Task-based programming models for shared memory—such as Cilk Plus and OpenMP 3—
are well established and documented. However, with the increase in parallel, many-core …

Through the huge growth of heavy computing applications which require a high level of
performance, it is observed that the interest of monitoring operating system performance has …

Technology enhancements and the growing breadth of application workflows running on
high-performance computing (HPC) platforms drive the development of new data services …

The Distributed Asynchronous Object Storage (DAOS) is an open source scale-out storage
system that is designed from the ground up to support Storage Class Memory (SCM) and …

Across embedded, mobile, enterprise, and high performance computing systems, computer
architectures are becoming more heterogeneous and complex. This complexity is causing a …

We present GekkoFS, a temporary, highly-scalable burst buffer file system which has been
specifically optimized for new access patterns of data-intensive High-Performance …

Scientific applications at exascale generate and analyze massive amounts of data. A critical
requirement of these applications is the capability to access and manage this data efficiently …

Many scientific fields increasingly use high-performance computing (HPC) to process and
analyze massive amounts of experimental data while storage systems in today's HPC …

Storage backends of parallel compute clusters are still based mostly on magnetic disks,
while newer and faster storage technologies such as flash-based SSDs or non-volatile …

With the increasing demand for distributed big data analytics and data-intensive programs
which contribute to large volumes of packets among processing elements (PEs) and …