Volume
OASIcs, Volume 127
16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)
Event
PARMA-DITAM 2025, January 22, 2025, Barcelona, SpainEditors
Publication Details
- published at: 2025-02-27
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- ISBN: 978-3-95977-363-8
- DBLP: db/conf/hipeac/parma2025
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Document
Complete Volume
OASIcs, Volume 127, PARMA-DITAM 2025, Complete Volume
Abstract
OASIcs, Volume 127, PARMA-DITAM 2025, Complete Volume
Cite as
16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025). Open Access Series in Informatics (OASIcs), Volume 127, pp. 1-100, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@Proceedings{cattaneo_et_al:OASIcs.PARMA-DITAM.2025,
title = {{OASIcs, Volume 127, PARMA-DITAM 2025, Complete Volume}},
booktitle = {16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)},
pages = {1--100},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-363-8},
ISSN = {2190-6807},
year = {2025},
volume = {127},
editor = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025},
URN = {urn:nbn:de:0030-drops-229378},
doi = {10.4230/OASIcs.PARMA-DITAM.2025},
annote = {Keywords: OASIcs, Volume 127, PARMA-DITAM 2025, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization
Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as
16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025). Open Access Series in Informatics (OASIcs), Volume 127, pp. 0:i-0:x, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{cattaneo_et_al:OASIcs.PARMA-DITAM.2025.0,
author = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
title = {{Front Matter, Table of Contents, Preface, Conference Organization}},
booktitle = {16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)},
pages = {0:i--0:x},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-363-8},
ISSN = {2190-6807},
year = {2025},
volume = {127},
editor = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025.0},
URN = {urn:nbn:de:0030-drops-229363},
doi = {10.4230/OASIcs.PARMA-DITAM.2025.0},
annote = {Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Analysis of GPU Memory Allocation Characteristics
Abstract
The number of applications subject to safety-critical regulations is on the rise, and consequently, the computing requirements for such applications are increasing as well. This trend has led to the integration of General-Purpose Graphics Processing Units (GPGPUs) into these systems. However, the inherent characteristics of GPGPUs, including their black-box nature, dynamic allocation mechanisms, and frequent use of pointers, present challenges in certifying these applications for safety-critical systems.
This paper aims to shed light on the unique characteristics of GPU programs and how they impact the certification process. To achieve this goal, several allocation methods are rigorously evaluated to determine which one is best suited to an application, regarding the program characteristics within the safety-critical domain.
By conducting this evaluation, we seek to provide insights into the complexities of GPU memory accesses and its compatibility with safety-critical requirements. The ultimate objective is to offer recommendations on the most appropriate allocation method based on the unique needs of each application, thus contributing to the safe and reliable integration of GPGPUs into safety-critical systems.
Cite as
Marcos Rodriguez, Irune Yarza, Leonidas Kosmidis, and Alejandro J. Calderón. Analysis of GPU Memory Allocation Characteristics. In 16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025). Open Access Series in Informatics (OASIcs), Volume 127, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{rodriguez_et_al:OASIcs.PARMA-DITAM.2025.1,
author = {Rodriguez, Marcos and Yarza, Irune and Kosmidis, Leonidas and Calder\'{o}n, Alejandro J.},
title = {{Analysis of GPU Memory Allocation Characteristics}},
booktitle = {16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)},
pages = {1:1--1:15},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-363-8},
ISSN = {2190-6807},
year = {2025},
volume = {127},
editor = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025.1},
URN = {urn:nbn:de:0030-drops-229057},
doi = {10.4230/OASIcs.PARMA-DITAM.2025.1},
annote = {Keywords: CUDA, Memory allocation, Rodinia, Embedded}
}
Document
Custom Floating-Point Computations for the Optimization of ODE Solvers on FPGA
Abstract
Mean Field Analysis and Markovian Agents are powerful techniques for modeling complex systems of distributed interacting objects, for which efficient analytical and numerical solution algorithms can be implemented through linear systems of ordinary differential equations (ODEs). Solving such ODE systems on Field Programmable Gate Arrays (FPGAs) is a promising alternative to traditional CPU- and GPU-based approaches, especially in terms of energy consumption; however, the floating-point computations required are generally thought to be slow and inefficient when implemented on FPGA. In this paper, we demonstrate the use of High-Level Synthesis with automated customization of low-precision floating-point calculations, obtaining hardware accelerators for ODE solvers with improved quality of results and minimal output error. The proposed methodology does not require any manual rewriting of the solver code, but it remains prohibitively slow to evaluate any possible floating-point configuration through logic synthesis; in the future, we will thus implement automated design space exploration methods able to suggest promising configurations under user-defined accuracy and performance constraints.
Cite as
Serena Curzel and Marco Gribaudo. Custom Floating-Point Computations for the Optimization of ODE Solvers on FPGA. In 16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025). Open Access Series in Informatics (OASIcs), Volume 127, pp. 2:1-2:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{curzel_et_al:OASIcs.PARMA-DITAM.2025.2,
author = {Curzel, Serena and Gribaudo, Marco},
title = {{Custom Floating-Point Computations for the Optimization of ODE Solvers on FPGA}},
booktitle = {16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)},
pages = {2:1--2:13},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-363-8},
ISSN = {2190-6807},
year = {2025},
volume = {127},
editor = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025.2},
URN = {urn:nbn:de:0030-drops-229064},
doi = {10.4230/OASIcs.PARMA-DITAM.2025.2},
annote = {Keywords: Differential Equations, High-Level Synthesis, FPGA, floating-point}
}
Document
System-Level Timing Performance Estimation Based on a Unifying HW/SW Performance Metric
Abstract
The rapidly increasing complexity of embedded systems and the critical impact of non-functional requirements demand the adoption of an appropriate system-level HW/SW co-design methodology. This methodology tries to satisfy all design requirements by simultaneously considering several alternative HW/SW implementations. In this context, early performance estimation approaches are crucial in reducing the design space, thereby minimizing design time and cost. To address the challenge of system-level performance estimation, this work presents and formalizes a novel approach based on a unifying HW/SW performance metric for early execution time estimation. The proposed approach estimates the execution time of a C function when executed by different HW/SW processor technologies. The approach is validated through an extensive experimental study, demonstrating its effectiveness and efficiency in terms of estimation error (i.e., lower than 10%) and estimation time (close to zero) when compared to existing methods in the literature.
Cite as
Vittoriano Muttillo, Vincenzo Stoico, Giacomo Valente, Marco Santic, Luigi Pomante, and Daniele Frigioni. System-Level Timing Performance Estimation Based on a Unifying HW/SW Performance Metric. In 16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025). Open Access Series in Informatics (OASIcs), Volume 127, pp. 3:1-3:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{muttillo_et_al:OASIcs.PARMA-DITAM.2025.3,
author = {Muttillo, Vittoriano and Stoico, Vincenzo and Valente, Giacomo and Santic, Marco and Pomante, Luigi and Frigioni, Daniele},
title = {{System-Level Timing Performance Estimation Based on a Unifying HW/SW Performance Metric}},
booktitle = {16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)},
pages = {3:1--3:14},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-363-8},
ISSN = {2190-6807},
year = {2025},
volume = {127},
editor = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025.3},
URN = {urn:nbn:de:0030-drops-229071},
doi = {10.4230/OASIcs.PARMA-DITAM.2025.3},
annote = {Keywords: embedded systems, hw/sw co-design, performance estimation, lasso, machine learning}
}
Document
Towards Studying the Effect of Compiler Optimizations and Software Randomization on GPU Reliability
Abstract
The evolution of Graphics Processing Unit (GPU) compilers has facilitated the support for general-purpose programming languages across various architectures. The NVIDIA CUDA Compiler (NVCC) employs multiple compilation levels prior to generating machine code, implementing intricate optimizations to enhance performance. These optimizations influence the manner in which software is mapped to the underlying hardware, which can also impact GPU reliability.
TASA is a source-to-source code randomization tool designed to alter the mapping of software onto the underlying hardware. It achieves this by generating random permutations of variable and function declarations, thereby introducing random padding between declarations of different types and modifying the program memory layout. Since this modifies their location in the memory, it also modifies their cache placement, affecting both their execution time (due to the different conflicts between them, which result in a different amount of cache misses in every execution), as well as their lifetime in the cache.
In this work, which is part of the HiPEAC Student Challenge 2025, we first examine the reproducibility of a subset of data presented in the ACM TACO paper "Assessing the Impact of Compiler Optimizations on GPU Reliability" [Santos et al., 2024], and second we extend it by combining it with our proposal of software randomization. The paper indicates that the -O3 optimization flag facilitates an increased workload before failures occur within the application. By employing TASA, we investigate the impact of GPU randomization on reliability and performance metrics.
By reproducing the results of the paper on a different GPU platform, we observe the same trend as reported in the original publication. Moreover, our preliminary results with the application of software randomization show in several cases an improved Mean Waiting Before Failure (MWBF) compared to the original source code.
Cite as
Pau López Castillón, Xavier Caricchio Hernández, and Leonidas Kosmidis. Towards Studying the Effect of Compiler Optimizations and Software Randomization on GPU Reliability. In 16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025). Open Access Series in Informatics (OASIcs), Volume 127, pp. 4:1-4:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{castillon_et_al:OASIcs.PARMA-DITAM.2025.4,
author = {Castill\'{o}n, Pau L\'{o}pez and Hern\'{a}ndez, Xavier Caricchio and Kosmidis, Leonidas},
title = {{Towards Studying the Effect of Compiler Optimizations and Software Randomization on GPU Reliability}},
booktitle = {16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)},
pages = {4:1--4:10},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-363-8},
ISSN = {2190-6807},
year = {2025},
volume = {127},
editor = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025.4},
URN = {urn:nbn:de:0030-drops-229083},
doi = {10.4230/OASIcs.PARMA-DITAM.2025.4},
annote = {Keywords: Graphics processing units, reliability, software randomization, error rate}
}
Document
Evaluation of the Parallel Features of Rust for Space Systems
Abstract
The rise in complexity of the algorithms run on space systems, largely attributable to higher resolution instruments which generate a large amount of the data to be processed, as well as to the need for increased autonomy, which relies on Neural Network inference systems in future missions, demand the adoption of more powerful on-board hardware, such as multicores.
At the same time, the correctness and reliability of critical on-board software is of paramount importance for the success of space missions. However, developing such complex software in low-level languages can have a negative impact on these aspects.
For this reason, this paper evaluates the role that the Rust programming language can have in this change, given its memory safety and built in support for parallelism, which allows to better utilise more powerful hardware, in particular multicore cpus, without compromising the programmability and safety of the code.
To this end, the GPU4S benchmarking suite, part of the open source OBPMark benchmarking suite of the European Space Agency (ESA), is ported to Rust, with sequential and parallel implementations. The performance of the ported benchmarks is compared to the existing sequential and parallel implementations in low-level languages to evaluate the trade-offs of the different solutions, and it is evaluated on several multicore platforms which are candidates for future on-board processing systems. A particular focus is put on parallel versions of the benchmarks, where Rust offers solid native support, as well as library support for fast parallelization similar to OpenMP. Finally, in terms of correctness, the Rust implementations are free of recently detected defects in the low-level implementations of the GPU4S benchmarks.
Cite as
Alberto Perugini and Leonidas Kosmidis. Evaluation of the Parallel Features of Rust for Space Systems. In 16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025). Open Access Series in Informatics (OASIcs), Volume 127, pp. 5:1-5:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{perugini_et_al:OASIcs.PARMA-DITAM.2025.5,
author = {Perugini, Alberto and Kosmidis, Leonidas},
title = {{Evaluation of the Parallel Features of Rust for Space Systems}},
booktitle = {16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)},
pages = {5:1--5:20},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-363-8},
ISSN = {2190-6807},
year = {2025},
volume = {127},
editor = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025.5},
URN = {urn:nbn:de:0030-drops-229098},
doi = {10.4230/OASIcs.PARMA-DITAM.2025.5},
annote = {Keywords: Rust, Multicore, Space Systems}
}
Document
HiPART: High-Performance Technology for Advanced Real-Time Systems
Abstract
Cyber-physical systems (CPS) attempt to meet real-time and safety requirements by using hypervisors that provide isolation via virtualisation and Real-Time Operating Systems that manage the concurrency of system tasks. However, the operating system’s (OS) decisions may hinder the efficiency of tasks because it needs more awareness of their specific intricacies. Hence, one critical limitation to efficiently developing CPSs is the lack of tailored parallel programming models that can harness the capabilities of advanced heterogeneous architectures while meeting the requirements integral to CPSs, such as real-time behaviour and safety requirements. While conventional HPC languages, like OpenMP and CUDA, cannot accommodate critical non-functional properties, safety languages, like Rust and Ada, are limited in their capabilities to exploit complex systems efficiently. On top of that, accessibility to the programming task is essential to making the system usable to different domain experts. HiPART tackles these challenges by developing a comprehensive framework holistically addressing efficiency, interoperability, reliability, and sustainability. The HiPART framework, based on OpenMP, provides tailored support for (1) real-time behaviour and safety requirements and (2) the efficient exploitation of advanced parallel and heterogeneous processor architectures. This support is exposed to users through extensions to the OpenMP specification and its implementation in the LLVM framework, including the compiler and the OpenMP runtime library. With this framework, HiPART will contribute to realising more capable and reliable autonomous systems across various domains, from autonomous mobility to space exploration.
Cite as
Sara Royuela, Adrian Munera, Chenle Yu, and Josep Pinot. HiPART: High-Performance Technology for Advanced Real-Time Systems. In 16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025). Open Access Series in Informatics (OASIcs), Volume 127, pp. 6:1-6:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)
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@InProceedings{royuela_et_al:OASIcs.PARMA-DITAM.2025.6,
author = {Royuela, Sara and Munera, Adrian and Yu, Chenle and Pinot, Josep},
title = {{HiPART: High-Performance Technology for Advanced Real-Time Systems}},
booktitle = {16th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 14th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2025)},
pages = {6:1--6:15},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-363-8},
ISSN = {2190-6807},
year = {2025},
volume = {127},
editor = {Cattaneo, Daniele and Fazio, Maria and Kosmidis, Leonidas and Morabito, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2025.6},
URN = {urn:nbn:de:0030-drops-229108},
doi = {10.4230/OASIcs.PARMA-DITAM.2025.6},
annote = {Keywords: Cyber-physical systems, OpenMP, Parallel and heterogeneous architectures, Efficiency, Adaptability, Interoperability, Real-time, Resilience, Reliability}
}