This work introduces Mashup, a novel strategy to leverage serverless computing model for
executing scientific workflows in a hybrid fashion by taking advantage of both the traditional …

HPC applications are increasingly being designed as dynamic workflows for the ease of
development and scaling. This work demonstrates how the serverless computing model can …

Scientific research and development campaigns are materialized by workflows of
applications executing on high-performance computing (HPC) systems. These applications …

Modern-era high performance computing (HPC) systems are providing multiple levels of
memory and storage layers to bridge the performance gap between fast memory and slow …

Modern scientific applications read and write massive amounts of data through simulations,
observations, and analysis. These applications spend the majority of their runtime in …

System administrators set default storage-system configuration parameters with the goal of
providing high per-formance for their system's I/O workloads. However, this gener-alized …

Abstract Modern High-Performance Computing (HPC) systems are adding extra layers to the
memory and storage hierarchy, named deep memory and storage hierarchy (DMSH), to …

In the era of data-intensive computing, accessing data with a high-throughput and low-
latency is more imperative than ever. Data prefetching is a well-known technique for hiding …

Task-based programming models have enabled the optimized execution of the computation
workloads of applications. These programming models can take advantage of large-scale …

The combination of ever-growing scientific datasets and distributed workflow complexity
creates I/O performance bottlenecks due to data volume, velocity, and variety. Although the …