# Platform independent profiling of a QCD code

## TL;DR

This paper introduces a platform-independent profiling method for the openQCD lattice QCD code using the SimGrid simulator, enabling efficient performance analysis and optimization across diverse supercomputing architectures.

## Contribution

It presents a simulation-based profiling procedure for openQCD that reduces costs and aids in performance prediction on current and future HPC platforms.

## Key findings

- Effective performance predictions for openQCD on various architectures.
- Reduced profiling costs through simulation-based approach.
- Ability to estimate code behavior on future supercomputers.

## Abstract

The supercomputing platforms available for high performance computing based research evolve at a great rate. However, this rapid development of novel technologies requires constant adaptations and optimizations of the existing codes for each new machine architecture. In such context, minimizing time of efficiently porting the code on a new platform is of crucial importance. A possible solution for this common challenge is to use simulations of the application that can assist in detecting performance bottlenecks. Due to prohibitive costs of classical cycle-accurate simulators, coarse-grain simulations are more suitable for large parallel and distributed systems. We present a procedure of implementing the profiling for openQCD code [1] through simulation, which will enable the global reduction of the cost of profiling and optimizing this code commonly used in the lattice QCD community. Our approach is based on well-known SimGrid simulator [2], which allows for fast and accurate performance predictions of HPC codes. Additionally, accurate estimations of the program behavior on some future machines, not yet accessible to us, are anticipated.