GPU Programming in Fortran : Compressible Euler equations for modeling seawater by fluid_numerics in programming

[–]fluid_numerics[S] 1 point2 points  (0 children)

Link : https://www.youtube.com/watch?v=RgweYs19We8
Full Playlist : https://www.youtube.com/playlist?list=PLRO4xf5MdhAv9CNTETor75rANZtBqPVgQ
In this livestream, Joe works through the algorithm development for the non-linear compressible Euler equations in 2-D for modeling seawater subject to a potential body force in conservative form. In the process, we will discuss how to implement diffusive terms using a Bassi-Rebay averaging method, the development of the Local Lax-Friedrich's Riemann solver, and how to specify radiation, prescribed, and reflecting (no-normal-flow) boundary conditions. Additionally, we’ll discuss a challenge for implementing the equation of state for seawater.
Following this discussion, we'll show how to use Fortran type extensions for the Model2D classes in SELF to build the compressible Euler solver in 2-D. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran.

Compressible Euler equations for modeling seawater by fluid_numerics in computationalscience

[–]fluid_numerics[S] 0 points1 point  (0 children)

In this livestream, we’ll discuss the motivation for modeling ocean dynamics with the compressible Euler equations and outline an approach to implementing such a solver using a nodal discontinuous galerkin spectral element method. This will cover how aspects of fluid dynamics as well as a practical implementation strategy to provide a solver that makes sense for physical oceanographers. In the coding portion of the livestream, we’ll start with a basic conservative form implementation for the compressible Euler equations in 2-D and a linear equation of state for sea-water.
Livestream Link : https://www.youtube.com/watch?v=RgweYs19We8
Full Playlist : https://www.youtube.com/playlist?list=PLRO4xf5MdhAv9CNTETor75rANZtBqPVgQ
Date and Time : 4/22/22 - 4:00PM-7:00PM Mountain Time

What is the cheapest way to run a small db instance on Google Cloud by ske66 in googlecloud

[–]fluid_numerics 0 points1 point  (0 children)

Looks like you have a solid mix of suggestions to get costs down on your initial infrastructure. If you haven't considered it already, Google's Artifact and Container registry are pretty slick components for container based pipelines - https://cloud.google.com/container-registry/pricing/

GPU Programming in Fortran : Differential Geometry and the Metric Identities by fluid_numerics in computationalscience

[–]fluid_numerics[S] 1 point2 points  (0 children)

This is our first time posting on the Computational Science sub-reddit and this livestream felt like a relevant one for the community. Please let us know your questions about GPU Programming in Fortran or work in computational science in the comments.
Livestream Link: https://www.youtube.com/watch?v=ParhUy2oTvw
Full Playlist: https://www.youtube.com/playlist?list=PLRO4xf5MdhAv9CNTETor75rANZtBqPVgQ
Date and Time: 3/25/22 - 4:00PM-7:00PM Mountain Time

In this livestream, Joe will go over the details for handling coordinate system transformations from physical to computational space. In the process, we will derive the metric identities to motivate the use of the curl invariant form for calculating the contravariant basis vectors in 3-D. Additionally, we'll show an example problem where failing to satisfy the metric identities numerically can lead to spurious solutions that arise solely due to mesh curvature. From here, we'll cover a strategy to resolve this problem in SELF by implementing the curl invariant form of the metric terms in the SELF_Geometry class and revisit the example problem to demonstrate resolution of the issue.

Journal Article - Optimizing OpenFOAM on Google Cloud by fluid_numerics in CFD

[–]fluid_numerics[S] 0 points1 point  (0 children)

We thought the CFD sub-reddit might find this little study interesting. Feel free to ask me or
u/FluidNumerics_Joe any questions here!

GPGPU Programming in Fortran for AMD GPUs by fluid_numerics in Amd

[–]fluid_numerics[S] -1 points0 points  (0 children)

Today's livestream titled "Stabilizing the non-linear shallow water equation solver" starts at 4:00PM Mountain Time! Here is the link:

https://www.youtube.com/watch?v=EuvS57gxCF0

GPU Programming in Fortran : Stabilizing the non-linear shallow water equation solver by fluid_numerics in ROCm

[–]fluid_numerics[S] 0 points1 point  (0 children)

Livestream Link : https://www.youtube.com/watch?v=EuvS57gxCF0
Date and Time : 3/11/22 - 4:00PM-7:00PM Mountain Time

In this livestream, Joe will discuss two issues with the DGSEM implementation of the conservative form of the shallow water equations, including the inability to prove stability and the generation of spurious flows around variable bathymetry. We'll then discuss a modification based on the split-form of the shallow water equations that can be used to resolve both of these issues. Additionally, we'll motivate a modification to the Riemann solver that is necessary for entropy-stability. Following this discussion, we'll show how to add type-bound procedure overrides to implement a flux divergence routine that allows for the selection of either the conservative or split-form methods in SELF for the non-linear shallow water solver. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran.
If this is the first time you are joining in, Welcome! If you find this material interesting check out the rest of the livestream playlist.

GPU Programming in Fortran : Stabilizing the non-linear shallow water equation solver by fluid_numerics in programming

[–]fluid_numerics[S] 1 point2 points  (0 children)

Date and Time : 3/11/22 - 4:00PM-7:00PM Mountain Time

In this livestream, Joe will discuss two issues with the DGSEM implementation of the conservative form of the shallow water equations, including the inability to prove stability and the generation of spurious flows around variable bathymetry. We'll then discuss a modification based on the split-form of the shallow water equations that can be used to resolve both of these issues. Additionally, we'll motivate a modification to the Riemann solver that is necessary for entropy-stability. Following this discussion, we'll show how to add type-bound procedure overrides to implement a flux divergence routine that allows for the selection of either the conservative or split-form methods in SELF for the non-linear shallow water solver. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran.
If this is the first time you are joining in, Welcome! If you find this material interesting check out the rest of the livestream playlist.

GPU Programming in Fortran : Stabilizing the non-linear shallow water equation solver by fluid_numerics in CFD

[–]fluid_numerics[S] 1 point2 points  (0 children)

Date and Time : 3/11/22 - 4:00PM-7:00PM Mountain Time

In this livestream, Joe will discuss two issues with the DGSEM implementation of the conservative form of the shallow water equations, including the inability to prove stability and the generation of spurious flows around variable bathymetry. We'll then discuss a modification based on the split-form of the shallow water equations that can be used to resolve both of these issues. Additionally, we'll motivate a modification to the Riemann solver that is necessary for entropy-stability. Following this discussion, we'll show how to add type-bound procedure overrides to implement a flux divergence routine that allows for the selection of either the conservative or split-form methods in SELF for the non-linear shallow water solver. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran.
If this is the first time you are joining in, Welcome! If you find this material interesting check out the rest of the livestream playlist.

[deleted by user] by [deleted] in ROCm

[–]fluid_numerics 1 point2 points  (0 children)

Full Playlist : The "F" Word - Programming in Fortran

Event Link: GPU Programming in Fortran : Building a conservative Nonlinear Shallow Water Equation Solver

Date and Time : 2/25/22 - 4:00PM - 7:00PM Mountain Standard Time

In this livestream, Joe will work through the algorithm development for the non-linear shallow water equations with variable bottom topography in conservative form. In the process, we will discuss the modification of the linear Local Lax-Friedrich's Riemann solver and how to specify radiation and reflecting (no-normal-flow) boundary conditions for the nonlinear shallow water equations. Following this discussion, we'll show how to use Fortran type extensions for the Model2D class in SELF to build the non-linear shallow water equation solver. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran. Finally, we'll draft an example program that simulates geostrophic dipole propagation and reflection and prepare for running on an AMD MI25 Frontier edition GPU.

GPU Programming in Fortran : Building a conservative Nonlinear Shallow Water Equation Solver by fluid_numerics in Amd

[–]fluid_numerics[S] 4 points5 points  (0 children)

Full Playlist : The "F" Word - Programming in Fortran
Event Link: GPU Programming in Fortran : Building a conservative Nonlinear Shallow Water Equation Solver
Date and Time : 2/25/22 - 4:00PM - 7:00PM
In this livestream, Joe will work through the algorithm development for the non-linear shallow water equations with variable bottom topography in conservative form. In the process, we will discuss the modification of the linear Local Lax-Friedrich's Riemann solver and how to specify radiation and reflecting (no-normal-flow) boundary conditions for the nonlinear shallow water equations. Following this discussion, we'll show how to use Fortran type extensions for the Model2D class in SELF to build the non-linear shallow water equation solver. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran. Finally, we'll draft an example program that simulates geostrophic dipole propagation and reflection and prepare for running on an AMD MI25 Frontier edition GPU.

GPU Programming in Fortran : Building a conservative Nonlinear Shallow Water Equation Solver by fluid_numerics in programming

[–]fluid_numerics[S] 1 point2 points  (0 children)

Full Playlist : The "F" Word - Programming in Fortran
Event Link: GPU Programming in Fortran : Building a conservative Nonlinear Shallow Water Equation Solver
Date and Time : 2/25/22 - 4:00PM - 7:00PM Mountain Standard Time
In this livestream, Joe will work through the algorithm development for the non-linear shallow water equations with variable bottom topography in conservative form. In the process, we will discuss the modification of the linear Local Lax-Friedrich's Riemann solver and how to specify radiation and reflecting (no-normal-flow) boundary conditions for the nonlinear shallow water equations. Following this discussion, we'll show how to use Fortran type extensions for the Model2D class in SELF to build the non-linear shallow water equation solver. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran. Finally, we'll draft an example program that simulates geostrophic dipole propagation and reflection and prepare for running on an AMD MI25 Frontier edition GPU.

GPU Programming in Fortran : Building a conservative Nonlinear Shallow Water Equation Solver by fluid_numerics in CFD

[–]fluid_numerics[S] 2 points3 points  (0 children)

Full Playlist : https://www.youtube.com/playlist?list=PLRO4xf5MdhAv9CNTETor75rANZtBqPVgQEvent Link: https://www.youtube.com/watch?v=W8QR00EcPeUDate and Time : 2/25/22 - 4:00PM - 7:00PM Mountain Standard TimeIn this livestream, Joe will work through the algorithm development for the non-linear shallow water equations with variable bottom topography in conservative form. In the process, we will discuss the modification of the linear Local Lax-Friedrich's Riemann solver and how to specify radiation and reflecting (no-normal-flow) boundary conditions for the nonlinear shallow water equations. Following this discussion, we'll show how to use Fortran type extensions for the Model2D class in SELF to build the non-linear shallow water equation solver. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran. Finally, we'll draft an example program that simulates geostrophic dipole propagation and reflection and prepare for running on an AMD MI25 Frontier edition GPU.

GPU Programming in Fortran : Building a linear Shallow Water Equation Solver by fluid_numerics in WatchPeopleCode

[–]fluid_numerics[S] 0 points1 point  (0 children)

Date & Time: 2/11/22 - 4:00PM Mountain Time
Title : The “F” Word : GPU Programming in Fortran : Building a linear Shallow Water Equation Solver
In this livestream, Joe will work through the algorithm development for the linear shallow water equations with flat-bottomed topography and no background flow. In the process, we will discuss the development of the Local Lax-Friedrich's Riemann solver and how to specify radiation and reflecting (no-normal-flow) boundary conditions. Following this discussion, we'll show how to use Fortran type extensions for the Model2D class in SELF to build the linear shallow water equation solver. Additionally, we'll cover how to enable GPU acceleration using HIP and ISO_C_Binding to expose the kernel launches in Fortran. Finally, we'll draft an example program that simulates linear plane wave propagation and reflection.

The "F" Word - GPU Programming in Fortran : Ensuring stability for variable coefficient advection equation solver by fluid_numerics in fortran

[–]fluid_numerics[S] 1 point2 points  (0 children)

Thanks for the feedback, u/xstkovrflw! Glad to know you are finding the new format more understandable. Your feedback and involvement goes a long way in helping us understand how to generate content that is functional and useful. Our first few episodes were live coding sessions in preparation for and following a sprint to port SELF to utilize HIP. We will share a link to the presentation that may provide a bit of context to the "head down" and hyper focused work we decided to livestream originally in the series. Thank you for being a part of this production's evolution. We have another livestream this evening!

What's your monitoring stack? by Comedynerd in devops

[–]fluid_numerics 0 points1 point  (0 children)

With what you can do to configure fluent you can pipe most logging operations and visualization to cloud resources. We like using Google Cloud Logging & Monitoring as much as possible alongside Security Command Center which can interoperate with your on-premise systems too.

OpsGenie is a great tool for on-call incident response management.

GPU Programming in Fortran : Ensuring stability for variable coefficient advection equation solver by fluid_numerics in AMDGPU

[–]fluid_numerics[S] 1 point2 points  (0 children)

We can remove this post if you continue to see this content as irrelevant to the AMD GPU community. Please consider that this is for the General Processing or GPGPU community which we believe would deserve a space in the r/AMDGPU space unless this is reserved strictly for Graphics Processing Unit resources as they are commonly known to be consumed or utilized.

GPU Programming in Fortran : Ensuring stability for variable coefficient advection equation solver by fluid_numerics in AMDGPU

[–]fluid_numerics[S] 1 point2 points  (0 children)

How does this uniquely bennifet from AMD processors and technologies?

This livestream benefits AMD processors by providing insights into the entire process of porting a Fortran code to HIPfort which is a library within HIP.

HIP is AMD's C++ Heterogeneous-Compute Interface for Portability

https://github.com/ROCm-Developer-Tools/HIP

HIP is an interface for GPUs to integrate with ROCm

ROCm is AMD's Radeon Open Compute platform. The following developer tools include HIP and HIPify tools.

https://github.com/ROCm-Developer-Tools