The DreamCloud Project

The main objective addressed by DreamCloud is to enable dynamic resource allocation in many- core embedded and high performance systems while providing appropriate guarantees on performance and energy efficiency.

DreamCloud will address techniques to allocate computation and communication workloads onto computing platforms during run-time whilst respecting performance and energy budget requirements. To achieve this, DreamCloud brings together teams from embedded computing and high- performance computing (HPC) to address these common ambitious yet achievable goals:

  • Provide complex embedded systems with cloud-like capabilities such as those available in today’s high-performance computing, allowing them to dynamically tune resource usage but without sacrificing critical application-specific constraints in performance and energy.
  • Enable HPC and cloud computing systems to balance workload and manage resources so that they can offer more meaningful guarantees in terms of performance and energy, focussing not only on improving average behaviour but also on reducing variability and upper bounds of timing and energy metrics.

DreamCloud brings together industrial partners from deeply embedded systems (e.g. automotive), consumer embedded systems (e.g. household media), and high performance computing (e.g. HPC platforms); academic partners from embedded systems, real-time systems and HPC. This will enable DreamCloud to develop better approaches by  cross-fertilising  expertise  and  experience from  multiple  industrial  domains  and  academic  communities.

Click the video below for an introduction to the project and technologies being developed.

News

  • Best Paper Award - IEEE ISORC 2016

    The DreamCloud team at York has received the Best Paper Award at the 19th IEEE International Symposium on Real-Time Distributed Computing (ISORC), with the paper "Energy-Aware Resource Allocation in Multi-Mode Automotive Applications with Hard Real-Time Constraints" authored by Piotr Dziurzanski, Amit Kumar Singh and Leandro Soares Indrusiak. Besides the winning paper, the paper on "Value and Energy Aware Adaptive Resource Allocation of Soft Real-time Jobs on Many-core HPC Data Centers", by the…

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    Started by Leandro Soares Indrusiak 0 Replies
  • Source Code of Interval Algebra with Genetic Algorithm Available Online

    The source code has been made available online GitHub Link The installation and usage instructions are provided in the file Description.odt available within the source.

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    Started by Amit Kumar Singh 0 Replies
  • Paper presented at ARCS 2016 conference

    A paper titled "Feedback-Based Admission Control for Hard Real-Time Task Allocation under Dynamic Workload on Many-core Systems" was presented at 2016 International Conference on Architecture of Computing Systems (ARCS), Nuremberg, Germany, April 2016. The ARCS series of conferences has over 30 years of tradition reporting high quality results in computer architecture and operating systems research. The focus of the 2016 conference was on Heterogeneity in Architectures and Systems - From…

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    Started by Amit Kumar Singh 0 Replies · Reply by Amit Kumar Singh Apr 28
  • New DreamCloud simulators available online

    The latest versions of our Manycore platform Simulation tool-suite (McSim) and AMALTHEA-Simgrid simulator are available on DreamCloud's Github link (https://github.com/DreamCloud-Project). McSim targets embedded manycore systems while AMALTHEA-Simgrid focuses on cloud/HPC systems. Give them a try and send us your feedback!

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    Started by Abdoulaye Gamatié 0 Replies

DreamCloud is a Specific Targeted Research Project (STREP) of the Seventh Framework Programme for research and technological development (FP7) - the European Union's chief instrument for funding research projects that commence over the period 2007 to 2013.


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Project Partners