1 citations · 1 across the 5 of their papers we have counts for
5 papers
Towards Load-Aware Prefill Deflection for Disaggregated LLM Serving
Shrikara Arun, Anjaly Parayil, Srikant Bharadwaj +2
Disaggregated LLM serving runs prefill and decode on separate GPU pools to keep the two phases from interfering. In practice, this creates a new asymmetry: under bursty, heavy-tail…
Serving Heterogeneous LoRA Adapters in Distributed LLM Inference Systems
Shashwat Jaiswal, Shrikara Arun, Anjaly Parayil +8
Low-Rank Adaptation (LoRA) has become the de facto method for parameter-efficient fine-tuning of large language models (LLMs), enabling rapid adaptation to diverse domains. In prod…
LLMs for Generation of Architectural Components: An Exploratory Empirical Study in the Serverless World
Shrikara Arun, Meghana Tedla, Karthik Vaidhyanathan
Recently, the exponential growth in capability and pervasiveness of Large Language Models (LLMs) has led to significant work done in the field of code generation. However, this gen…
Engineering LLM Powered Multi-agent Framework for Autonomous CloudOps
Kannan Parthasarathy, Karthik Vaidhyanathan, Rudra Dhar +8
Cloud Operations (CloudOps) is a rapidly growing field focused on the automated management and optimization of cloud infrastructure which is essential for organizations navigating…
Towards Architecting Sustainable MLOps: A Self-Adaptation Approach
Hiya Bhatt, Shrikara Arun, Adyansh Kakran +1
In today's dynamic technological landscape, sustainability has emerged as a pivotal concern, especially with respect to architecting Machine Learning enabled Systems (MLS). Many ML…