# Assessing Performance Implications of Deep Copy Operations via Microbenchmarking

## TL;DR

This paper evaluates the performance impact of deep copy operations on complex nested data structures in heterogeneous systems, proposing benchmarks and a new pointerchain directive to improve efficiency assessment.

## Contribution

It introduces a set of benchmarks and a pointerchain directive to better evaluate deep copy methods for complex data structures on heterogeneous systems.

## Key findings

- Benchmark results highlight performance differences among deep copy approaches.
- The pointerchain directive offers a new way to optimize deep copy operations.
- The benchmarks serve as a basis for future research on deep copy efficiency.

## Abstract

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.