Below is data I got from knowledge base for COSMOS 2005 :

COSMOSMotion and COSMOSFloWorks do not make use of Dual Processor or Dual Core.

COSMOSworks, on the other hand, does: - FFEPlus will take advantage of Dual Processor only. There is a improvement of 15% on using this.

- Direct Sparse solvers will take advantage of both multi Processor and Dual Core system. There is improvement of 60% for this solver.

I need data at least for SW 2009 for preparing hardware.

And of course hope it will also work for SW 2010.

And below just I got from knowledge base for Simulation 2009 :

Yes, the solvers for Simulation 2009 can
utilize more than one CPU/core. Most studies that solve using the
Direct Sparse solver will see a significant improvement in performance
due to the number of CPUs that are used. In 2009 this is not limited to
just static studies as with older releases.

In addition, if
the user runs multiple studies simultaneously (new functionality in
2009), each study could potentially run on a different CPU/core. There
is also some minor (typically less than 20%) improvement due to a
multi-core environment with the Iterative solver (FFEPlus).

Version 2009 The table below shows the Percentage improvement in time taken to complete solving when 4 cores were allowed compared to when just one core was permitted for the respective solver. The data was obtained using test cases in Simulation 2009 SP2.1 on a Windows XP x64 Dell Precision T7400 with Quad Core Intel Xeon X5472 @ 3.0 GHz, 16 GB RAM.

[See attached chart.]

Other Study Types:

Drop Test

Only one solver type available, test model used only one core.

Fatigue

Only one solver type available. Fatigue solver itself used only one core but preparing to run a fatigue study involves setting up and running one or more static studies. Since static studies do benefit from multiple cores, users doing this type of analysis would see an overall improvement in time to perform a fatigue analysis on a multi-core machine.

Optimization

Most of the time spent solving an optimization analysis is taken up by running loops of designs iterations of the studies defined for constraints. In the current release, these constraints can be based on static, buckling, frequency, and thermal studies. Since the user can specify which solver type they wish to use for each of the constraint studies, performing an optimization analysis on a multi-core machine would show improvement in performance over using just a single core machine.

Linear Dynamic

The actual post dynamic analysis and stress calculations use special solvers which used only one core in testing. However, performing a linear dynamic analysis involves first finding resonant frequencies, which did show usage of more than one core when using the FFEPlus solver.

Pressure Vessel Design

The majority of the time taken to complete a pressure vessel analysis is running the respective static studies that you wish to combine. The actual calculations for combination of results used only one core during testing but it made up a small percentage of the total time perform the analysis. As a result, a user with a multi-core machine would see an overall improvement in time to perform a pressure vessel design analysis when compared to a single-core machine.

Conclusion

Every analysis type with the exception of Drop Test is capable of showing an improvement in overall time taken to complete solving when a multi-core/CPU machine is used.

Notes

When looking at CPU usage in Task Manager, 100% indicates that all four CPUs are being used at maximum capacity. 25% indicates that one CPU is being used at full capacity.

In general, the Iterative solver (FFEPlus) did not show usage beyond 60% which could imply full usage of two CPUs and partial usage of a third.

Direct Sparse showed the greatest improvement in performance during the matrix decomposition stage, where for most testing done the total CPU usage was 99%.

Even for solver stages or study types which use only one core, there is still a minor benefit to having more than one CPU since it makes it possible to allocate an entire core to the solver while leaving background applications and system processes to use their own separate cores.

Nonlinear test models showed usage of more than one CPU only for certain stages of the Direct Sparse solver – during contact iterations for test model, total CPU usage stayed below 25%.

Multistep analysis such as the nonlinear one can have significant differences in multi-core performance between models depending on geometry, setup, number of contacts, etc.

Hi David,

Thanks for update info for flosimulation 2009.

How about SW Simulation its self ?

Below is data I got from knowledge base for COSMOS 2005 :

I need data at least for SW 2009 for preparing hardware.

And of course hope it will also work for SW 2010.

And below just I got from knowledge base for Simulation 2009 :

Many thanks guys...

-AZ

Message was edited by: Ahmad Zulker

The table below shows the Percentage improvement in time taken to complete solving when 4 cores were allowed compared to when just one core was permitted for the respective solver. The data was obtained using test cases in Simulation 2009 SP2.1 on a Windows XP x64 Dell Precision T7400 with Quad Core Intel Xeon X5472 @ 3.0 GHz, 16 GB RAM.

[See attached chart.]

Other Study Types:

Drop Test

Only one solver type available, test model used only one core.

Fatigue

Only one solver type available. Fatigue solver itself used only one core but preparing to run a fatigue study involves setting up and running one or more static studies. Since static studies do benefit from multiple cores, users doing this type of analysis would see an overall improvement in time to perform a fatigue analysis on a multi-core machine.

Optimization

Most of the time spent solving an optimization analysis is taken up by running loops of designs iterations of the studies defined for constraints. In the current release, these constraints can be based on static, buckling, frequency, and thermal studies. Since the user can specify which solver type they wish to use for each of the constraint studies, performing an optimization analysis on a multi-core machine would show improvement in performance over using just a single core machine.

Linear Dynamic

The actual post dynamic analysis and stress calculations use special solvers which used only one core in testing. However, performing a linear dynamic analysis involves first finding resonant frequencies, which did show usage of more than one core when using the FFEPlus solver.

Pressure Vessel Design

The majority of the time taken to complete a pressure vessel analysis is running the respective static studies that you wish to combine. The actual calculations for combination of results used only one core during testing but it made up a small percentage of the total time perform the analysis. As a result, a user with a multi-core machine would see an overall improvement in time to perform a pressure vessel design analysis when compared to a single-core machine.

Conclusion

Every analysis type with the exception of Drop Test is capable of showing an improvement in overall time taken to complete solving when a multi-core/CPU machine is used.

Notes

When looking at CPU usage in Task Manager, 100% indicates that all four CPUs are being used at maximum capacity. 25% indicates that one CPU is being used at full capacity.

In general, the Iterative solver (FFEPlus) did not show usage beyond 60% which could imply full usage of two CPUs and partial usage of a third.

Direct Sparse showed the greatest improvement in performance during the matrix decomposition stage, where for most testing done the total CPU usage was 99%.

Even for solver stages or study types which use only one core, there is still a minor benefit to having more than one CPU since it makes it possible to allocate an entire core to the solver while leaving background applications and system processes to use their own separate cores.

Nonlinear test models showed usage of more than one CPU only for certain stages of the Direct Sparse solver – during contact iterations for test model, total CPU usage stayed below 25%.

Multistep analysis such as the nonlinear one can have significant differences in multi-core performance between models depending on geometry, setup, number of contacts, etc.

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