Atomic structure prediction and associated property calculations are the bedrock of chemical
physics. Since high-fidelity ab initio modeling techniques for computing the structure and …

The growing memory demands of modern applications have driven the adoption of far
memory technologies in data centers to provide cost-effective, high-capacity memory …

In-Memory Graph Databases for Web-Scale Data Page 1 24 COMPUTER PUBLISHED BY THE
IEEE COMPUTER SOCIETY 0018-9162/15/$31.00 © 2015 IEEE COVER FEATURE BIG DATA …

This paper introduces Itoyori, a task-parallel runtime system designed to tackle the
challenge of scaling task parallelism (more specifically, nested fork-join parallelism) beyond …

We investigated a software cache for PGAS PUT and GET operations. The cache is
implemented as a software write-back cache with dirty bits, local memory consistency …

The unprecedented amount of data that needs to be processed in emerging data analytics
applications poses novel challenges to industry and academia. Scalability and high …

The need for coupling high performance with productivity is steering the recent evolution of
the C++ language where low-level aspects of parallel and distributed computing are now …

Graph-parallel computation has become a crucial component in emerging applications of
web search, data analytics and machine learning. In practice, most graphs derived from real …

While the term “Big Data” is open to varying interpretation, it is quite clear that the Volume,
Velocity, and Variety (3Vs) of data have impacted every aspect of computational science and …

Distributed systems incorporate GPUs because they provide massive parallelism in an
energy-efficient manner. Unfortunately, existing programming models make it difficult to …