Celebrating the 30th Anniversary of PPAM
The first PPAM was held in 1994, in Czestochowa
HONORARY PATRONAGE
The PPAM 2024 conference is under the honorary patronage of the city of Ostrava.
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Celebrating the 30th Anniversary of PPAM
The first PPAM was held in 1994, in Czestochowa
HONORARY PATRONAGE
The PPAM 2024 conference is under the honorary patronage of the city of Ostrava.
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PPAM 2024 Session Recordings Already Available
Session recordings are available on the conference site: program.
All recordings are protected by a password sent in e-mail.
Photo gallery is now available!!!
Author's Instructions for Accepted Contributions!!
Author's Instructions for Accepted Contributions are already available!!!
Turing Laureate Jack Dongarra discusses HPC challenges
We invite you to read the interviewgiven by Jack Dongarra during the conference. [download pdf file]
PPAM 2024 Special Award for the best paper presented at the First PPAM Workshop on RISC-V
Based on the reviewers’ reports, the Workshop chairs decided to give this award, including 400 euros funded by sponsors - Codasip and Semidynamics, to the paper:
PPAM Best Paper Award
The International Conference on Parallel Processing and Applied Mathematics (PPAM) Best Paper Award is given upon recommendation of the PPAM Chairs and Program Committee in recognition of the research paper quality, originality and significance of the work in high performance computing.
The PPAM Best Paper was first awarded at PPAM 2019 in Bialystok.
PPAM 20224 Winner for Main Track
PPAM 2024 Winner for Workshops
PPAM 2024 Winner for Student Paper
To stimulate potential authors' interest in submitting high-quality articles to the PPAM conference, one author of each winning paper will receive a significant reduction in the conference fee for the next PPAM conference. As we have three winning papers in PPAM 2024, one author of each work gets at least a 50% discount on the conference fee for PPAM 2026.
The PPAM 2024 conference is organized by the Department of Computer Science of the Czestochowa University of Technology together with the Faculty of Electrical Engineering and Computer Science and IT4Innovations National Supercomputing Center of the Technical University of Ostrava, in technical cooperation with Poznań Supercomputing and Networking Center, under the patronage of the Committee of Informatics of the Polish Academy of Sciences.
This year, the PPAM conference will take place in Ostrava, a city in the northeast of the Czech Republic and the capital of the Moravian-Silesian Region. PPAM2024 will be held from September 8 to September 11, 2024, at the Technical University of Ostrava, at the Faculty of Electrical Engineering and Computer Science.
17. listopadu 2172/15, 708 00 Ostrava-Poruba (set the route in google maps )
The PPAM 2024 conference, fifteenth in a series, will cover topics in parallel and distributed processing, including theory and applications, as well as applied mathematics. The focus will be on models, algorithms, and software tools which facilitate efficient and convenient utilization of modern parallel and distributed computing architectures, as well as on large-scale applications. A special attention is expected to be given to the future of computing beyond Moore's Law, and AI/ML approaches in high performance computing.
PPAM is a biennial conference started in 1994, with the proceedings published by Springer in the Lecture Notes in Computer Sciences series. The PPAM Proceedings are indexed in main databases such as Web of Science, Scopus, and DBLP.
PPAM 2024 is expected to be an in-person conference with the possibility of remote participation. However, we strongly encourage in-person participation, as PPAM also has very compelling networking aspects and a social and cultural program.
The organizers will provide shuttles between Krakow airport and conference hotels in Ostrava.
 
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Ivona Brandic Vienna University of Technology, Austria Vincenzo De Maio Vienna University of Technology, Austria "Building Blocks of Quantum-Accelerated Supercomputing" abstract |
 | Suma George Cardwell Sandia National Laboratories, USA "Neuromorphic Computing: Towards Brain-like Energy Efficiency" abstract |
 | Jack Dongarra University of Tennessee and ORNL, USA "Hits, Flops, and More" abstract |
 | Anshu Dubey Argonne National Laboratory, USA "Design, Code-generation, and Synthesis for Next Generation Science Codes" abstract |
 | Lin Gan Tsinghua University & National Supercomputing Center in Wuxi, China "Extreme Scale Earthquake Simulation with Crossing Multi-faults and Topography" abstract |
 | Torsten Hoefler ETH Zurich, Switzerland "AI for High-Performance Climate and Earth Virtualization Engines" abstract |
 | Klaus Jansen University of Kiel, Germany "New Algorithmic Results for Scheduling via Integer Linear Programming" abstract |
 | Dieter Kranzlmüller Leibniz Supercomputing Centre (LRZ) and Ludwig-Maximilians-Universität Munich (LMU), Germany |
 | Jesus Labarta Barcelona Supercomputing Center, Spain "Pushing RISC-V into HPC" abstract |
 | Filippo Mantovani Barcelona Supercomputing Center, Spain "A RISC-V vector CPU for High-Performance Computing: architecture, platforms and tools to make it happen" abstract |
 | Satoshi Matsuoka RIKEN Center for Computational Science, Japan "Beyond Fugaku/Exascale--- Evolving Computing Towards the Next Generation at Riken R-CCS: AI for Science TRIP-AGIS, JHPC-Quantum, and FugakuNEXT" |
 | Dhabaleswar K. Panda Ohio State University, USA "Designing Converged Middleware for HPC, AI, Big Data, and Data Science" abstract |
 | Manish Parashar University of Utah, USA "From the Edge to HPC – Harnessing the Computing Continuum for Science" abstract |
 | Massimiliano Lupo Pasini Oak Ridge National Laboratory, USA "Overview of Oak Ridge National Laboratory’s AI Initiative: Advancing Secure, Trustworthy, and Energy-Efficient AI at Scale for Scientific Discovery" abstract |
 | Olga Pearce Lawrence Livermore National Laboratory, USA "Collaborative continuous benchmarking for HPC" abstract |
 | John Shalf Lawrence Berkeley National Laboratory, LBNL, USA "Investigating Chiplets for Scalable and Cost Effective HPC Beyond Exascale" abstract |
 | Amarda Shehu George Mason University, USA "Strengthening AI to Enable Scientific Discovery" abstract |
 | Michela Taufer University of Tennessee, USA "Analytics4NN: Accelerating Neural Architecture Search through Modeling and High-Performance Computing Techniques" abstract |
 | Juris Ulmanis Alpine Quantum Technology (AQT), Austria "Bridging the gap: quantum accelerators for HPC" abstract |
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Gabriele Paciucci Nvidia , Principal Solution Architect EMEA "How to Harness the Power of High-Performance Computing for Machine Learning and Artificial Intelligence" abstract |
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Vineet Tyagi Supermicro, System Architekt EMEA "How to Harness the Power of High-Performance Computing for Machine Learning and Artificial Intelligence" abstract |
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Utz-Uwe Haus Hewlett Packard Enterprise "Digitial Twins – Past, Present and a Challenging Future " abstract |
Ivona Brandic Suma George Cardwell Jack Dongarra Anshu Dubey Lin Gan
Torsten Hoefler Klaus Jansen Jesus Labarta Filippo Mantovani Satoshi Matsuoka
Thomas Monz Dhabaleswar K. Panda Manish Parashar Massimiliano Lupo Pasini Olga Pearce John Shalf Amarda Shehu Michela Taufer
CHAIR OF PROGRAM COMMITTEE
Czestochowa University of Technology, Poland
Roman Wyrzykowski received the MSc and PhD degrees from Kiev Polytechnic Institute in Computer Science, in 1982 and 1986, respectively. Since 1982, he is employed at Czestochowa University of Technology, Poland, where currently, he is a Full Professor in the Department of Computer Science. His fields of expertise are: parallel and distributed computing, cloud and edge technologies, HPC co-design technologies, performance modeling and optimization, parallel computing applications, accelerating fluid dynamic simulation with machine learning methods, etc. Since 1994, he has chaired the program committee of the PPAM series of international conferences on parallel processing and applied mathematics. He is an IEEE Senior Member and member of ACM.
CO-CHAIR OF PROGRAM COMMITTEE
University of Southern California, USA
Ewa Deelman received the PhD degree in computer science from Rensselaer Polytechnic Institute. She is currently a research professor with the Computer Science Department and the assistant director for the Science Automation Technologies group at the University of Southern California Information Sciences Institute. Her research focuses on distributed computing, in particular regarding how to best support complex scientific applications on a variety of computational environments, including campus clusters, clouds, and high-performance and high-throughput computing systems. Dr. Deelman is a AAAS, IEEE, and USC/ISI Felow.
