The growth in the number of computational resources used by high-performance computing
(HPC) systems leads to an increase in failure rates. Fault-tolerant techniques will become …

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 …

Process malleability has proved to have a highly positive impact on the resource utilization
and global productivity in data centers compared with the conventional static resource …

Traditionally, on-demand, rigid, and malleable applications have been scheduled and
executed on separate systems. The ever-growing workload demands and rapidly …

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

The evolution of parallel architectures points to dynamic environments where the number of
available resources or configurations may vary during the execution of applications. This …

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

Adaptive workloads can change on–the–fly the configuration of their jobs, in terms of
number of processes. To carry out these job reconfigurations, we have designed a …

In this paper we introduce a methodology for dynamic job reconfiguration driven by the
programming model runtime in collaboration with the global resource manager. We improve …

The adoption of graphic processor units (GPU) in high-performance computing (HPC)
infrastructures determines, in many cases, the energy consumption of those facilities. For …