Cloud computing is a modern paradigm to provide services through the Internet. Load
balancing is a key aspect of cloud computing and avoids the situation in which some nodes …

Resource management in a cloud environment is a hard problem, due to: the scale of
modern data centers; the heterogeneity of resource types and their interdependencies; the …

The rise of large language models (LLMs) has enabled LLM-based applications (aka AI
agents or co-pilots), a new software paradigm that combines the strength of LLM and …

Deep learning (DL) training jobs bring some unique challenges to existing cluster
managers, such as unpredictable training times, an all-or-nothing execution model, and …

We propose a novel coding theoretic framework for mitigating stragglers in distributed
learning. We show how carefully replicating data blocks and coding across gradients can …

We consider a large-scale matrix multiplication problem where the computation is carried
out using a distributed system with a master node and multiple worker nodes, where each …

Codes are widely used in many engineering applications to offer robustness against noise.
In large-scale systems, there are several types of noise that can affect the performance of …

Big data has become an important issue for a large number of research areas such as data
mining, machine learning, computational intelligence, information fusion, the semantic Web …

Serverless computing is poised to fulfill the long-held promise of transparent elasticity and
millisecond-level pricing. To achieve this goal, service providers impose a finegrained …

We consider the problem of massive matrix multiplication, which underlies many data
analytic applications, in a large-scale distributed system comprising a group of worker …