With the recent arrival of the exascale era, modern supercomputers are increasingly big
making their programming much more complex. In addition to performance, software …

Chapel supports distributed computing with an underlying PGAS memory address space.
While it provides abstractions for writing simple and elegant distributed code, the type …

Chapel is an emerging scalable, productive parallel programming language. In this work, we
analyze Chapel's performance using The Parallel Research Kernels on two different …

In big-data analytics, using tensor decomposition to extract patterns from large, sparse
multivariate data is a popular technique. Many challenges exist for designing parallel, high …

Modern supercomputers have complex features: many hardware threads, deep memory
hierarchies, and many co-processors/accelerators. Productively and effectively designing …

Chapel is an emerging PGAS (Partitioned Global Address Space) language whose design
goal is to make parallel programming more productive and generally accessible. To date …

Current programming models face challenges in dealing with modern supercomputers'
growing parallelism and heterogeneity. Emerging programming models, like the task-based …

Parallel programming is hard, and it is even harder to analyze parallel programs and identify
specific performance bottlenecks. Chapel is an emerging Partitioned-Global-Address-Space …

Demands on computational performance, power efficiency, data transfer, resource capacity,
and resilience for next generation high performance computing (HPC) systems present a …

With a widening gap between processor speed and communication latencies, overlap of
computation and communication becomes increasingly important. At the same time, variable …