Performance Analysis and Debugging on Shaheen III: Practical Optimization on AMD Genoa Systems

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Full Day October 26, 2026
Building 3, Room 5209
Presented by
AE Aniello Esposito Principal Research Engineer, HPE
JP Jean Pourroy Senior HPC Performance Engineer, HPE
TB Thierry Braconnier HPC Performance Specialist, HPE
PB Pierre-Eric Bernard HPC Specialist, HPE
MG Mathieu Gontier Field Application Engineer & Head of HPC, AMD
KA Kadir Akbudak Computational Scientist, KAUST Supercomputing Laboratory
About this session

Abstract

Achieving high application performance on modern HPC systems requires more than computational power alone. This full-day tutorial provides a practical introduction to performance analysis, debugging, and optimization on the Shaheen III CPU partition, powered by AMD EPYC™ Genoa processors. The morning session combines presentations with demonstrations covering key performance engineering concepts and workflows. Participants will learn how to identify computational bottlenecks, analyze memory and communication behavior, interpret profiling results, and investigate correctness and scalability issues. HPE experts will introduce HPE Performance Tools and GDB4HPC for performance analysis and large-scale debugging, while AMD specialists will present AMD Zen Software Studio and optimization techniques tailored to Genoa-based systems. The afternoon session will be organized as an interactive Application Clinic. Participants are encouraged to bring their own applications and performance challenges for dedicated one-on-one consultations with AMD and HPE experts. These sessions will focus on real-world bottlenecks, debugging strategies, profiling methodologies, and optimization opportunities specific to each workload. The tutorial targets HPC users, application developers, computational scientists, and performance engineers seeking to improve application efficiency and accelerate scientific discovery on next-generation AMD-powered supercomputing platforms.

Presenters

Biographies

Aniello Esposito HPE

Aniello Esposito is a Principal Research Engineer in the EMEA Research Lab at Hewlett Packard Enterprise (HPE), based in Switzerland. His work focuses on high-performance computing (HPC), AI/ML, and emerging hybrid classical-quantum computing technologies. He leads collaborations with research institutions and supercomputing centers across Europe and the Middle East, including long-standing engagements with KAUST. Aniello has more than a decade of experience in application performance analysis, scalability optimization, and scientific software development on large-scale supercomputers. He is actively involved in HPC research, user enablement, and technology evaluation

Jean Pourroy HPE

Jean Pourroy is a Senior HPC Performance Engineer at Hewlett Packard Enterprise specializing in performance analysis, code optimization, MPI, GPU computing, and exascale applications. He works with leading supercomputing centers and research organizations across Europe and the Middle East to identify performance bottlenecks and optimize scientific workloads. Jean holds a PhD in High Performance Computing from ENS Paris-Saclay, where his research focused on architecture characterization and application optimization for future supercomputers. His expertise spans performance engineering, profiling methodologies, accelerator programming, and large-scale application tuning

Thierry Braconnier HPE

Thierry Braconnier is an HPC performance specialist at Hewlett Packard Enterprise with extensive experience in application profiling, performance analysis, and system optimization on large-scale HPC platforms. He regularly contributes to advanced training programs and user workshops, including performance analysis courses for the LUMI supercomputer ecosystem. His expertise includes identifying scalability bottlenecks, performance measurement methodologies, and practical optimization techniques for scientific applications running on modern CPU and accelerator-based architectures

Pierre-Eric Bernard HPE

Pierre-Eric Bernard is an HPC specialist at Hewlett Packard Enterprise with expertise in customer support for large-scale supercomputing environments. He works closely with scientific users to improve application performance, debugging productivity, and efficient utilization of modern HPC platforms

Mathieu Gontier AMD

Mathieu Gontier, Field Application Engineer and Head of HPC within the AMD Center of Excellence, has worked in the semiconductor industry for more than a decade. His expertise includes characterization and performance modeling of HPC applications on AMD platforms and associated software ecosystems. Before joining AMD, Mathieu spent many years as an HPC software developer and performance engineer, giving him a strong understanding of both application and hardware perspectives. He works closely with HPC centers and end users to optimize scientific applications and maximize performance on modern AMD architectures

Kadir Akbudak KAUST

Kadir Akbudak is a computational scientist at the Supercomputing Laboratory (KSL) at King Abdullah University of Science and Technology (KAUST). His work focuses on performance modeling and research collaborations in high-performance scientific computing, spanning areas such as linear algebra, seismic imaging, GPU acceleration, and atmospheric and oceanic sciences. During his undergraduate studies and postdoctoral research at Bilkent University, Dr. Akbudak participated in European Commission–funded PRACE projects. As a postdoctoral researcher at KAUST’s Extreme Computing Research Center, he led the development of the Hierarchical Computations on Manycore Architectures (HiCMA) software toolkit. He later joined the Innovative Computing Laboratory (ICL) at the University of Tennessee, Knoxville, where he contributed to the U.S. Department of Energy–funded Software for Linear Algebra Targeting Exascale (SLATE) project as a research scientist under the supervision of Turing Award laureate Dr. Jack Dongarra. Dr. Akbudak holds both master’s and doctoral degrees in computer science from Bilkent University

Seats are limited

Tutorials run on Monday, 26 October 2026 at KAUST. Attendance is free, but registration is required.