Pubblicazione: (2025)

DEX: Scalable Range Indexing on Disaggregated Memory [Extended Version]
di: Lu, Baotong, et al.
Pubblicazione: (2024)

Scalable Graph Indexing using GPUs for Approximate Nearest Neighbor Search
di: Li, Zhonggen, et al.
Pubblicazione: (2025)

Self-Evolving Distributed Memory Architecture for Scalable AI Systems
di: Li, Zixuan, et al.
Pubblicazione: (2026)

DIMS: Distributed Index for Similarity Search in Metric Spaces
di: Zhu, Yifan, et al.
Pubblicazione: (2024)

PilotANN: Memory-Bounded GPU Acceleration for Vector Search
di: Gui, Yuntao, et al.
Pubblicazione: (2025)

SDSL-Solver: Scalable Distributed Sparse Linear Solvers for Large-Scale Interior Point Methods
di: Yang, Shaofeng, et al.
Pubblicazione: (2026)

SOLANET: Distributed Neighbor Graph Construction on GPU-Accelerated Systems
di: Iwabuchi, Keita, et al.
Pubblicazione: (2026)

EXaCTz: Guaranteed Extremum Graph and Contour Tree Preservation for Distributed- and GPU-Parallel Lossy Compression
di: Li, Yuxiao, et al.
Pubblicazione: (2026)

Distributed Speculative Execution for Resilient Cloud Applications
di: Li, Tianyu, et al.
Pubblicazione: (2024)

WindVE: Collaborative CPU-NPU Vector Embedding
di: Huang, Jinqi, et al.
Pubblicazione: (2025)

SQUASH: Serverless and Distributed Quantization-based Attributed Vector Similarity Search
di: Oakley, Joe, et al.
Pubblicazione: (2025)

Communication-Efficient Distributed Learning via Sparse and Adaptive Stochastic Gradient
di: Deng, Xiaoge, et al.
Pubblicazione: (2021)

Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda
di: Xu, Minxian, et al.
Pubblicazione: (2026)

Experiences Building Enterprise-Level Privacy-Preserving Federated Learning to Power AI for Science
di: Li, Zilinghan, et al.
Pubblicazione: (2025)

Lagom: Unleashing the Power of Communication and Computation Overlapping for Distributed LLM Training
di: Xu, Guanbin, et al.
Pubblicazione: (2026)

GRNND: A GPU-Parallel Relative NN-Descent Algorithm for Efficient Approximate Nearest Neighbor Graph Construction
di: Li, Xiang, et al.
Pubblicazione: (2025)

DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
di: Wang, Zhixin, et al.
Pubblicazione: (2025)

NAVIS: Concurrent Search and Update with Low Position-Seeking Overhead in On-SSD Graph-Based Vector Search
di: Song, Jaeyong, et al.
Pubblicazione: (2026)

On the Performance and Memory Footprint of Distributed Training: An Empirical Study on Transformers
di: Lu, Zhengxian, et al.
Pubblicazione: (2024)

Pilotfish: Distributed Execution for Scalable Blockchains
di: Kniep, Quentin, et al.
Pubblicazione: (2024)

Half a Century of Distributed Byzantine Fault-Tolerant Consensus: Design Principles and Evolutionary Pathways
di: Wu, Huanyu, et al.
Pubblicazione: (2024)

StableShard: Stable and Scalable Blockchain Sharding with High Concurrency via Collaborative Committees
di: Li, Mingzhe, et al.
Pubblicazione: (2024)

SIVF: GPU-Resident IVF Index for Streaming Vector Search
di: Zhao, Dongfang
Pubblicazione: (2026)

Towards the Distributed Large-scale k-NN Graph Construction by Graph Merge
di: Zhang, Cheng, et al.
Pubblicazione: (2025)

Scalable Analysis of Urban Scaling Laws: Leveraging Cloud Computing to Analyze 21,280 Global Cities
di: Li, Zhenhui, et al.
Pubblicazione: (2024)

Fantasy: Efficient Large-scale Vector Search on GPU Clusters with GPUDirect Async
di: Liu, Yi, et al.
Pubblicazione: (2025)

AnchorTP: Resilient LLM Inference with State-Preserving Elastic Tensor Parallelism
di: Xu, Wendong, et al.
Pubblicazione: (2025)

FuxiShuffle: An Adaptive and Resilient Shuffle Service for Distributed Data Processing on Alibaba Cloud
di: Lin, Yuhao, et al.
Pubblicazione: (2026)

ParaGAN: A Scalable Distributed Training Framework for Generative Adversarial Networks
di: Shi, Ziji, et al.
Pubblicazione: (2024)

Biased Compression in Gradient Coding for Distributed Learning
di: Li, Chengxi, et al.
Pubblicazione: (2026)

UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving
di: Li, Yifei, et al.
Pubblicazione: (2024)

Towards Scalable GPU-Accelerated SNN Training via Temporal Fusion
di: Li, Yanchen, et al.
Pubblicazione: (2024)

Accuracy Is Speed: Towards Long-Context-Aware Routing for Distributed LLM Serving
di: Yoshimura, Takeshi, et al.
Pubblicazione: (2026)

Privacy-Preserving Distributed Maximum Consensus Without Accuracy Loss
di: Yu, Wenrui, et al.
Pubblicazione: (2024)

Distributed Bilevel Optimization with Dual Pruning for Resource-limited Clients
di: Li, Mingyi, et al.
Pubblicazione: (2025)

Characterizing the Dilemma of Performance and Index Size in Billion-Scale Vector Search and Breaking It with Second-Tier Memory
di: Cheng, Rongxin, et al.
Pubblicazione: (2024)

Preserving Near-Optimal Gradient Sparsification Cost for Scalable Distributed Deep Learning
di: Yoon, Daegun, et al.
Pubblicazione: (2024)

Black Hole Search: Dynamics, Distribution, and Emergence
di: Kaur, Tanvir, et al.
Pubblicazione: (2026)