Many program optimizations require exact knowledge of the sets of array elements that are
referenced in or that flow between statements or procedures. Some examples are array …

Parallel and heterogeneous computing are growing in audience thanks to the increased
performance brought by ubiquitous manycores and GPUs. However, available programming …

High Performance Fortran (HPF) was developed to support data parallel programming for
single‐instruction multiple‐data (SIMD) and multiple‐instruction multiple‐data (MIMD) …

Appropriate data distribution has been found to be critical for obtaining good performance
on distributed memory multicomputers such as the Thinking Machines CM-5, Intel Paragon …

Advanced program optimizations, such as array privatization, require precise array data flow
analyses, usually relying on conservative over-(or may) and under-(or must) approximations …

Abstract Distributed Memory Multicomputers (DMMs) such as the IBM SP-2, the Intel
Paragon and the Thinking Machines CM-5 offer significant advantages over shared memory …

Array remapping are useful to many applications on distributed memory parallel machines.
They are available in High Performance Fortran, a Fortran-based data-parallel language …

Since the beginning of the 2000s, the raw performance of processors stopped its
exponential increase. The modern graphic processing units (GPUs) have been designed as …

Data locality and workload balance are key factors for getting high performance out of data-
parallel programs on multiprocessor architectures. Data-parallel languages such as High …

Distributed-memory multicomputers, such as the Intel iPSC/860, the Intel Paragon, the IBM
SP-1/SP-2, the NCUBE/2, and the Thinking Machines CM-5, offer significant advantages …