2 citations · 2 across the 8 of their papers we have counts for
8 papers
Autopoiesis: A Self-Evolving System Paradigm for LLM Serving Under Runtime Dynamics
Youhe Jiang, Ran Yan, You Peng +4
Modern Large Language Model (LLM) serving operates in highly volatile environments characterized by severe runtime dynamics, such as workload fluctuations and elastic cluster autos…
OServe: Accelerating LLM Serving via Spatial-Temporal Workload Orchestration
Youhe Jiang, Fangcheng Fu, Taiyi Wang +2
Serving Large Language Models (LLMs) can benefit immensely from parallelizing both the model and input requests across multiple devices, but incoming workloads exhibit substantial…
AutoIndexer: A Reinforcement Learning-Enhanced Index Advisor Towards Scaling Workloads
Taiyi Wang, Eiko Yoneki
Efficiently selecting indexes is fundamental to database performance optimization, particularly for systems handling large-scale analytical workloads. While deep reinforcement lear…
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach
Taiyi Wang, Liang Liang, Guang Yang +2
Learned Index Structures (LIS) have significantly advanced data management by leveraging machine learning models to optimize data indexing. However, designing these structures ofte…
ThunderServe: High-performance and Cost-efficient LLM Serving in Cloud Environments
Youhe Jiang, Fangcheng Fu, Xiaozhe Yao +4
Recent developments in large language models (LLMs) have demonstrated their remarkable proficiency in a range of tasks. Compared to in-house homogeneous GPU clusters, deploying LLM…
Navigating in High-Dimensional Search Space: A Hierarchical Bayesian Optimization Approach
Wenxuan Li, Taiyi Wang, Eiko Yoneki
Optimizing black-box functions in high-dimensional search spaces has been known to be challenging for traditional Bayesian Optimization (BO). In this paper, we introduce HiBO, a no…
Learned Graph Rewriting with Equality Saturation: A New Paradigm in Relational Query Rewrite and Beyond
George-Octavian Bărbulescu, Taiyi Wang, Zak Singh +1
Query rewrite systems perform graph substitutions using rewrite rules to generate optimal SQL query plans. Rewriting logical and physical relational query plans is proven to be an…
IA2: Leveraging Instance-Aware Index Advisor with Reinforcement Learning for Diverse Workloads
Taiyi Wang, Eiko Yoneki
This study introduces the Instance-Aware Index Advisor (IA2), a novel deep reinforcement learning (DRL)-based approach for optimizing index selection in databases facing large acti…