This paper focuses on the efficient scheduling on multicore systems of very fine-grain
networked tasks, which are the typical building block of online data-intensive applications …

Large parallel machines with hundreds of thousands of processors are becoming more
prevalent. Ensuring good load balance is critical for scaling certain classes of parallel …

The prevalence of dynamic-content web services, exemplified by search and online social
networking, has motivated an increasingly wide web-facing front end. Horizontal scaling in …

Taskflow aims to streamline the building of parallel and heterogeneous applications using a
lightweight task graph-based approach. Taskflow introduces an expressive task graph …

The Breadth-First Search (BFS) algorithm serves as the foundation for many graph-
processing applications and analytics workloads. While Graphics Processing Unit (GPU) …

FlexRR provides a scalable, efficient solution to the straggler problem for iterative machine
learning (ML). The frequent (eg, per iteration) barriers used in traditional BSP-based …

We present two novel methods to automatically learn spatio-temporal dependencies of
moving agents in complex dynamic scenes. They allow to discover temporal rules, such as …

As mobile devices evolve to be powerful and pervasive computing tools, their usage also
continues to increase rapidly. However, mobile device users frequently experience …

Work stealing has proven to be an effective method for scheduling parallel programs on
multicore computers. To achieve high performance, work stealing distributes tasks between …

Load balancing techniques (eg work stealing) are important to obtain the best performance
for distributed task scheduling systems that have multiple schedulers making scheduling …