Assessing Performance Implications of Deep Copy Operations via Microbenchmarking

Millad Ghane, Sunita Chandrasekaran, Margaret S. Cheung

As scientific frameworks become sophisticated, so do their data structures. Current data structures are no longer simple in design and they have been progressively complicated. The typical trend in designing data structures in scientific applications are basically nested data structures: pointing to a data structure within another one. Managing nested data structures on a modern heterogeneous system requires tremendous effort due to the separate memory space design. In this paper, we will discuss the implications of deep copy on data transfers on current heterogeneous. Then, we will discuss the two options that are currently available to perform the memory copy operations on complex structures and will introduce pointerchain directive that we proposed. Afterwards, we will introduce a set of extensive benchmarks to compare the available approaches. Our goal is to make our proposed benchmarks a basis to examine the efficiency of upcoming approaches that address the challenge of deep copy operations.

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