activity
20222026
most citedNo Provisioned Concurrency: Fast RDMA-codesigned Remote Fork for Serverless Computing

10 citations · 23 across the 16 of their papers we have counts for

collaborators

17 papers

cs.DC2026

SMetric: Rethink LLM Scheduling for Serving Agents with Balanced Session-centric Scheduling

Jiahao Wang, Kaizhan Lin, Kaixi Zhang +7

LLM scheduling is critical to serving, yet how well existing designs fit agentic serving--where agents, not humans, issue the requests--remains unclear. Agents shift the workload i…

cs.DC2026

CoAgent: Concurrency Control for Multi-Agent Systems

Hongtao Lyu, Dingyan Zhang, Mingyu Wu +2

Multi-agent LLM systems -- coding agents, devops agents, document agents -- now routinely run several agents in parallel against the same git tree, Kubernetes cluster, or document.…

cs.DB2026

Efficient K-generalizable Learned Search

Yifan Peng, Jiafei Fan, Xingda Wei +7

Learned top-K search improves the accuracy-latency trade-off of graph-based vector search, but existing methods target a fixed K. Serving real-world workloads with various K values…

cs.DC2026

Simple is Better: Multiplication May Be All You Need for LLM Request Scheduling

Dingyan Zhang, Jinbo Han, Kaixi Zhang +6

High-quality LLM request scheduling requires meeting two key objectives: ensuring the routed instance has KVCache to accelerate request execution, and ensuring that the workload is…

cs.DC2025

Fast LLM Post-training via Decoupled and Fastest-of-N Speculation

Rongxin Cheng, Kai Zhou, Xingda Wei +8

Rollout dominates the training time in large language model (LLM) post-training, where the trained model is used to generate tokens given a batch of prompts. This work, SpecActor,…

cs.DC2025

KVCache Cache in the Wild: Characterizing and Optimizing KVCache Cache at a Large Cloud Provider

Jiahao Wang, Jinbo Han, Xingda Wei +6

Serving large language models (LLMs) is important for cloud providers, and caching intermediate results (KV$) after processing each request substantially improves serving throughp…

cs.DC2025

DiFache: Efficient and Scalable Caching on Disaggregated Memory using Decentralized Coherence

Hanze Zhang, Kaiming Wang, Rong Chen +2

The disaggregated memory (DM) architecture offers high resource elasticity at the cost of data access performance. While caching frequently accessed data in compute nodes (CNs) red…

cs.DC2025

DecLock: A Case of Decoupled Locking for Disaggregated Memory

Hanze Zhang, Ke Cheng, Rong Chen +2

This paper reveals that locking can significantly degrade the performance of applications on disaggregated memory (DM), sometimes by several orders of magnitude, due to contention…

cs.DC2024★ 1 cited

KunServe: Parameter-centric Memory Management for Efficient Memory Overloading Handling in LLM Serving

Rongxin Cheng, Yuxin Lai, Xingda Wei +2

Serving LLMs with a cluster of GPUs is common nowadays, where the serving system must meet strict latency SLOs required by applications. However, the stateful nature of LLM serving…

cs.DC2024

BLITZSCALE: Fast and Live Large Model Autoscaling with O(1) Host Caching

Dingyan Zhang, Haotian Wang, Yang Liu +4

Model autoscaling is the key mechanism to achieve serverless model-as-a-service, but it faces a fundamental trade-off between scaling speed and storage/memory usage to cache parame…

cs.DC2024★ 2 cited

Characterizing the Dilemma of Performance and Index Size in Billion-Scale Vector Search and Breaking It with Second-Tier Memory

Rongxin Cheng, Yifan Peng, Xingda Wei +4

Vector searches on large-scale datasets are critical to modern online services like web search and RAG, which necessity storing the datasets and their index on the secondary storag…

cs.DC2024

PhoenixOS: Concurrent OS-level GPU Checkpoint and Restore with Validated Speculation

Xingda Wei, Zhuobin Huang, Tianle Sun +5

PHOENIXOS (PHOS) is the first OS service that can concurrently checkpoint and restore (C/R) GPU processes--a fundamental capability for critical tasks such as fault tolerance, proc…

cs.OS2024★ 1 cited

Characterizing Network Requirements for GPU API Remoting in AI Applications

Tianxia Wang, Zhuofu Chen, Xingda Wei +3

GPU remoting is a promising technique for supporting AI applications. Networking plays a key role in enabling remoting. However, for efficient remoting, the network requirements in…

cs.DB2023★ 2 cited

Transactional Indexes on (RDMA or CXL-based) Disaggregated Memory with Repairable Transaction

Xingda Wei, Haotian Wang, Tianxia Wang +4

The failure atomic and isolated execution of clients operations is a default requirement for a system that serve multiple loosely coupled clients at a server. However, disaggregate…

cs.DC2022★ 5 cited

Characterizing Off-path SmartNIC for Accelerating Distributed Systems

Xingda Wei, Rongxin Cheng, Yuhan Yang +2

SmartNICs have recently emerged as an appealing device for accelerating distributed systems. However, there has not been a comprehensive characterization of SmartNICs, and existing…

cs.OS2022★ 10 cited

No Provisioned Concurrency: Fast RDMA-codesigned Remote Fork for Serverless Computing

Xingda Wei, Fangming Lu, Tianxia Wang +4

Serverless platforms essentially face a tradeoff between container startup time and provisioned concurrency (i.e., cached instances), which is further exaggerated by the frequent n…

cs.NI2022★ 2 cited

KRCORE: a microsecond-scale RDMA control plane for elastic computing

Xingda Wei, Fangming Lu, Rong Chen +1

We present KRCORE, an RDMA library with a microsecond-scale control plane on commodity RDMA hardware for elastic computing. KRCORE can establish a full-fledged RDMA connection with…