In recent years, significant advances have been made in the design and evaluation of
balanced (hyper) graph partitioning algorithms. We survey trends of the past decade in …

Algorithmic and data-driven decisions and recommendations are commonly used in high-
stakes decision-making settings such as criminal justice, medicine, and public policy. We …

Dependence between iterations in sparse computations causes inefficient use of memory
and computation resources. This paper proposes sparse fusion, a technique that generates …

When scheduling a directed acyclic graph (DAG) of tasks with communication costs on
computational platforms, a good trade-off between load balance and data locality is …

Early but promising results in quantum computing have been enabled by the concurrent
development of quan-tum algorithms, devices, and materials. Classical simulation of …

Serverless computing has revolutionized application deployment, obviating traditional
infrastructure management and dynamically allocating resources on demand. A significant …

A directed acyclic hypergraph is a generalized concept of a directed acyclic graph, where
each hyperedge can contain an arbitrary number of tails and heads. Directed hypergraphs …

Deep learning services based on cloud computing have deficiencies in latency, privacy, etc.
To meet the requirements of low latency, researchers have begun to consider the …

This work addresses the NP-Hard problem of acyclic directed acyclic graph (DAG)
partitioning problem. The acyclic partitioning problem is defined as partitioning the vertex set …

Scaling up the capacity of deep neural networks (DNN) is one of the effective approaches to
improve the model quality for several different DNN-based applications, making the DNN …