1 citations · 1 across the 5 of their papers we have counts for
5 papers
KLAS: Using Similarity to Stitch Neural Networks for Improved Accuracy-Efficiency Tradeoffs
Debopam Sanyal, Anantharaman Iyer, Alind Khare +5
Given the wide range of deployment targets, flexible model selection is essential for optimizing performance within a given compute budget. Recent work demonstrates that stitching…
Cornserve: A Distributed Serving System for Any-to-Any Multimodal Models
Jae-Won Chung, Jeff J. Ma, Jisang Ahn +4
Any-to-Any models are an emerging class of multimodal models that accept combinations of multimodal data (e.g., text, image, video, audio) as input and generate them as output. Ser…
Cornfigurator: Automated Planning for Any-to-Any Multimodal Model Serving
Jeff J. Ma, Jae-Won Chung, Jisang Ahn +5
Any-to-Any models are an emerging class of multimodal models that accept combinations of text and multimodal data as input and generate them as output, introducing heterogeneous co…
Enabling Elastic Model Serving with MultiWorld
Myungjin Lee, Akshay Jajoo, Ramana Rao Kompella
Machine learning models have been exponentially growing in terms of their parameter size over the past few years. We are now seeing the rise of trillion-parameter models. The large…
Atomicity and Abstraction for Cross-Blockchain Interactions
Huaixi Lu, Akshay Jajoo, Kedar S. Namjoshi
A blockchain facilitates secure and atomic transactions between mutually untrusting parties on that chain. Today, there are multiple blockchains with differing interfaces and secur…