Glosten Predicts Barehull KRISO Containership Resistance Using Cloud Solutions

In this study, the Glosten team runs Fine Marine simulations using UberCloud containers, assesses the performance of the available hardware, and compares it to resources currently used by the end user. The benchmark case was analyzed on local hardware, virtual instances from Amazon Web Services (AWS), and the bare metal cloud solution offered by CPU 24/7 and UberCloud.

Company Profile

Glosten

Glosten is a Seattle-based engineering consultancy comprising naval, marine, electrical, and ocean architects. Since the firm's inception in 1958, Glosten has repeatedly delivered innovative solutions to challenging problems in the marine industry. Their design experience includes tugs, barges, research vessels, cruise vessels, passenger/car ferries, and special-purpose platforms.

CPU 24/7

The cloud resource provider CPU 24/7 GmbH is a leading provider of CAE service solutions for all industrial and academic /university research and development application areas. Headquartered in Potsdam/Germany, CPU 24/7 develops and operates on-demand high-performance computing services based on the latest, globally accepted hardware, software, and application industry standards.

About the Project

This project focuses on the barehull resistance calculation of the KRISO containership (KCS) in the cloud. The KRISO containership is a standard hull form frequently used as a benchmark case for computational fluid dynamics (CFD) study in the marine industry. Both basic hull form parameters and experimental results are available in published literature.

Process and Benchmark Results

The simulation was set up as a steady-state solution, fixed in trim and heave to duplicate the conditions of the experimental data.  The half-model mesh contains 1.6 million cells.  The simulation control variables are as follows:

• 300-time steps
• Uniform time step = 5 sub-cycles
• Eight non-linear iterations

The solution converges to a steady state resistance force within 150-time steps; however, the simulation was allowed to run to completion on all platforms to provide a performance comparison.

This model's calculated total resistance coefficient is noted to be 0.003574. There is a 0.4% difference compared to the experimental result of 0.00356. Figure 1. illustrates the calculated wave field (top) compared to the measured data (bottom).

Figure 1. Comparison of experimental and calculated results

UberCloud Application Containers for Fine Marine

UberCloud containers are ready-to-execute packages of software. They are designed to deliver the tools to complete a complex task. In this case study, the Fine Marine software has been pre-installed, configured, and runs on bare metal without performance loss. The software was ready to run without installing or dealing with complex OS commands or configurations.

The UberCloud container technology offers engineers wide options as the containers are portable from server to server or cloud to cloud. Cloud operators or IT departments will no more restrict the different varieties of tasks since they no longer have to install, tune, and maintain the underlying software. They can rely on the UberCloud containers to cut through this complexity. This technology also provides hardware abstraction, wherein the container is not tightly coupled with the server abstraction between the hardware and software stacks, providing the ease of use and agility that bare metal environments lack.

Benefits

This case helped us understand the performance benefits offered by UberCloud and CPU 24/7. Glosten considers the UberCloud service a viable alternative to a local server upgrade. The processors offered by CPU 24/7 and available through the UberCloud container significantly improved performance over local Glosten hardware and the virtual instances available through AWS. The AWS compute instance used here is the third generation, c3.8xlarge.  

Additional benefits include on-demand access, the use of the software and hardware resources, and reduced overhead to manage virtual instances and maintain software updates.

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