Given the complexity of current supercomputers and applications, being able to trace
application executions to understand their behavior is not a luxury. As constraints, tracing …

Fine-grain time synchronization is important to address several challenges in today and
future High Performance Computing (HPC) centers. Among the many,(i) co-scheduling …

A fundamental problem in parallel processing is the difficulty in efficiently partitioning work:
the result is that much of a parallel program's execution time is often spent idle or performing …

Performance benchmarks are an integral part of the development and evaluation of parallel
algorithms, both in distributed applications as well as MPI implementations themselves. The …

Data movement is considered the main performance concern for exascale, including both on-
node memory and off-node network communication. Indeed, many application traces show …

Network performance has contributed fundamentally to the growth of supercomputing over
the past decades. In parallel, High Performance Computing (HPC) peak performance has …

Computational problems can be classified according to their algorithmic complexity, which is
defined based on how the resources needed to solve the problem, eg the execution time …

Data movement is considered the main performance concern for exascale, including both on-
node memory and off-node network communication. Indeed, many application traces show …

Supercomputers are employed for the execution of jobs that require considerably extensive
computational resources. However, over or under-request job runtime has been observed in …

Normally deadlock is the common situation of multithreaded applications; it causes longer
memory access time, page table memory utilization, and internal fragmentation. Due to …