The advent of petascale computing has introduced new challenges (eg Heterogeneity,
system failure) for programming scalable parallel applications. Increased complexity and …

Datacenter operations today provide a plethora of new queueing and scheduling problems.
The notion of a “job” has become more general and multi-dimensional. The ways in which …

Many shared computing clusters allow users to utilize excess idle resources at lower cost or
priority, with the proviso that some or all may be taken away at any time. But, exploiting such …

Job management software on peta-and exascale supercomputers continues to provide static
resource allocations, from a program's start until its end. Dynamic resource allocation and …

The throughput of supercomputers depends not only on efficient job scheduling but also on
the type of jobs that form the workload. Malleable jobs are most favourable for a cluster as …

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 …

With the growing constraints on power budget and increasing hardware failure rates, the
operation of future exascale systems faces several challenges. Towards this, resource …

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 …

In the design of future HPC systems, research in resource management is showing an
increasing interest in a more dynamic control of the available resources. It has been proven …

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 …