Hobbes: Difference between revisions
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| image = [[File:hobbes-logos.png]] | | image = [[File:hobbes-logos.png]] | ||
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| website = | | website = [http://xstack.sandia.gov/hobbes/ http://xstack.sandia.gov/hobbes/ ] | ||
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| pi = Ron Brightwell (SNL) | | pi = Ron Brightwell (SNL) | ||
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The goal of the Hobbes project is to deliver an operating system for future extreme-scale parallel computing platforms that will address the major technical challenges of energy efficiency, managing massive parallelism and deep memory hierarchies, and providing resilience in the presence of increasing failures. Our approach is to enable application composition through lightweight virtualization. Application composition is a critical capability that will be the foundation of the way extreme-scale systems must be used in the future. The tighter integration of modeling and simulation capability with analysis and the increasing complexity of application workflows demand more sophisticated machine usage models and new system-level services. Ensemble calculations for uncertainty quantification, large graph analytics, multi-materials and multi-physics applications are just a few examples that are driving the need for these new system software interfaces and mechanisms for managing memory, network, and computational resources. Rather than providing a single unified operating system and runtime system that supports several parallel programming models, Hobbes is leveraging lightweight virtualization to provide the flexibility to construct and efficiently execute custom OS/R environments. Hobbes extends our existing work on the [https://software.sandia.gov/trac/kitten Kitten] lightweight operating system and the [http://v3vee.org/palacios/ Palacios] lightweight virtual machine monitor. | The goal of the Hobbes project is to deliver an operating system for future extreme-scale parallel computing platforms that will address the major technical challenges of energy efficiency, managing massive parallelism and deep memory hierarchies, and providing resilience in the presence of increasing failures. Our approach is to enable application composition through lightweight virtualization. Application composition is a critical capability that will be the foundation of the way extreme-scale systems must be used in the future. The tighter integration of modeling and simulation capability with analysis and the increasing complexity of application workflows demand more sophisticated machine usage models and new system-level services. Ensemble calculations for uncertainty quantification, large graph analytics, multi-materials and multi-physics applications are just a few examples that are driving the need for these new system software interfaces and mechanisms for managing memory, network, and computational resources. Rather than providing a single unified operating system and runtime system that supports several parallel programming models, Hobbes is leveraging lightweight virtualization to provide the flexibility to construct and efficiently execute custom OS/R environments. Hobbes extends our existing work on the [https://software.sandia.gov/trac/kitten Kitten] lightweight operating system and the [http://v3vee.org/palacios/ Palacios] lightweight virtual machine monitor. | ||
== Products == | |||
This [https://xstackwiki.modelado.org/images/2/23/Hobbes-Products-v2.pdf document] lists all of the software and publications resulting from the Hobbes project. | |||
== Team Members == | == Team Members == | ||
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* [http://www.cs.unm.edu University of New Mexico (UNM)] | * [http://www.cs.unm.edu University of New Mexico (UNM)] | ||
* [http://www.cs.pitt.edu University of PIttsburgh (Pitt)] | * [http://www.cs.pitt.edu University of PIttsburgh (Pitt)] | ||
Latest revision as of 18:27, August 16, 2016
| Hobbes | |
|---|---|
 | |
| Team Members | |
| PI | Ron Brightwell (SNL) |
| Chief Scientist | Barney Maccabe (ORNL) |
| Co-PIs | Costin Iancu (LBL), Mike Lang (LANL), David Bernholdt (ORNL), Karsten Schwan (GT), Thomas Sterling (IU), Frank Mueller (NCSU), Peter Dinda (NU), David Lowenthal (UA), Eric Brewer (UCB), Patrick Bridges (UNM), Jack Lange (Pitt) |
| Website | http://xstack.sandia.gov/hobbes/ |
The goal of the Hobbes project is to deliver an operating system for future extreme-scale parallel computing platforms that will address the major technical challenges of energy efficiency, managing massive parallelism and deep memory hierarchies, and providing resilience in the presence of increasing failures. Our approach is to enable application composition through lightweight virtualization. Application composition is a critical capability that will be the foundation of the way extreme-scale systems must be used in the future. The tighter integration of modeling and simulation capability with analysis and the increasing complexity of application workflows demand more sophisticated machine usage models and new system-level services. Ensemble calculations for uncertainty quantification, large graph analytics, multi-materials and multi-physics applications are just a few examples that are driving the need for these new system software interfaces and mechanisms for managing memory, network, and computational resources. Rather than providing a single unified operating system and runtime system that supports several parallel programming models, Hobbes is leveraging lightweight virtualization to provide the flexibility to construct and efficiently execute custom OS/R environments. Hobbes extends our existing work on the Kitten lightweight operating system and the Palacios lightweight virtual machine monitor.
Products
This document lists all of the software and publications resulting from the Hobbes project.
Team Members
- Sandia National Laboratories (SNL)
- Oak Ridge National Laboratory (ORNL)
- Lawrence Berkeley National Laboratory (LBL)
- Los Alamos National Laboratory (LANL)
- Georgia Institute of Technology (GT)
- Indiana University (IU)
- North Carolina State University (NCSU)
- Northwestern University (NU)
- University of Arizona (UA)
- University of California - Berkeley (UCB)
- University of New Mexico (UNM)
- University of PIttsburgh (Pitt)