Maintaining a high rate of productivity, in terms of completed jobs per unit of time, in High-
Performance Computing (HPC) facilities is a cornerstone in the next generation of exascale …

Malleability allows computing facilities to adapt their workloads through resource
management systems to maximize the throughput of the facility and the efficiency of the …

Resource elasticity allows to dynamically change the resources of running jobs, which may
significantly improve the throughput on supercomputers. Elasticity requires support from …

Malleability—the ability for applications to dynamically adjust their resource allocations at
runtime—presents great potential to enhance the efficiency and resource utilization of …

In recent years, supercomputers have experienced significant advancements in
performance and have grown in size, now comprising several thousands nodes. To unlock …

Applying malleability to HPC systems can increase their productivity without degrading or
even improving the performance of running applications. This paper presents Proteo, a …

Elastic parallel applications that can change the number of processors while being executed
promise improved application and system performance, allow new classes of data and event …

Data redistribution aims to reshuffle data to optimize some objective for an algorithm. The
objective can be multi-dimensional, such as improving computational load balance or …

The current static job scheduling on supercomputers for MPI-based applications is well
known to be a limiting factor for the exploitation of a system's top performance in terms of …

With the increase of complex scientific simulations driven by workflows and heterogeneous
workload profiles, managing system resources effectively is essential for improving …