2 citations · 3 across the 12 of their papers we have counts for
13 papers
KREX: Concurrent Kernel Benchmarking on Shared GPUs via Region-Granular Exclusivity
Tianyu Feng, Haoxuan Yu, Tianyuan Wu +8
LLM agents automate GPU kernel optimization by repeatedly composing candidates and measuring their duration on real GPUs. Existing systems preserve measurement fidelity by reservin…
From LLM Inference to Agentic Workloads: Characterization and Implications for Serving Systems
Chaokun Chang, Yukun Zhou, Kaihua Fu +10
Agentic applications are shifting AI serving from isolated model inference to long-running workloads in which LLMs coordinate tools, environments, and persistent state. However, th…
ServerlessT2I: Efficient Text-to-Image Workflow Serving on a Serverless Platform
Xiaoxiao Jiang, Suyi Li, Sheng Yao +5
Text-to-image (T2I) workflows are increasingly deployed on serverless platforms because users often compose customized workflows and invoke them intermittently. Existing platforms…
Gleam: Adaptive Network-Efficient CUDA API Remoting for Cross-Device GPU Sharing over LANs
Zhihao Xu, Hao Zhong, Zeting Zhou +9
This paper aims to enable computation- and communication-efficient GPU sharing across devices within local area networks (LANs), facilitating ubiquitous AI inference on heterogeneo…
Benchmarking Confidential GPU Inference on NVIDIA H100 under Intel TDX
Wei Wang, Abdul Hyee Waqas, Burns Smith
Confidential computing is becoming a practical deployment requirement for AI inference workloads that process sensitive inputs or protect proprietary model assets. However, the per…
DisagFusion: Asynchronous Pipeline Parallelism and Elastic Scheduling for Disaggregated Diffusion Serving
Hantian Zha, Teng Ma, Yang Yong +7
Diffusion-based generation is increasingly powering production content pipelines; however, deploying these models at scale remains a significant challenge. Model weights frequently…
Polars inside Intel SGX2 Enclaves: An Empirical Study of Confidential Analytical Query Processing
Wei Wang, Burns Smith, Kenny Leftin
Trusted Execution Environments (TEEs) have renewed interest in confidential analytics, but most prior evaluations focus on SQL database engines or earlier SGX generations. This pap…
C2CServe: Leveraging NVLink-C2C for Elastic Serverless LLM Serving on MIG
Shutian Luo, Ali Zafar Sadiq, Rui Yang +4
Modern LLM serving is increasingly serverless in shape: large model catalogs, long-tail invocations, and multi-tenant demand. Existing GPU serving systems face a tradeoff: dedicate…
InstGenIE: Generative Image Editing Made Efficient with Mask-aware Caching and Scheduling
Xiaoxiao Jiang, Suyi Li, Lingyun Yang +12
Generative image editing using diffusion models has become a prevalent application in today's AI cloud services. In production environments, image editing typically involves a mask…
Adaptra: Straggler-Resilient Hybrid-Parallel Training with Pipeline Adaptation
Tianyuan Wu, Lunxi Cao, Hanfeng Lu +8
Training large Deep Neural Network (DNN) models at scale often encounters straggler issues, mostly in communications due to network congestion, RNIC/switch defects, or topological…
FALCON: Pinpointing and Mitigating Stragglers for Large-Scale Hybrid-Parallel Training
Tianyuan Wu, Wei Wang, Yinghao Yu +7
Fail-slows, or stragglers, are common but largely unheeded problems in large-scale hybrid-parallel training that spans thousands of GPU servers and runs for weeks to months. Yet, t…
SwiftDiffusion: Efficient Diffusion Model Serving with Add-on Modules
Suyi Li, Lingyun Yang, Xiaoxiao Jiang +12
Text-to-image (T2I) generation using diffusion models has become a blockbuster service in today's AI cloud. A production T2I service typically involves a serving workflow where a b…
CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference
Suyi Li, Hanfeng Lu, Tianyuan Wu +6
Pre-trained large language models (LLMs) often need specialization for domain-specific tasks. Low-Rank Adaptation (LoRA) is a popular approach that adapts a base model to multiple…