Scale-out programs run on multiple processes in a cluster. In scale-out systems, processes
can fail. Computations using traditional libraries such as MPI fail when any component …

We present GLB, a programming model and an associated implementation that can handle
a wide range of irregular parallel programming problems running over large-scale …

The Partitioned Global Address Space (PGAS) programming models combine shared and
distributed memory features, providing the basis for high performance and high productivity …

Swift/T is a high-level language for writing concise, deterministic scripts that compose serial
or parallel codes implemented in lower-level programming models into large-scale parallel …

An important feature of functional programs is that they are parallel by default. Implementing
an efficient parallel functional language, however, is a major challenge, in part because the …

With the rise of multicore computers, parallel applications no longer consist solely of
computational, batch workloads, but also include applications that may, for example, take …

Scalability is a key feature for big data analysis and machine learning frameworks and for
applications that need to analyze very large and real-time data available from data …

GPUs (Graphics Processing Unit) and other accelerators are nowadays commonly found in
desktop machines, mobile devices and even data centres. While these highly parallel …

Cloud computing has made the resources needed to execute large-scale in-memory
distributed computations widely available. Specialized programming models, eg …

Effective support for array-based programming has long been one of the central design
concerns of the X10 programming language. After significant research and exploration, X10 …