TACO-template based collections for distributed computing platforms

Collective operations on distributed data sets promote a high-level data-parallel programming style that eases many aspects of parallel programming on distributed computing platforms. The authors describe the design and implementation of TACO, a template library that extends the Multiple Threads Template Library with higher-order operations on distributed object sets by means of reusable topology classes and C++ function templates.