9th Workshop on Parallel/High-performance Object-oriented Scientific Computing

摘要

While object-oriented programming has been embraced in industry, particularly in the form of C++, Java, and Python, its acceptance by the parallel scientific programming community has been relatively slow. Nonetheless, various factors practically dictate the use of language features that provide higher level abstractions than do C or older FORTRAN standards. These include increasingly complex physics models, numerical algorithms, and hardware, e.g. deep memory hierarchies, ever-increasing numbers of processors, the advent of multi-core processors; more recently the use of heterogeneous architectures using the IBM Cell/BE or GP-GPUs, and soon the experimentation with many-core processors.