Configuration in software systems helps to ensure efficient operation and meet diverse user
needs. Yet, some, if not all, configuration options have profound implications for the system's …

Deep Neural Network (DNN) frameworks use distributed training to enable faster time to
convergence and alleviate memory capacity limitations when training large models and/or …

Aggregated HPC resources have rigid allocation systems and programming models which
struggle to adapt to diverse and changing workloads. Consequently, HPC systems fail to …

The computational patterns of stencil operations are commonly used in HPC applications.
Many HPC platforms utilize the computation capability of GPUs to accelerate stencil …

Performance tuning, software/hardware co-design, and job scheduling are among the many
tasks that rely on models to predict application performance. We propose and evaluate low …

Taint analysis aims to track data flows in systems, with potential use cases for security,
privacy and performance. This paper describes an end-to-end dynamic taint analysis …

The many configuration options of modern applications make it difficult for users to select a
performance-optimal configuration. Performance models help users in understanding …

Performance engineering is a proactive and systematic approach aimed at designing,
building, and enhancing software systems to ensure their efficient and reliable operation. It …

Modern high-performance applications are highly-configurable systems that provide
hundreds of configuration options. Performance models offer insights into the performance …

Diversely Heterogeneous System-on-Chips (DH-SoC) are increasingly popular computing
platforms in many fields, such as autonomous driving and AR/VR applications, due to their …