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GTC ON-DEMAND

Presentation
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Abstract:
We are working with NVIDIA to lower the barrier of scientific understanding by improving the communication tools that scientists will have access to. NVIDIA has been working with Kitware to not only bring NVIDIA RTX support to ParaView, but allow ParaView users to access the omniverse. Come see how advancements in ParaView will unlock the next generation of visualization communication/collaboration techniques for your science.
We are working with NVIDIA to lower the barrier of scientific understanding by improving the communication tools that scientists will have access to. NVIDIA has been working with Kitware to not only bring NVIDIA RTX support to ParaView, but allow ParaView users to access the omniverse. Come see how advancements in ParaView will unlock the next generation of visualization communication/collaboration techniques for your science.  Back
 
Topics:
HPC and Supercomputing
Type:
Talk
Event:
Supercomputing
Year:
2019
Session ID:
SC1915
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Abstract:
Learn about CMake and find out how to use its native CUDA support, which allows users to fully leverage modern target-based features inside projects that require CUDA compilation. We'll show how we iteratively develop the CMake logic for a sample project using modern CMake with a focus on CUDA. We'll cover transitive usage requirements, how to request language standard levels, mixed language libraries, CUDA separable compilation, and generating export configuration files. Participants should have some familiarity with the concept of build systems.
Learn about CMake and find out how to use its native CUDA support, which allows users to fully leverage modern target-based features inside projects that require CUDA compilation. We'll show how we iteratively develop the CMake logic for a sample project using modern CMake with a focus on CUDA. We'll cover transitive usage requirements, how to request language standard levels, mixed language libraries, CUDA separable compilation, and generating export configuration files. Participants should have some familiarity with the concept of build systems.  Back
 
Topics:
Tools & Libraries
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9444
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Abstract:
We'll discuss the VTK-m project, an HPC library for scientific visualization algorithms, and describe how it changed over the past three years. Part of the Exascale Computing Project, VTK-m is designed around fine-grained concurrency and an abstraction between the low-level hardware architectures and the data-parallel high-level code. This allows developers to write small worklets that can be executed on any hardware. We'll examine significant performance and development lessons learned since the VTK-m project began and talk about the challenges we see ahead.
We'll discuss the VTK-m project, an HPC library for scientific visualization algorithms, and describe how it changed over the past three years. Part of the Exascale Computing Project, VTK-m is designed around fine-grained concurrency and an abstraction between the low-level hardware architectures and the data-parallel high-level code. This allows developers to write small worklets that can be executed on any hardware. We'll examine significant performance and development lessons learned since the VTK-m project began and talk about the challenges we see ahead.  Back
 
Topics:
In-Situ & Scientific Visualization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9458
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Abstract:
The VTK-m project is a library to enable scientific visualization algorithms across a range of GPU's and Accelerator's and CPU's. VTK-m is designed around fine-grained concurrency and provides a flexible data and execution models. The abstraction between the low-level hardware architectures and the data parallel high-level code, allows for algorithms to be designed independently of where they are going to be executed. We will cover not only the status of the existing VTK-m algorithms, and the supporting architecture, but will talk about the unique challenges and solutions for writing performance oriented code that targets multiple hardware architectures.
The VTK-m project is a library to enable scientific visualization algorithms across a range of GPU's and Accelerator's and CPU's. VTK-m is designed around fine-grained concurrency and provides a flexible data and execution models. The abstraction between the low-level hardware architectures and the data parallel high-level code, allows for algorithms to be designed independently of where they are going to be executed. We will cover not only the status of the existing VTK-m algorithms, and the supporting architecture, but will talk about the unique challenges and solutions for writing performance oriented code that targets multiple hardware architectures.  Back
 
Topics:
In-Situ & Scientific Visualization, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8450
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Abstract:

Learn all about CMake's new CUDA support and how best to combine it with "modern" CMake usage requirements. CMake is an open-source, cross-platform meta build generator. This year CMake was updated to fully support CUDA as a first-class language on all major platforms. This enables projects to fully leverage "modern" target-based features inside projects that require CUDA compilation. We'll iteratively develop the CMake logic for a sample project using modern CMake with a focus on CUDA. We'll cover transitive usage requirements, how to request language standard levels, mix language libraries, CUDA separable compilation, and generating export configuration files. We expect people to already have some familiarity with the CMake language.

Learn all about CMake's new CUDA support and how best to combine it with "modern" CMake usage requirements. CMake is an open-source, cross-platform meta build generator. This year CMake was updated to fully support CUDA as a first-class language on all major platforms. This enables projects to fully leverage "modern" target-based features inside projects that require CUDA compilation. We'll iteratively develop the CMake logic for a sample project using modern CMake with a focus on CUDA. We'll cover transitive usage requirements, how to request language standard levels, mix language libraries, CUDA separable compilation, and generating export configuration files. We expect people to already have some familiarity with the CMake language.

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Topics:
Tools & Libraries
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7438
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Abstract:
Learn about how the latest changes to VTK, VTK-m, and Catalyst are allowing for better GPU-accelerated rendering and compute. We'll give an overview of the latest changes to VTK's rendering infrastructure, VTK-m compute capabilities, and Catalyst. Lastly, we'll demonstrate the results of this work by showing the results of an in-situ visualization of PYFR GPU simulation.
Learn about how the latest changes to VTK, VTK-m, and Catalyst are allowing for better GPU-accelerated rendering and compute. We'll give an overview of the latest changes to VTK's rendering infrastructure, VTK-m compute capabilities, and Catalyst. Lastly, we'll demonstrate the results of this work by showing the results of an in-situ visualization of PYFR GPU simulation.  Back
 
Topics:
In-Situ & Scientific Visualization, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6193
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Abstract:
The Visualization Toolkit (VTK) is an open source scientific visualization framework. We will describe the new VTK rendering backend which targets modern GPUs, taking advantage of the flexible programmable pipeline. This has resulted in significant improvements in rendering performance, especially with large geometries (20 million+ triangles) being rendered over 100 times faster, without significant API changes, with near identical rendering. This offers a drop-in replacement for existing applications, and a turn-key open source visualization framework for new applications. The VTK-M offers highly parallel and efficient algorithms for scientific data. The architecture, and how it will interact with VTK will be discussed.
The Visualization Toolkit (VTK) is an open source scientific visualization framework. We will describe the new VTK rendering backend which targets modern GPUs, taking advantage of the flexible programmable pipeline. This has resulted in significant improvements in rendering performance, especially with large geometries (20 million+ triangles) being rendered over 100 times faster, without significant API changes, with near identical rendering. This offers a drop-in replacement for existing applications, and a turn-key open source visualization framework for new applications. The VTK-M offers highly parallel and efficient algorithms for scientific data. The architecture, and how it will interact with VTK will be discussed.  Back
 
Topics:
Visualization - In-Situ & Scientific
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5604
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Abstract:

Explore new techniques in scientific data analysis and visualization algorithms by looking at Dax toolkit which provides a development framework for the next generation of high-performance computers and GPU''s. Dax provides a concept mechanism to automatically build parallel scheduling code from signatures using C++.

Explore new techniques in scientific data analysis and visualization algorithms by looking at Dax toolkit which provides a development framework for the next generation of high-performance computers and GPU''s. Dax provides a concept mechanism to automatically build parallel scheduling code from signatures using C++.

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Topics:
Scientific Visualization, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
S3400
Streaming:
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