We present Grappa, a modern take on software distributed shared memory (DSM) for in-
memory data-intensive applications. Grappa enables users to program a cluster as if it were …

Irregular and dynamic parallel applications pose significant challenges to achieving
scalable performance on large-scale multicore clusters. These applications often require …

Datacenter operators today strive to support microsecond-latency applications while also
using their limited CPU resources as efficiently as possible. To achieve this, several recent …

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 …

This paper presents Personal Data Lake, a unified storage facility for storing, analyzing and
querying personal data. A data lake stores data regardless of format and thus provides an …

We believe that a market-based resource allocation will be effective in a cloud computing
environment where resources are virtualized and delivered to users as services. We …

We propose a novel method to estimate and track the 3D line of sight of a person based on
3D computer vision techniques. Most of the existing nonintrusive gaze tracking methods …

On shared-memory systems, Cilk-style work-stealing has been used to effectively parallelize
irregular task-graph based applications such as Unbalanced Tree Search (UTS). There are …

In computational Grids, performance‐hungry applications need to simultaneously tap the
computational power of multiple, dynamically available sites. The crux of designing Grid …

Increasingly heterogeneous and hierarchical parallel architectures are now mainstream,
however, most of the traditional programming models are lowlevel and explicit, limiting …