1 citations · 1 across the 4 of their papers we have counts for
5 papers
Online Batching with Lookahead: Adversarial Limits and Stochastic Gains
Dimitris Christou, Jiayi Chen, Nihal Sharma +3
Modern inference systems rely on batching to exploit parallel execution and amortize serial execution overheads, but batching creates a fundamental online scheduling tradeoff: serv…
A Joint Learning Approach to Hardware Caching and Prefetching
Samuel Yuan, Divyanshu Saxena, Jiayi Chen +2
Several learned policies have been proposed to replace heuristics for scheduling, caching, and other system components in modern systems. By leveraging diverse features, learning f…
Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation
Wenzhuo Qian, Hailiang Zhao, Jiayi Chen +7
Microservice architectures enable scalable cloud-native applications; however, the distributed nature of these systems complicates the maintenance of strict Service Level Objective…
Accelerating Distributed Deep Learning using Lossless Homomorphic Compression
Haoyu Li, Yuchen Xu, Jiayi Chen +5
As deep neural networks (DNNs) grow in complexity and size, the resultant increase in communication overhead during distributed training has become a significant bottleneck, challe…
On a Foundation Model for Operating Systems
Divyanshu Saxena, Nihal Sharma, Donghyun Kim +15
This paper lays down the research agenda for a domain-specific foundation model for operating systems (OSes). Our case for a foundation model revolves around the observations that…