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Träfflista för sökning "WFRF:(Xydis Sotirios) "

Sökning: WFRF:(Xydis Sotirios)

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1.
  • Anagnostopoulos, Iraklis, et al. (författare)
  • Custom Microcoded Dynamic Memory Management for Distributed On-Chip Memory Organizations
  • 2011
  • Ingår i: IEEE Embedded Systems Letters. - 1943-0663. ; 3:2, s. 66-69
  • Tidskriftsartikel (refereegranskat)abstract
    • Multiprocessor system-on-chip (MPSoCs) have attracted significant attention since they are recognized as a scalable paradigm to interconnect and organize a high number of cores. Current multicore embedded systems exhibit increased levels of dynamicbehavior, leading to unexpected memory footprint variations unknown at design time.Dynamic memory management (DMM) is a promising solution for such types of dynamicsystems. Although some efficient dynamic memory managers have been proposed for conventional bus-based MPSoC platforms, there are no DMM solutions regarding the constraints and the opportunities delivered by the physical distribution of multiple memorynodes of the platform. In this work, we address the problem of providing customizedmicrocoded DMM on MPSoC platforms with distributed memory organization. Customization is enabled at application-and platform-level. Results show that customizedmicrocoded DMM can serve approximately 7× more allocation requests compared to puredistributed memory platforms and perform 25% faster than the corresponding high-level implementation in C language. 
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2.
  • Candaele, Bernard, et al. (författare)
  • Mapping Optimisation for Scalable multi-core ARchiTecture : The MOSART approach
  • 2010
  • Ingår i: Proceedings - IEEE Annual Symposium on VLSI, ISVLSI 2010. - 9780769540764 ; , s. 518-523
  • Konferensbidrag (refereegranskat)abstract
    • The project will address two main challenges of prevailing architectures: 1) The global Interconnect and memory bottleneck due to a single, globally shared memory with high access times and power consumption; 2) The difficulties in programming heterogeneous, multi-core platforms, in particular in dynamically managing data structures in distributed memory. MOSART aims to overcome these through a multi-core architecture with distributed memory organisation, a Network-on-Chip (NoC) communication backbone and configurable processing cores that are scaled, optimised and customised together to achieve diverse energy, performance, cost and size requirements of different classes of applications. MOSART achieves this by: A) Providing platform support for management of abstract data structures Including middleware services and a run-time data manager for NoC based communication infrastructure; 2) Developing tool support for parallelizing and mapping applications on the multi-core target platform and customizing the processing cores for the application.
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3.
  • Candaele, Bernard, et al. (författare)
  • The MOSART Mapping Optimization for multi-core Architectures
  • 2011
  • Ingår i: VLSI 2010 Annual Symposium. - Dordrecht : Springer Publishing Company. ; , s. 181-195
  • Konferensbidrag (refereegranskat)abstract
    • MOSART project addresses two main challenges of prevailing architectures: (i) Theglobal interconnect and memory bottleneck due to a single, globally shared memorywith high access times and power consumption; (ii) The difficulties in programmingheterogeneous, multi-core platforms MOSART aims to overcome these through amulti-core architecture with distributed memory organization, a Network-on-Chip(NoC) communication backbone and configurable processing cores that are scaled,optimized and customized together to achieve diverse energy, performance, cost andsize requirements of different classes of applications. MOSART achieves this by:(i) Providing platform support for management of abstract data structures includingmiddleware services and a run-time data manager for NoC based communicationinfrastructure; (ii) Developing tool support for parallelizing and mapping applicationson the multi-core target platform and customizing the processing cores for theapplication.
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4.
  • Koliogeorgi, Konstantina, et al. (författare)
  • Auto-tuning Multi-GPU High-Fidelity Numerical Simulations for Urban Air Mobility
  • 2024
  • Ingår i: 2024 Design, Automation and Test in Europe Conference and Exhibition, DATE 2024 - Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE).
  • Konferensbidrag (refereegranskat)abstract
    • The aviation field is rapidly evolving towards an era where both typical aviation and Unmanned Aicraft Systems are essential and co-exist in the same airspace. This new territory raises important concerns regarding environmental impact, safety and societal acceptance. The RefMap European Project is an initiative that addresses these issues and aims at optimizing air traffic in terms of the environmental footprint in aviation and drone flights. One of RefMap's objectives is the development of powerful deep-learning models that predict urban flow based on extensive CFD simulations. The excessive time requirements of CFD simulations require the computational power of exascale heterogeneous supercomputer clusters. This work presents RefMap's strategy to mitigate simulation to GPU-enabled high-class solvers and further leverage sophisticated autotuning HPC techniques for creating portable high-performance simulations that can efficiently run on any GPU architecture and parallel system.
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5.
  • Soudris, Dimitrios, et al. (författare)
  • AEGLE : A Big Bio-Data Analytics Framework for Integrated Health-Care Services
  • 2015
  • Ingår i: Proceedings International Conference on Embedded Computer Systems - Architectures, Modeling and Simulation (SAMOS XV). - 9781467373111 ; , s. 246-253
  • Konferensbidrag (refereegranskat)abstract
    • AEGLE project(1) targets to build an innovative ICT solution addressing the whole data value chain for health based on: cloud computing enabling dynamic resource allocation, HPC infrastructures for computational acceleration and advanced visualization techniques. In this paper, we provide an analysis of the addressed Big Data health scenarios and we describe the key enabling technologies, as well as data privacy and regulatory issues to be integrated into AEGLE's ecosystem, enabling advanced health-care analytic services, while also promoting related research activities.
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