Model parallelism is conventionally viewed as a method to scale a single large deep
learning model beyond the memory limits of a single device. In this paper, we demonstrate …

We propose cloud oracles, an alternative to machine learning for online optimization of
cloud configurations. Our cloud oracle approach guarantees complete accuracy and …

Resource allocation is fundamental for cloud systems to ensure efficient resource sharing
among tenants. However, the scale of such optimization problems has outgrown the …

Cloud object stores offer vastly different price points for object storage as a function of
workload and geography. Poor object placement can thus lead to significant cost overheads …

Navigating the intricacies of data management in the era of Large Language Models (LLMs)
presents both challenges and opportunities for database and data management …

Аннотация Введение: идентификация эффективных расписаний выполнения в
конвейерных системах наборов однотипных заданий предусматривает поиск лучших …

Abstract Large Language Models (LLMs) have shown remarkable capabilities in a variety of
tasks, including chatting, programming, and searching. However, the high costs of LLMs are …

Resource management is ubiquitous in networked systems and ensures the effective
sharing of resources among various demands. Examples include traffic engineering, cluster …

As the scale of both computing and data grows, developers are increasingly building
distributed statefulsystems in the cloud. However, these systems are challenging to build at …