PyOMP: Writing HPC code in Python

Benchmarking of I/O Activities in HPC Applications with STrace Inspector

ZeroSum: User Space Utility for Monitoring Process, Thread, OS and HW Resources

OpenMP 6.0 Part 2: New Device Offloading Features

OpenMP 6.0 Part 1: New Host-side Features and Enhancements

ChEESE and POP: a Story of Success and Fruitful Interaction

Assessing CPU Code Quality

How to Use POP Services

The CARM Tool: Cache-aware Roofline Model for HPC

Performance Analysis of OpenMP Target Offloading in Score-P

Asynchronous GPU Programming in OpenMP

Six and a half years of POP CoE: What Remains?

Resources for Co Design

The POP Superheroes

POP: The SME Perspective

Introduction to Paraver

Module 4.2a: Introduction to Paraver - Timelines

Module 4.2b: Introduction to Paraver - Tables

Module 4.2c: Introduction to Paraver - Semantic Functions

Module 4.2: Introduction to Paraver

Module 8: Computing the POP Metrics with Score-P, Scalasca, Cube

The Scalasca Scalable Parallel Performance Analysis Toolset – for POP assessments and beyond

Debugging Tools for Correctness Analysis of MPI and OpenMP Applications

Using Paraver: On Sampling In Traces

Using Paraver: Life without Noise

Using Paraver: See the Noise

Using Paraver: Identifying Structure

POPCast #4: Why Does Code Matter?

Identifying performance bottlenecks in hybrid MPI + OpenMP software

PyPOP An interactive tool for performance assessment