Increasing node and cores-per-node counts in supercomputers render scheduling and load
balancing critical for exploiting parallelism. OpenMP applications can achieve high …

This article proposes Bayesian optimization augmented factoring self-scheduling (BO FSS),
a new parallel loop scheduling strategy. BO FSS is an automatic tuning variant of the …

Parallel libraries such as OpenMP distribute the iterations of parallel-for-loops among the
threads, using a programmer-specified scheduling policy. While the existing scheduling …

Parallelizing code in a shared-memory environment is commonly done utilizing loop
scheduling (LS) in a fork-join manner as in OpenMP. This manner of parallelization is …

Many shared‐memory parallel irregular applications, such as sparse linear algebra and
graph algorithms, depend on efficient loop scheduling (LS) in a fork‐join manner despite …

The scalability of high-performance, parallel iterative applications is directly affected by how
well they use the available computing resources. These applications are subject to load …

Task-parallel languages such as X10 implement dynamic lightweight task-parallel execution
model, where programmers are encouraged to express the ideal parallelism in the program …

Scientific and data analysis applications are increasingly complex, with evolving
computational and memory requirements during execution. Conversely, modern high …

Irregular algorithms (ie, algorithms that make irregular memory accesses) are notorious for
being difficult to optimize on parallel architectures due to load imbalance in the number of …

Global schedulers are components in parallel runtime libraries that distribute the
application's workload across physical resources. More often than not, applications …