20 citations · 20 across the 4 of their papers we have counts for
6 papers
Benchmarking LLM Serving Systems for Agentic AI Workloads with XPerf
Michael Wang, Yikang Yue, Shaobo Li +3
We present XPerf, a benchmarking framework that load-tests LLM serving systems with diverse agentic AI workloads. It provides detailed profiling of the serving system and hardware,…
RAGPerf: An End-to-End Benchmarking Framework for Retrieval-Augmented Generation Systems
Shaobo Li, Yirui Zhou, Yuan Xu +5
We present the design and implementation of a RAG-based AI system benchmarking (RAGPerf) framework for characterizing the system behaviors of RAG pipelines. To facilitate detailed…
Cost-Efficient LLM Training with Lifetime-Aware Tensor Offloading via GPUDirect Storage
Ziqi Yuan, Haoyang Zhang, Yirui Eric Zhou +4
We present the design and implementation of a new lifetime-aware tensor offloading framework for GPU memory expansion using low-cost PCIe-based solid-state drives (SSDs). Our frame…
SkyByte: Architecting an Efficient Memory-Semantic CXL-based SSD with OS and Hardware Co-design
Haoyang Zhang, Yuqi Xue, Yirui Eric Zhou +2
The CXL-based solid-state drive (CXL-SSD) provides a promising approach towards scaling the main memory capacity at low cost. However, the CXL-SSD faces performance challenges due…
ByteFS: System Support for (CXL-based) Memory-Semantic Solid-State Drives
Shaobo Li, Yirui Eric Zhou, Hao Ren +1
Unlike non-volatile memory that resides on the processor memory bus, memory-semantic solid-state drives (SSDs) support both byte and block access granularity via PCIe or CXL interc…
G10: Enabling An Efficient Unified GPU Memory and Storage Architecture with Smart Tensor Migrations
Haoyang Zhang, Yirui Eric Zhou, Yuqi Xue +2
To break the GPU memory wall for scaling deep learning workloads, a variety of architecture and system techniques have been proposed recently. Their typical approaches include memo…