8 Search Results for "Soudris, Dimitrios"


Artifact
Software
FPGAScheduler

Authors: Aggelos Ferikoglou


Abstract

Cite as

Aggelos Ferikoglou. FPGAScheduler (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@misc{dagstuhl-artifact-25581,
   title = {{FPGAScheduler}}, 
   author = {Ferikoglou, Aggelos},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:2941cf80f4a5b396622da5ebb3f1fb76ffae7b8b;origin=https://github.com/aferikoglou/FPGAScheduler;visit=swh:1:snp:901fb2866292917bb3ed2a4e9973317816eb0787;anchor=swh:1:rev:a7ed7d4ed62bc17fd412752ec49f59cf8f313499}{\texttt{swh:1:dir:2941cf80f4a5b396622da5ebb3f1fb76ffae7b8b}} (visited on 2026-04-10)},
   url = {https://github.com/aferikoglou/FPGAScheduler},
   doi = {10.4230/artifacts.25581},
}
Document
Linking High-Level Synthesis with FPGA Runtime Orchestration

Authors: Despoina Tomkou, Aggelos Ferikoglou, Dimosthenis Masouros, Sotirios Xydis, and Dimitrios Soudris

Published in: OASIcs, Volume 141, 17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026)


Abstract
FPGAs are increasingly being adopted across the edge-to-cloud continuum due to their ability to provide both high performance and energy efficiency. However, the complexity of programming FPGAs often leads to deployed designs that underutilize available resources. FPGA multi-tenancy has been proposed to enhance resource utilization, yet monolithic designs and dynamic workload demands continue to challenge efficient FPGA usage and compliance with Quality of Service requirements. To address these issues, we propose a novel framework for the optimal orchestration of FPGAs across the edge-to-cloud continuum while meeting user demands. The framework generates approximations of Pareto-optimal designs for each application, capturing trade-offs between performance and resource usage with minimal bitstream generation. This information allows the runtime orchestrator to select the most suitable design based on available PR regions and the QoS requirements of each user. Experimental results demonstrate that the proposed approach achieves an average reduction of QoS violations by a factor of 8.1× across diverse workloads and baseline configurations. Overall, the framework offers a practical and effective solution for realizing FPGA-as-a-Service across the edge-to-cloud continuum.

Cite as

Despoina Tomkou, Aggelos Ferikoglou, Dimosthenis Masouros, Sotirios Xydis, and Dimitrios Soudris. Linking High-Level Synthesis with FPGA Runtime Orchestration. In 17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026). Open Access Series in Informatics (OASIcs), Volume 141, pp. 7:1-7:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{tomkou_et_al:OASIcs.PARMA-DITAM.2026.7,
  author =	{Tomkou, Despoina and Ferikoglou, Aggelos and Masouros, Dimosthenis and Xydis, Sotirios and Soudris, Dimitrios},
  title =	{{Linking High-Level Synthesis with FPGA Runtime Orchestration}},
  booktitle =	{17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026)},
  pages =	{7:1--7:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-416-1},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{141},
  editor =	{Baroffio, Davide and Busia, Paola and Denisov, Lev and Shukla, Nitin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2026.7},
  URN =		{urn:nbn:de:0030-drops-256746},
  doi =		{10.4230/OASIcs.PARMA-DITAM.2026.7},
  annote =	{Keywords: FPGA, Orchestration, Partial Reconfiguration, FPGAaaS}
}
Document
Performance Modeling & Mapping of LLM Inference on Heterogeneous Vectorized CGRAs

Authors: Dionysios Kefallinos, Georgios Alexandris, Alexis Maras, Panagiotis Chaidos, Manil Dev Gomony, Henk Corporaal, Dimitrios Soudris, and Sotirios Xydis

Published in: OASIcs, Volume 141, 17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026)


Abstract
Since the emergence of transformer-based models, the computational demands for Large Language Model (LLM) inference have been increasing exponentially, primarily due to their compounding parameter sizes, their structural complexity, and the use of non-linear functions. This tendency leads to the necessity of deploying them on low-power edge devices and DNN accelerators, to fuel next-generation agentic AI systems. Coarse-Grained Reconfigurable Architectures (CGRAs) have proven to be a compelling paradigm for edge acceleration, combining the programmability of general-purpose platforms with the high performance and energy efficiency associated with ASICs. In this work, we introduce an end-to-end performance modeling and mapping framework for LLM inference on heterogeneous CGRAs. Our methodology enables rapid exploration of the micro-architectural design space parameters, i.e., the number of processing elements, vector sizes, and memory configurations, by providing an accurate, explainable, and analytical CGRA performance modeling methodology, with an average cycle error of 0.9%. Architecturally, we build upon R-Blocks, a heterogeneous CGRA platform, and extend it to support floating-point arithmetic operations as well as a full-stack compilation and mapping flow for both full (FP32) and quantized (INT8) Llama2 models. The proposed methodology, evaluated on a 22nm technology node, achieves superior peak performance per Watt compared to related works such as REVAMP and CFEACT (1.8× and 2.8× respectively).

Cite as

Dionysios Kefallinos, Georgios Alexandris, Alexis Maras, Panagiotis Chaidos, Manil Dev Gomony, Henk Corporaal, Dimitrios Soudris, and Sotirios Xydis. Performance Modeling & Mapping of LLM Inference on Heterogeneous Vectorized CGRAs. In 17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026). Open Access Series in Informatics (OASIcs), Volume 141, pp. 8:1-8:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{kefallinos_et_al:OASIcs.PARMA-DITAM.2026.8,
  author =	{Kefallinos, Dionysios and Alexandris, Georgios and Maras, Alexis and Chaidos, Panagiotis and Gomony, Manil Dev and Corporaal, Henk and Soudris, Dimitrios and Xydis, Sotirios},
  title =	{{Performance Modeling \& Mapping of LLM Inference on Heterogeneous Vectorized CGRAs}},
  booktitle =	{17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026)},
  pages =	{8:1--8:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-416-1},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{141},
  editor =	{Baroffio, Davide and Busia, Paola and Denisov, Lev and Shukla, Nitin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2026.8},
  URN =		{urn:nbn:de:0030-drops-256752},
  doi =		{10.4230/OASIcs.PARMA-DITAM.2026.8},
  annote =	{Keywords: Edge AI, LLM, CGRA, Heterogeneous Architectures, Performance Modeling, Hardware Acceleration, Low Power Computing}
}
Document
DAMA: A Dual Arbitration Mechanism for Mixed-Criticality Applications

Authors: Wafic Lawand and Rodolfo Pellizzoni

Published in: LIPIcs, Volume 335, 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)


Abstract
We discuss hardware resource management in mixed-criticality systems, where requestors may issue latency-critical (LTC) and non-latency-critical (NLTC) requests. LTC requests must adhere to strict latency bounds imposed by safety-critical applications, but timely servicing NLTC requests is necessary to maximize overall system performance in the average case. In this paper, we address this tradeoff for a shared memory resource by proposing DAMA, a dual arbitration mechanism that imposes an upper bound on the cumulative latency of LTC requests without unduly impacting NLTC performance. DAMA comprises a high-performance arbiter, a real-time arbiter, and a mechanism that constantly monitors the cumulative latency of requests suffered by each requestor. DAMA primarily executes in high-performance mode and only switches to real-time mode in the rare instances when its incorporated mechanism detects a violation of a task’s timing guarantee. We demonstrate the effectiveness of our arbitration scheme by adapting a predictable prefetcher that issues NLTC requests and attaching it to the L1 caches of our cores. We show both formally and experimentally that DAMA provides timing guarantees for LTC requests while processing other NLTC requests. We also demonstrate that with a negligible overhead of less than 1.5% on the cumulative latency bound of LTC requests, DAMA can achieve an equivalent average performance to a prefetcher that processes requests under a high-performance arbitration scheme.

Cite as

Wafic Lawand and Rodolfo Pellizzoni. DAMA: A Dual Arbitration Mechanism for Mixed-Criticality Applications. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 9:1-9:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{lawand_et_al:LIPIcs.ECRTS.2025.9,
  author =	{Lawand, Wafic and Pellizzoni, Rodolfo},
  title =	{{DAMA: A Dual Arbitration Mechanism for Mixed-Criticality Applications}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{9:1--9:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-377-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{335},
  editor =	{Mancuso, Renato},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2025.9},
  URN =		{urn:nbn:de:0030-drops-235875},
  doi =		{10.4230/LIPIcs.ECRTS.2025.9},
  annote =	{Keywords: Real-time Systems, Mixed-criticality Applications, Memory controllers, Prefetchers}
}
Document
System-Level Timing Performance Estimation Based on a Unifying HW/SW Performance Metric

Authors: Vittoriano Muttillo, Vincenzo Stoico, Giacomo Valente, Marco Santic, Luigi Pomante, and Daniele Frigioni

Published in: 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)


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
Custom Floating-Point Computations for the Optimization of ODE Solvers on FPGA

Authors: Serena Curzel and Marco Gribaudo

Published in: 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)


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
Adjacent LSTM-Based Page Scheduling for Hybrid DRAM/NVM Memory Systems

Authors: Manolis Katsaragakis, Konstantinos Stavrakakis, Dimosthenis Masouros, Lazaros Papadopoulos, and Dimitrios Soudris

Published in: OASIcs, Volume 107, 14th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 12th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2023)


Abstract
Recent advances in memory technologies have led to the rapid growth of hybrid systems that combine traditional DRAM and Non Volatile Memory (NVM) technologies, as the latter provide lower cost per byte, low leakage power and larger capacities than DRAM, while they can guarantee comparable access latency. Such kind of heterogeneous memory systems impose new challenges in terms of page placement and migration among the alternative technologies of the heterogeneous memory system. In this paper, we present a novel approach for efficient page placement on heterogeneous DRAM/NVM systems. We design an adjacent LSTM-based approach for page placement, which strongly relies on page accesses prediction, while sharing knowledge among pages with behavioral similarity. The proposed approach leads up to 65.5% optimized performance compared to existing approaches, while achieving near-optimal results and saving 20.2% energy consumption on average. Moreover, we propose a new page replacement policy, namely clustered-LRU, achieving up to 8.1% optimized performance, compared to the default Least Recently Used (LRU) policy.

Cite as

Manolis Katsaragakis, Konstantinos Stavrakakis, Dimosthenis Masouros, Lazaros Papadopoulos, and Dimitrios Soudris. Adjacent LSTM-Based Page Scheduling for Hybrid DRAM/NVM Memory Systems. In 14th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 12th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2023). Open Access Series in Informatics (OASIcs), Volume 107, pp. 7:1-7:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{katsaragakis_et_al:OASIcs.PARMA-DITAM.2023.7,
  author =	{Katsaragakis, Manolis and Stavrakakis, Konstantinos and Masouros, Dimosthenis and Papadopoulos, Lazaros and Soudris, Dimitrios},
  title =	{{Adjacent LSTM-Based Page Scheduling for Hybrid DRAM/NVM Memory Systems}},
  booktitle =	{14th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 12th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2023)},
  pages =	{7:1--7:12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-269-3},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{107},
  editor =	{Bispo, Jo\~{a}o and Charles, Henri-Pierre and Cherubin, Stefano and Massari, Giuseppe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2023.7},
  URN =		{urn:nbn:de:0030-drops-177278},
  doi =		{10.4230/OASIcs.PARMA-DITAM.2023.7},
  annote =	{Keywords: Page Placement, Long Short-Term Memory, LSTM, Prediction, NVM, DRAM}
}
Document
Resource Aware GPU Scheduling in Kubernetes Infrastructure

Authors: Aggelos Ferikoglou, Dimosthenis Masouros, Achilleas Tzenetopoulos, Sotirios Xydis, and Dimitrios Soudris

Published in: OASIcs, Volume 88, 12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021)


Abstract
Nowadays, there is an ever-increasing number of artificial intelligence inference workloads pushed and executed on the cloud. To effectively serve and manage the computational demands, data center operators have provisioned their infrastructures with accelerators. Specifically for GPUs, support for efficient management lacks, as state-of-the-art schedulers and orchestrators, threat GPUs only as typical compute resources ignoring their unique characteristics and application properties. This phenomenon combined with the GPU over-provisioning problem leads to severe resource under-utilization. Even though prior work has addressed this problem by colocating applications into a single accelerator device, its resource agnostic nature does not manage to face the resource under-utilization and quality of service violations especially for latency critical applications. In this paper, we design a resource aware GPU scheduling framework, able to efficiently colocate applications on the same GPU accelerator card. We integrate our solution with Kubernetes, one of the most widely used cloud orchestration frameworks. We show that our scheduler can achieve 58.8% lower end-to-end job execution time 99%-ile, while delivering 52.5% higher GPU memory usage, 105.9% higher GPU utilization percentage on average and 44.4% lower energy consumption on average, compared to the state-of-the-art schedulers, for a variety of ML representative workloads.

Cite as

Aggelos Ferikoglou, Dimosthenis Masouros, Achilleas Tzenetopoulos, Sotirios Xydis, and Dimitrios Soudris. Resource Aware GPU Scheduling in Kubernetes Infrastructure. In 12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021). Open Access Series in Informatics (OASIcs), Volume 88, pp. 4:1-4:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{ferikoglou_et_al:OASIcs.PARMA-DITAM.2021.4,
  author =	{Ferikoglou, Aggelos and Masouros, Dimosthenis and Tzenetopoulos, Achilleas and Xydis, Sotirios and Soudris, Dimitrios},
  title =	{{Resource Aware GPU Scheduling in Kubernetes Infrastructure}},
  booktitle =	{12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021)},
  pages =	{4:1--4:12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-181-8},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{88},
  editor =	{Bispo, Jo\~{a}o and Cherubin, Stefano and Flich, Jos\'{e}},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2021.4},
  URN =		{urn:nbn:de:0030-drops-136403},
  doi =		{10.4230/OASIcs.PARMA-DITAM.2021.4},
  annote =	{Keywords: cloud computing, GPU scheduling, kubernetes, heterogeneity}
}
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