16 citations · 18 across the 10 of their papers we have counts for
10 papers
EMA: Elastic and Performance Transparent Memory Across GPUs
Yi Xu, Tian Xia, Ion Stoica
Multi-GPU servers have become the standard building block of modern data centers, providing aggregated capacity through high-bandwidth interconnects. At the same time, workloads su…
Idleness is Relative: Exploiting Tool-Call Idle Windows for Offloading in Agentic Systems with MORI
Tian Xia, Hanchen Li, Zhifei Li +5
Modern LLM serving systems increasingly host agentic workloads, whose sessions issue tens of model invocations interleaved with tool calls, accumulating KV cache that can be reused…
SkyNomad: On Using Multi-Region Spot Instances to Minimize AI Batch Job Cost
Zhifei Li, Tian Xia, Ziming Mao +9
AI batch jobs such as model training, inference pipelines, and data analytics require substantial GPU resources and often need to finish before a deadline. Spot instances offer 3-1…
Let the Barbarians In: How AI Can Accelerate Systems Performance Research
Audrey Cheng, Shu Liu, Melissa Pan +18
Artificial Intelligence (AI) is beginning to transform the research process by automating the discovery of new solutions. This shift depends on the availability of reliable verifie…
FrontierCS: Evolving Challenges for Evolving Intelligence
Qiuyang Mang, Wenhao Chai, Zhifei Li +48
We introduce FrontierCS, a benchmark of 156 open-ended problems across diverse areas of computer science, designed and reviewed by experts, including CS PhDs and top-tier competiti…
Barbarians at the Gate: How AI is Upending Systems Research
Audrey Cheng, Shu Liu, Melissa Pan +14
Artificial Intelligence (AI) is starting to transform the research process as we know it by automating the discovery of new solutions. Given a task, the typical AI-driven approach…
SkyWalker: A Locality-Aware Cross-Region Load Balancer for LLM Inference
Tian Xia, Ziming Mao, Jamison Kerney +5
Serving Large Language Models (LLMs) efficiently in multi-region setups remains a challenge. Due to cost and GPU availability concerns, providers typically deploy LLMs in multiple…
The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks
Alejandro Cuadron, Dacheng Li, Wenjie Ma +13
Large Reasoning Models (LRMs) represent a breakthrough in AI problem-solving capabilities, but their effectiveness in interactive environments can be limited. This paper introduces…
Locality-aware Fair Scheduling in LLM Serving
Shiyi Cao, Yichuan Wang, Ziming Mao +10
Large language model (LLM) inference workload dominates a wide variety of modern AI applications, ranging from multi-turn conversation to document analysis. Balancing fairness and…
SkyServe: Serving AI Models across Regions and Clouds with Spot Instances
Ziming Mao, Tian Xia, Zhanghao Wu +6
Recent years have witnessed an explosive growth of AI models. The high cost of hosting AI services on GPUs and their demanding service requirements, make it timely and challenging…