scholarly journals Computational Fluid Dynamics Using Graphics Processing Units: Challenges and Opportunities

2011 ◽  
Author(s):  
S. Pratap Vanka ◽  
Aaron F. Shinn ◽  
Kirti C. Sahu
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Fluid Flow ◽  
Graphics Processing Units ◽  
Review Paper ◽  
Fluid Flows ◽  
New Paradigm ◽  
The Past ◽  
Challenges And Opportunities ◽  
Graphics Processing

A new paradigm for computing fluid flows is the use of Graphics Processing Units (GPU), which have recently become very powerful and convenient to use. In the past three years, we have implemented five different fluid flow algorithms on GPUs and have obtained significant speed-ups over a single CPU. Typically, it is possible to achieve a factor of 50–100 over a single CPU. In this review paper, we describe our experiences on the various algorithms developed and the speeds achieved.

2012 Freeman Scholar Lecture: Computational Fluid Dynamics on Graphics Processing Units

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
S. P. Vanka
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Graphics Processing Units ◽  
Stokes Equations ◽  
Multicore Processors ◽  
Fluid Flows ◽  
Data Access ◽  
Central Processing ◽  
Data Parallel ◽  
Graphics Processing

This paper discusses the various issues of using graphics processing units (GPU) for computing fluid flows. GPUs, used primarily for processing graphics functions in a computer, are massively parallel multicore processors, which can also perform scientific computations in a data parallel mode. In the past ten years, GPUs have become quite powerful and have challenged the central processing units (CPUs) in their price and performance characteristics. However, in order to fully benefit from the GPUs' performance, the numerical algorithms must be made data parallel and converge rapidly. In addition, the hardware features of the GPUs require that the memory access be managed carefully in order to not suffer from the high latency. Fully explicit algorithms for Euler and Navier–Stokes equations and the lattice Boltzmann method for mesoscopic flows have been widely incorporated on the GPUs, with significant speed-up over a scalar algorithm. However, more complex algorithms with implicit formulations and unstructured grids require innovative thinking in data access and management. This article reviews the literature on linear solvers and computational fluid dynamics (CFD) algorithms on GPUs, including the author's own research on simulations of fluid flows using GPUs.

A Computational Fluid Dynamics Study of Liquid–Solid Nano-fluid Flow in Horizontal Pipe

2021 ◽  
Author(s):  
Zainab Yousif Shnain ◽  
Jamal M. Ali ◽  
Khalid A. Sukkar ◽  
May Ali Alsaffar ◽  
Mohammad F. Abid
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Fluid Flow ◽  
Horizontal Pipe ◽  
Nano Fluid

scholarly journals Acceleration of a CFD Code with a GPU

2010 ◽  
Vol 18 (3-4) ◽  
pp. 193-201 ◽  
Author(s):  
Dennis C. Jespersen
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Graphics Processing Unit ◽  
Computational Time ◽  
Processing Unit ◽  
Graphics Processing ◽  
Work Done

The Computational Fluid Dynamics code OVERFLOW includes as one of its solver options an algorithm which is a fairly small piece of code but which accounts for a significant portion of the total computational time. This paper studies some of the issues in accelerating this piece of code by using a Graphics Processing Unit (GPU). The algorithm needs to be modified to be suitable for a GPU and attention needs to be given to 64-bit and 32-bit arithmetic. Interestingly, the work done for the GPU produced ideas for accelerating the CPU code and led to significant speedup on the CPU.

Simulation of an Effect of a Baffle Length on the Power Consumption in an Agitated Vessel

2008 ◽  
Vol 4 (2) ◽  
Author(s):  
Palani Sivashanmugam ◽  
S. Prabhakaran
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Cfd Simulation ◽  
Turbulence Modeling ◽  
Fluid Flows ◽  
Power Number ◽  
Food Industries ◽  
Agitated Vessel ◽  
Computational Fluid Dynamics Cfd ◽  
Miscible Liquids

Agitated vessels are often used for homogenization of the miscible liquids in chemical, biochemical, and food industries. Computational fluid dynamics (CFD) is a useful tool for studying fluid flows, including those of mixing systems. It is particularly powerful where the ability exists to corroborate model results with available data. The CFD simulation was carried out for Rushton and Smith turbines agitators. The standard k-? model has been used for turbulence modeling. The data obtained by simulation are matching with the literature experimental value for standard baffle with the discrepancy of less than +_4.5% for power number. The simulated results for agitated vessel with short baffle (non-standard) are agreeing with the literature values within plus or minus 5% for Power Number.

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