Deep configuration performance learning: A systematic survey and taxonomy

J Gong, T Chen - ACM Transactions on Software Engineering and …, 2024 - dl.acm.org
Performance is arguably the most crucial attribute that reflects the quality of a configurable
software system. However, given the increasing scale and complexity of modern software …

Towards hpc i/o performance prediction through large-scale log analysis

S Kim, A Sim, K Wu, S Byna, Y Son, H Eom - Proceedings of the 29th …, 2020 - dl.acm.org
Large-scale high performance computing (HPC) systems typically consist of many
thousands of CPUs and storage units, while used by hundreds to thousands of users at the …

Leveraging interpolation models and error bounds for verifiable scientific machine learning

T Chang, A Gillette, R Maulik - Journal of Computational Physics, 2025 - Elsevier
Effective verification and validation techniques for modern scientific machine learning
workflows are challenging to devise. Statistical methods are abundant and easily deployed …

Algorithm 1012: DELAUNAYSPARSE: Interpolation via a sparse subset of the Delaunay triangulation in medium to high dimensions

TH Chang, LT Watson, TCH Lux, AR Butt… - ACM Transactions on …, 2020 - dl.acm.org
DELAUNAYSPARSE contains both serial and parallel codes written in Fortran 2003 (with
OpenMP) for performing medium-to high-dimensional interpolation via the Delaunay …

A quantitative study of the spatiotemporal i/o burstiness of hpc application

W Yang, X Liao, D Dong, J Yu - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Understanding the I/O characteristics of applications on supercomputers is crucial to paving
the path for application optimization and system resource allocation. We collect and analyze …

I/o burst prediction for hpc clusters using darshan logs

E Saeedizade, R Taheri, E Arslan - 2023 IEEE 19th …, 2023 - ieeexplore.ieee.org
Understanding cluster-wide I/O patterns of large-scale HPC clusters is essential to minimize
the occurrence and impact of I/O interference. Yet, most previous work in this area focused …

Design strategies and approximation methods for high-performance computing variability management

Y Wang, L Xu, Y Hong, R Pan, T Chang… - Journal of Quality …, 2023 - Taylor & Francis
Performance variability management is an active research area in high-performance
computing (HPC). In this article, we focus on input/output (I/O) variability, which is a …

Pushing the Boundary: Specialising Deep Configuration Performance Learning

J Gong - arxiv preprint arxiv:2407.02706, 2024 - arxiv.org
Software systems often have numerous configuration options that can be adjusted to meet
different performance requirements. However, understanding the combined impact of these …

Modeling I/O performance variability in high-performance computing systems using mixture distributions

L Xu, Y Wang, T Lux, T Chang, J Bernard, B Li… - Journal of Parallel and …, 2020 - Elsevier
Performance variability is an important factor of high-performance computing (HPC)
systems. HPC performance variability is often complex because its sources interact and are …