1 citations · 2 across the 7 of their papers we have counts for
9 papers
Vulcan: Instance-specialized, Verifiable Systems Heuristics Through LLM-driven Search
Rohit Dwivedula, Divyanshu Saxena, Sujay Yadalam +3
Systems resource management tasks rely primarily on hand-designed heuristics. However, growing hardware heterogeneity and workload diversity require heuristics specialized to parti…
Continuous Benchmark Generation for Evaluating Enterprise-scale LLM Agents
Divyanshu Saxena, Rishikesh Maurya, Xiaoxuan Ou +7
The rapid adoption of AI agents across domains has made systematic evaluation crucial for ensuring their usefulness and successful production deployment. Evaluation of AI agents ty…
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…
Man-Made Heuristics Are Dead. Long Live Code Generators!
Rohit Dwivedula, Divyanshu Saxena, Aditya Akella +2
Policy design for various systems controllers has conventionally been a manual process, with domain experts carefully tailoring heuristics for the specific instance in which the po…
Fast Userspace Networking for the Rest of Us
Alireza Sanaee, Vahab Jabrayilov, Ilias Marinos +5
After a decade of research in userspace network stacks, why do new solutions remain inaccessible to most developers? We argue that this is because they ignored (1) the hardware con…
Canopy: Property-Driven Learning for Congestion Control
Chenxi Yang, Divyanshu Saxena, Rohit Dwivedula +3
Learning-based congestion controllers offer better adaptability compared to traditional heuristics. However, the unreliability of learning techniques can cause learning-based contr…
CONGO: Compressive Online Gradient Optimization
Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena +3
We address the challenge of zeroth-order online convex optimization where the objective function's gradient exhibits sparsity, indicating that only a small number of dimensions pos…
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…
Dirigo: Self-scaling Stateful Actors For Serverless Real-time Data Processing
Le Xu, Divyanshu Saxena, Neeraja J. Yadwadkar +2
We propose Dirigo, a distributed stream processing service built atop virtual actors. Dirigo achieves both a high level of resource efficiency and performance isolation driven by u…