This paper surveys a range of methods to collect necessary performance data on Intel CPUs
and NVIDIA GPUs for hierarchical Roofline analysis. As of mid-2020, two vendor …

With the rise of exascale systems and large, data‐centric workflows, the need to observe
and analyze high performance computing (HPC) applications during their execution is …

This paper presents a practical methodology for collecting performance data necessary to
conduct hierarchical Roofline analysis on NVIDIA GPUs. It discusses the extension of the …

Database peptide search algorithms deduce peptides from mass spectrometry data. There
has been substantial effort in improving their computational efficiency to achieve larger and …

Deep learning applications based on neural networks are generating considerable interest
in various fields due to their high accuracy. Such an application is usually very compute …

APEX (Autonomic Performance Environment for eXascale) is a performance measurement
library for distributed, asynchronous multitasking runtime systems. It provides support for …

Performance profiling tools are crucial for HPC specialists to identify performance
bottlenecks in parallel codes at various levels of granularity (ie, across nodes, ranks, and …

Database peptide search is the primary computational technique for identifying peptides
from the mass spectrometry (MS) data. Graphical Processing Units (GPU) computing is now …

In an effort to guide optimizations and detect performance regressions, developers of large
HPC codes must regularly collect and analyze application performance profiles across …

Performance optimization can be a daunting task especially as the hardware architecture
becomes more and more complex. This paper takes a kernel from the Materials Science …