Applications: Difference between revisions
From Modelado Foundation
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= Sandia's Task-DAG R&D 2014-2016 = | = Sandia's Task-DAG R&D 2014-2016 = | ||
https://wiki.modelado.org/images/d/d6/SAND2016-9613.pdf | [https://wiki.modelado.org/images/d/d6/SAND2016-9613.pdf Sandia's Task-DAG LDRD report] | ||
Sandia conducted a three year laboratory directed research and development (LDRD) effort to explore on-node, performance portable directed acyclic graph (DAG) of tasks parallel pattern, usage algorithms, application programmer interface, scheduling algorithms, and implementations. Of significance this LDRD used C++ meta-programming to achieve performance portability across CPU and NVIDIA GPU (CUDA) architectures. The above document is the final report for this R&D. | Sandia conducted a three year laboratory directed research and development (LDRD) effort to explore on-node, performance portable directed acyclic graph (DAG) of tasks parallel pattern, usage algorithms, application programmer interface, scheduling algorithms, and implementations. Of significance this LDRD used C++ meta-programming to achieve performance portability across CPU and NVIDIA GPU (CUDA) architectures. The above document is the final report for this R&D. |
Revision as of 17:37, January 17, 2017
The propose of this page is to gather user applications that serve as poster children for HHAT.
Please this this approach
- Create a new subsection for each application, with two equal signs and a space around the title of each app
- Include the content in the template below
CORAL apps
Collaboration of Oak Ridge, Argonne and Livermore
APEX apps
Alliance for Application Performance at Extreme Scale
ECP apps
Exascale computing project
PASC apps
Platform for Advanced Scientific Computing, Switzerland
ISV apps
Sandia's Task-DAG R&D 2014-2016
Sandia conducted a three year laboratory directed research and development (LDRD) effort to explore on-node, performance portable directed acyclic graph (DAG) of tasks parallel pattern, usage algorithms, application programmer interface, scheduling algorithms, and implementations. Of significance this LDRD used C++ meta-programming to achieve performance portability across CPU and NVIDIA GPU (CUDA) architectures. The above document is the final report for this R&D.
The prototype developed through this LDRD is currently (2017) being matured (overhauled) to address performance issues and elevate to production quality. This effort is scheduled for delivery within Kokkos by September 2017.
Add more
Template
Application 1
- Brief description of app and its business importance
- Brief description of app domain
- Qualitative or quantitative analysis of where and how it would benefit from HHAT
- Expected time table for delivery of a solution (e.g. readiness for the arrival of a new supercomputer at a USG lab), and resources available to implement it with HHAT
- purpose: identify apps that could lead vehicles that drive the development of an open source project and that would be a poster child that would build confidence for others to follow