8 papers
Towards Simple Models of Complex SmartNICs
Robert Chang, Teng Jiang, Wonsup Yoon +3
Cloud vendors push ambitious in-network processing (e.g., crypto, telemetry) onto the NIC to offload servers even as link rates climb to terabit speeds. Vendors have responded with…
Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation
Joon Ha Kim, Geon-Woo Kim, Anoop Rachakonda +1
Selecting the optimal LLM inference configuration requires evaluation across hardware, serving engines, attention backends, and model architectures, since no single choice performs…
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…
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…
ConfigBot: Adaptive Resource Allocation for Robot Applications in Dynamic Environments
Rohit Dwivedula, Sadanand Modak, Aditya Akella +3
The growing use of service robots in dynamic environments requires flexible management of on-board compute resources to optimize the performance of diverse tasks such as navigation…
Reforge: Low-Latency Distributed GNN Serving with Selective Embedding Recomputation
Geon-Woo Kim, Donghyun Kim, Jeongyoon Moon +5
Graph Neural Networks (GNNs) have been widely adopted for their ability to compute expressive node representations in graph datasets. However, serving GNNs on large graphs is chall…
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…