2015
Lu, Kewei
Portable Data Parallel Visualization Algorithms with VTK-m Presentation
05.10.2015, (LA-UR-15-27724).
Abstract | Links | BibTeX | Tags: data parallel, VTK-m
@misc{Lu2015,
title = {Portable Data Parallel Visualization Algorithms with VTK-m},
author = {Kewei Lu
},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/Portable_Data_Parallel_Visualization_Algorithms_with_VTK-m.pdf},
year = {2015},
date = {2015-10-05},
abstract = {This presentation summarizes summer work to develop portable data parallel visualization algorithms in VTK-m. This included writing visualization filters for streamlines and stream surfaces as well as modifying the original isosurface implementation using the new data model and worklets.},
note = {LA-UR-15-27724},
keywords = {data parallel, VTK-m},
pubstate = {published},
tppubtype = {presentation}
}
This presentation summarizes summer work to develop portable data parallel visualization algorithms in VTK-m. This included writing visualization filters for streamlines and stream surfaces as well as modifying the original isosurface implementation using the new data model and worklets.
2014
Sewell, Christopher
Streaming Data-Parallel Algorithms Enable Cosmology Data Analysis for Large Halos Presentation
31.12.2014, (LA-UR-14-29638).
Abstract | Links | BibTeX | Tags: cosmology, data parallel
@misc{Sewell2014,
title = {Streaming Data-Parallel Algorithms Enable Cosmology Data Analysis for Large Halos},
author = {Christopher Sewell },
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/Streaming_Data-Parallel_Algorithms_Enable_Cosmology_Data_Analysis_for_Large_Halos.pdf},
year = {2014},
date = {2014-12-31},
abstract = {This presentation given by Christopher Sewell describes how streaming data-parallel algorithms have enabled cosmology data analysis for large halos.},
note = {LA-UR-14-29638},
keywords = {cosmology, data parallel},
pubstate = {published},
tppubtype = {presentation}
}
This presentation given by Christopher Sewell describes how streaming data-parallel algorithms have enabled cosmology data analysis for large halos.
Sewell, Christopher; Lo, Li-ta; Francois, Marianne; Ahrens, James
Data-Parallel Programming with PISTON and PINION Presentation
30.08.2014, (LA-UR-14-26186).
Abstract | Links | BibTeX | Tags: data parallel, PINION, PISTON
@misc{Sewell2014b,
title = {Data-Parallel Programming with PISTON and PINION},
author = {Christopher Sewell and Li-ta Lo and Marianne Francois and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/Data-Parallel_Programming_with_PISTON_and_PINION.pdf},
year = {2014},
date = {2014-08-30},
abstract = {This presentation provides an introduction to data-parallel programming, NVIDIA's Thrust library, and our PISTON and PINION projects, which use this programming model to implement visualization and analysis operators, as well as simulation code.},
note = {LA-UR-14-26186},
keywords = {data parallel, PINION, PISTON},
pubstate = {published},
tppubtype = {presentation}
}
This presentation provides an introduction to data-parallel programming, NVIDIA's Thrust library, and our PISTON and PINION projects, which use this programming model to implement visualization and analysis operators, as well as simulation code.
Sewell, Christopher; Ahrens, James; Patchett, John
New Data-parallel Algorithms Accelerate Cosmology Data Analysis on GPUs Presentation
30.06.2014, (LA-UR-14-22054).
Abstract | Links | BibTeX | Tags: cosmo, cosmology, data parallel, gpu
@misc{Sewell2014b,
title = {New Data-parallel Algorithms Accelerate Cosmology Data Analysis on GPUs},
author = {Christopher Sewell and James Ahrens and John Patchett},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/New_Data-parallel_Algorithms_Accelerate_Cosmology_Data_Analysis_on_GPUs.pdf},
year = {2014},
date = {2014-06-30},
abstract = {This presentation describes how new data-parallel algorithms have accelerated cosmology data analysis on GPUs.},
note = {LA-UR-14-22054},
keywords = {cosmo, cosmology, data parallel, gpu},
pubstate = {published},
tppubtype = {presentation}
}
This presentation describes how new data-parallel algorithms have accelerated cosmology data analysis on GPUs.
Sewell, Christopher; Lo, Li-ta; Ahrens, James
PISTON Presentation
31.01.2014, (LA-UR-14-20028).
Abstract | Links | BibTeX | Tags: data parallel, PINION, PISTON
@misc{Sewell2014b,
title = {PISTON},
author = {Christopher Sewell and Li-ta Lo and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/PISTON.pdf},
year = {2014},
date = {2014-01-31},
abstract = {This set of two guest lectures provides an introductory tutorial to data-parallel programming and NVIDIA's Thrust library, as well as an overview of our research in out PISTON and PINION projects.},
note = {LA-UR-14-20028},
keywords = {data parallel, PINION, PISTON},
pubstate = {published},
tppubtype = {presentation}
}
This set of two guest lectures provides an introductory tutorial to data-parallel programming and NVIDIA's Thrust library, as well as an overview of our research in out PISTON and PINION projects.
2013
Sewell, Christopher
Portable Data-Parallel Visualization and Analysis Operators Presentation
20.03.2013, (LA-UR-13-21884).
Abstract | Links | BibTeX | Tags: data parallel, gpu, PINION, PISTON
@misc{Sewell2013,
title = {Portable Data-Parallel Visualization and Analysis Operators},
author = {Christopher Sewell},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/PortableDataParallelVisualizationAndAnalysisOperators.pdf},
year = {2013},
date = {2013-03-20},
abstract = {This presentation describes the overall goal of PISTON and PINION (to provide high parallel performance on current and next-generation supercomputers using portable, data-parallel code), and summarizes the work on these projects to date. It is intended for an audience at NVIDIA's GPU Technology Conference, and thus has an emphasis on how it uses Thrust to write code that obtains good parallel performance when compiled to different backends, including CUDA.},
note = {LA-UR-13-21884},
keywords = {data parallel, gpu, PINION, PISTON},
pubstate = {published},
tppubtype = {presentation}
}
This presentation describes the overall goal of PISTON and PINION (to provide high parallel performance on current and next-generation supercomputers using portable, data-parallel code), and summarizes the work on these projects to date. It is intended for an audience at NVIDIA's GPU Technology Conference, and thus has an emphasis on how it uses Thrust to write code that obtains good parallel performance when compiled to different backends, including CUDA.
: . .
1.
Lu, Kewei
Portable Data Parallel Visualization Algorithms with VTK-m Presentation
05.10.2015, (LA-UR-15-27724).
@misc{Lu2015,
title = {Portable Data Parallel Visualization Algorithms with VTK-m},
author = {Kewei Lu
},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/Portable_Data_Parallel_Visualization_Algorithms_with_VTK-m.pdf},
year = {2015},
date = {2015-10-05},
abstract = {This presentation summarizes summer work to develop portable data parallel visualization algorithms in VTK-m. This included writing visualization filters for streamlines and stream surfaces as well as modifying the original isosurface implementation using the new data model and worklets.},
note = {LA-UR-15-27724},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
This presentation summarizes summer work to develop portable data parallel visualization algorithms in VTK-m. This included writing visualization filters for streamlines and stream surfaces as well as modifying the original isosurface implementation using the new data model and worklets.
2.
Sewell, Christopher
Streaming Data-Parallel Algorithms Enable Cosmology Data Analysis for Large Halos Presentation
31.12.2014, (LA-UR-14-29638).
@misc{Sewell2014,
title = {Streaming Data-Parallel Algorithms Enable Cosmology Data Analysis for Large Halos},
author = {Christopher Sewell },
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/Streaming_Data-Parallel_Algorithms_Enable_Cosmology_Data_Analysis_for_Large_Halos.pdf},
year = {2014},
date = {2014-12-31},
abstract = {This presentation given by Christopher Sewell describes how streaming data-parallel algorithms have enabled cosmology data analysis for large halos.},
note = {LA-UR-14-29638},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
This presentation given by Christopher Sewell describes how streaming data-parallel algorithms have enabled cosmology data analysis for large halos.
3.
Sewell, Christopher; Lo, Li-ta; Francois, Marianne; Ahrens, James
Data-Parallel Programming with PISTON and PINION Presentation
30.08.2014, (LA-UR-14-26186).
@misc{Sewell2014b,
title = {Data-Parallel Programming with PISTON and PINION},
author = {Christopher Sewell and Li-ta Lo and Marianne Francois and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/Data-Parallel_Programming_with_PISTON_and_PINION.pdf},
year = {2014},
date = {2014-08-30},
abstract = {This presentation provides an introduction to data-parallel programming, NVIDIA's Thrust library, and our PISTON and PINION projects, which use this programming model to implement visualization and analysis operators, as well as simulation code.},
note = {LA-UR-14-26186},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
This presentation provides an introduction to data-parallel programming, NVIDIA's Thrust library, and our PISTON and PINION projects, which use this programming model to implement visualization and analysis operators, as well as simulation code.
4.
Sewell, Christopher; Ahrens, James; Patchett, John
New Data-parallel Algorithms Accelerate Cosmology Data Analysis on GPUs Presentation
30.06.2014, (LA-UR-14-22054).
@misc{Sewell2014b,
title = {New Data-parallel Algorithms Accelerate Cosmology Data Analysis on GPUs},
author = {Christopher Sewell and James Ahrens and John Patchett},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/New_Data-parallel_Algorithms_Accelerate_Cosmology_Data_Analysis_on_GPUs.pdf},
year = {2014},
date = {2014-06-30},
abstract = {This presentation describes how new data-parallel algorithms have accelerated cosmology data analysis on GPUs.},
note = {LA-UR-14-22054},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
This presentation describes how new data-parallel algorithms have accelerated cosmology data analysis on GPUs.
5.
Sewell, Christopher; Lo, Li-ta; Ahrens, James
PISTON Presentation
31.01.2014, (LA-UR-14-20028).
@misc{Sewell2014b,
title = {PISTON},
author = {Christopher Sewell and Li-ta Lo and James Ahrens},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/PISTON.pdf},
year = {2014},
date = {2014-01-31},
abstract = {This set of two guest lectures provides an introductory tutorial to data-parallel programming and NVIDIA's Thrust library, as well as an overview of our research in out PISTON and PINION projects.},
note = {LA-UR-14-20028},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
This set of two guest lectures provides an introductory tutorial to data-parallel programming and NVIDIA's Thrust library, as well as an overview of our research in out PISTON and PINION projects.
6.
Sewell, Christopher
Portable Data-Parallel Visualization and Analysis Operators Presentation
20.03.2013, (LA-UR-13-21884).
@misc{Sewell2013,
title = {Portable Data-Parallel Visualization and Analysis Operators},
author = {Christopher Sewell},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/08/PortableDataParallelVisualizationAndAnalysisOperators.pdf},
year = {2013},
date = {2013-03-20},
abstract = {This presentation describes the overall goal of PISTON and PINION (to provide high parallel performance on current and next-generation supercomputers using portable, data-parallel code), and summarizes the work on these projects to date. It is intended for an audience at NVIDIA's GPU Technology Conference, and thus has an emphasis on how it uses Thrust to write code that obtains good parallel performance when compiled to different backends, including CUDA.},
note = {LA-UR-13-21884},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
This presentation describes the overall goal of PISTON and PINION (to provide high parallel performance on current and next-generation supercomputers using portable, data-parallel code), and summarizes the work on these projects to date. It is intended for an audience at NVIDIA's GPU Technology Conference, and thus has an emphasis on how it uses Thrust to write code that obtains good parallel performance when compiled to different backends, including CUDA.