GTC ON-DEMAND

 
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GTC ON-DEMAND

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Abstract:
Our talk will examine advances in the simulation of particulate systems in computer-aided engineering applications. We'll focus on the discrete element method (DEM) and the strides made in the number of particles and particle shape using the GPU-Based code, Blaze-DEM. We'll cover a number of industrial applications including mining, agriculture, civil engineering, and pharmaceuticals. We will ook at fluid and heat couplings made possible by the increased computational power of the latest NVIDIA GPUs. We'll also discuss work by various groups to create a multi-physics GPU-Based platform using Blaze-DEM.
Our talk will examine advances in the simulation of particulate systems in computer-aided engineering applications. We'll focus on the discrete element method (DEM) and the strides made in the number of particles and particle shape using the GPU-Based code, Blaze-DEM. We'll cover a number of industrial applications including mining, agriculture, civil engineering, and pharmaceuticals. We will ook at fluid and heat couplings made possible by the increased computational power of the latest NVIDIA GPUs. We'll also discuss work by various groups to create a multi-physics GPU-Based platform using Blaze-DEM.  Back
 
Topics:
Computer Aided Engineering, Computational Fluid Dynamics, Computational Physics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9436
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Abstract:
In this talk we will look at advances in the simulation of particulate systems in Computer Aided Engineering (CAE) applications. We will in particular be focusing on the Discrete Element Method (DEM) and the strides made in terms of the number of particles and particle shape using the GPU based code Blaze-DEM. A variety of industrial applications ranging from mining, agriculture, civil engineering to pharmaceuticals will be discussed. We will also touch on how we can leverage the next wave of GPU computing namely, half precession and tensor cores in scientific computing which is still predominantly double precision based. Finally we look at the work been done by various groups to create a multi-physics GPU based platform using Blaze-DEM.
In this talk we will look at advances in the simulation of particulate systems in Computer Aided Engineering (CAE) applications. We will in particular be focusing on the Discrete Element Method (DEM) and the strides made in terms of the number of particles and particle shape using the GPU based code Blaze-DEM. A variety of industrial applications ranging from mining, agriculture, civil engineering to pharmaceuticals will be discussed. We will also touch on how we can leverage the next wave of GPU computing namely, half precession and tensor cores in scientific computing which is still predominantly double precision based. Finally we look at the work been done by various groups to create a multi-physics GPU based platform using Blaze-DEM.  Back
 
Topics:
Computational Fluid Dynamics, Computer Aided Engineering
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8348
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Abstract:

We'll explore the impact of the GPU in engineering simulations of discrete elements and glimpse into the future of simulations and engineering training. We consider the roles played by the open-source Blaze-DEMGPU framework we developed, as well as the commercial framework XPS, developed specifically for the pharmaceutical industry by the RCPE GmbH (Research Center Pharmaceutical Engineering GmbH) that allows engineers to simulate process changes before being actually implemented. Industrial-scale discrete element simulations remain a big challenge, but the GPU architecture is changing that perception fast, as is demonstrated by the open-source framework Blaze-DEM and the commercial framework XPS. However, engineering simulation remains characterized by either the analyze-wait-modify-analyze cycle or more recently the batch analyze-wait-modify-batch analyze cycle. The GPU is enabling a new and alternative paradigm denoted interactive simulation and design (ISD) as is demonstrated by Blaze-DEMGPU. We'll explore the algorithmic development of Blaze-DEMGPU in detail with a short historical tour outlining the development as the GPU architectures changed from Kepler to Pascal, enabling higher fidelity models in addition to the natural progression from the conventional analysis cycle towards ISD and the various roles machine learning can play.

We'll explore the impact of the GPU in engineering simulations of discrete elements and glimpse into the future of simulations and engineering training. We consider the roles played by the open-source Blaze-DEMGPU framework we developed, as well as the commercial framework XPS, developed specifically for the pharmaceutical industry by the RCPE GmbH (Research Center Pharmaceutical Engineering GmbH) that allows engineers to simulate process changes before being actually implemented. Industrial-scale discrete element simulations remain a big challenge, but the GPU architecture is changing that perception fast, as is demonstrated by the open-source framework Blaze-DEM and the commercial framework XPS. However, engineering simulation remains characterized by either the analyze-wait-modify-analyze cycle or more recently the batch analyze-wait-modify-batch analyze cycle. The GPU is enabling a new and alternative paradigm denoted interactive simulation and design (ISD) as is demonstrated by Blaze-DEMGPU. We'll explore the algorithmic development of Blaze-DEMGPU in detail with a short historical tour outlining the development as the GPU architectures changed from Kepler to Pascal, enabling higher fidelity models in addition to the natural progression from the conventional analysis cycle towards ISD and the various roles machine learning can play.

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Topics:
Computational Physics, Computational Biology & Chemistry, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7524
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Abstract:
This talk describes the DEM algorithms and heuristics that are optimized for the parallel NVIDIA® Kepler GPU architecture in detail. This includes a novel collision detection algorithm for convex polyhedra based on the separating plane (SP) method. In addition, we present heuristics optimized for the parallel NVIDIA® Kepler GPU architecture. Our algorithms have minimalistic memory requirements, which enables us to store data in the limited but high bandwidth constant memory on the GPU. We then systematically verify the DEM implementation after we demonstrate the computational scaling on two large-scale simulations.
This talk describes the DEM algorithms and heuristics that are optimized for the parallel NVIDIA® Kepler GPU architecture in detail. This includes a novel collision detection algorithm for convex polyhedra based on the separating plane (SP) method. In addition, we present heuristics optimized for the parallel NVIDIA® Kepler GPU architecture. Our algorithms have minimalistic memory requirements, which enables us to store data in the limited but high bandwidth constant memory on the GPU. We then systematically verify the DEM implementation after we demonstrate the computational scaling on two large-scale simulations.  Back
 
Topics:
Computational Physics, Astronomy & Astrophysics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5244
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Abstract:
DEM simulations are useful in a number of engineering disciplines such as mining, agriculture, etc. The computational cost of discrete methods limits the number and detail of particles that can be simulated in a reasonable time frame without the use of a dedicated CPU cluster. Here, we present a GPU framework for a DEM code that takes particle shape into account by using polyhedra while allowing for millions of spherical particles to be simulated also.
DEM simulations are useful in a number of engineering disciplines such as mining, agriculture, etc. The computational cost of discrete methods limits the number and detail of particles that can be simulated in a reasonable time frame without the use of a dedicated CPU cluster. Here, we present a GPU framework for a DEM code that takes particle shape into account by using polyhedra while allowing for millions of spherical particles to be simulated also.   Back
 
Topics:
Computational Physics
Type:
Poster
Event:
GTC Silicon Valley
Year:
2014
Session ID:
P4126
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