1 citations · 1 across the 4 of their papers we have counts for
4 papers
WANSpec: Leveraging Global Compute Capacity for LLM Inference
Noah Martin, Fahad Dogar
Data centers capable of running large language models (LLMs) are spread across the globe. Some have high end GPUs for running the most advanced models (100B+ parameters), and other…
WaLLM -- Understanding Use and Engagement with a General-Purpose LLM on WhatsApp
Hiba Eltigani, Rukhshan Haroon, Asli Kocak +3
Large language model (LLM) chatbots are increasingly reaching users through messaging platforms (e.g. WhatsApp). However, these systems remain largely proprietary and opaque, while…
LLMBridge: Reducing Costs to Access LLMs in a Prompt-Centric Internet
Noah Martin, Abdullah Bin Faisal, Hiba Eltigani +3
Today's Internet infrastructure is centered around content retrieval over HTTP, with middleboxes (e.g., HTTP proxies) playing a crucial role in performance, security, and cost-effe…
Towards providing reliable job completion time predictions using PCS
Abdullah Bin Faisal, Noah Martin, Hafiz Mohsin Bashir +2
In this paper we build a case for providing job completion time predictions to cloud users, similar to the delivery date of a package or arrival time of a booked ride. Our analysis…