Best workbench specs for PLAXIS3d

Your computer specifications seem to be quite good. If there is no restriction on resources, following spec will bring about a lot of computing power.

Processor:  AMD Ryzen Threadripper 3970X 32-Core, 64-Thread Unlocked Desktop Processor

Operating System: Windows 10 Pro 64-bit

Memory:  Large projects: 64 GB 

Disk Space:  Large projects: 1 TB SSD. For best performance, ensure that the TEMP directory and the project directory reside on the same partition.

Display  Graphics Card: Required: GPU with 256 MB OpenGL 1.3. Bentley recommends avoiding simple onboard graphics chips in favor of a discrete GPU from the nVidia GeForce or Quadro range with at least 128-bit bus and 1 GB of RAM, or equivalent solution from ATI/AMD.

Video: Required: 1024 x 768 pixels 32-bit color palette, Recommended: 1920 x 1080 pixels 32-bit color palette

Usually with the increase in the processor speed and the number of cores, the decrease of computational time is NOT linearly proportional. It depends on how much portion of the code is parallelized. Above all there is the overhead cost of message passing while computing on multiple cores/processors. So you get faster computation but not as you expected. 

To get quick operations in the program:

• make sure the Windows TEMP is stored on a fast disk, e.g. an SSD. During the calculations, the calculation will need to read and write a lot of data so having a fast drive will help overall for the calculation; 
• storing the final data on a normal hard drive does not influence the calculation time: only when you tell PLAXIS to save the data, the data from the Windows TEMP folder will be moved to the final save location; 
• have enough RAM. For models up to 500,000 elements not doing dynamic calculations, 16 GB should work. For larger models, get at least 32 GB. Only when you have models with roughly more than 1 million elements 32 GB RAM would be required; 
• For visualization, get a recent (gaming) graphics card that supports OpenGL 2 or higher with at least 1 GB of dedicated, not shared, RAM. Preferably from NVIDIA; Note that the Finite Element calculation does not use the graphics card to execute the calculations, this is still all done on the CPU;
• From our benchmarking, we do not see a conclusive speed increase for all kinds of calculation types (Plastic, Consolidation, Dynamics, etc.) in the calculation when you have more than 8 cores; 
• Note that we do not use hyper-threading, but PLAXIS will utilize all physically available cores. If the processor uses hyper-threading, this is not used. What hyper-threading does, is that it splits a core usage into two virtual cores. For a PLAXIS calculation, this means that it will try to use 1 at 100% and the other at about 20% (this is managed by Windows and the processor architecture). Then for the Plaxis calculation, the performance of the first one drops a bit too, since one processor cannot be used for 120% (so to run 120% of calculation operations per second). So, the total performance drops a bit too. In general, for a PLAXIS calculation, this runs slower than using the e.g. 4 physical cores to the max, compared to a setup with 4 hyper-threaded cores (8 logical cores). 
• And of course, a faster CPU will mean faster calculations.  

 If you need to make a choice between more CPU cores or faster CPU cores, I would go for the faster cores if your main concern is the Plaxis calculation speed. We have seen once you have at least quad-core processors, you benefit more from a faster CPU than from more cores.

 PLAXIS does not enforce limits on the number of items in a 3D calculation, but of course, the more elements you have, the more memory the program needs, and then you can run into hardware limitations.

 Of course, this is the experience we have with the current program.

 See more details here:

• Hardware: https://communities.bentley.com/products/geotechnical1/w/wiki/45817/multicore-cpu-and-32-64-bit
• Setting up phases efficiently: https://communities.bentley.com/products/geotechnical1/w/wiki/45816/is-plaxis-3d-enabled-for-multicore
  includes info about running parallel phases simultaneously 

Your computer specifications seem to be quite good. If there is no restriction on resources, following spec will bring about a lot of computing power.

Processor:  AMD Ryzen Threadripper 3970X 32-Core, 64-Thread Unlocked Desktop Processor

Operating System: Windows 10 Pro 64-bit

Memory:  Large projects: 64 GB 

Disk Space:  Large projects: 1 TB SSD. For best performance, ensure that the TEMP directory and the project directory reside on the same partition.

Display  Graphics Card: Required: GPU with 256 MB OpenGL 1.3. Bentley recommends avoiding simple onboard graphics chips in favor of a discrete GPU from the nVidia GeForce or Quadro range with at least 128-bit bus and 1 GB of RAM, or equivalent solution from ATI/AMD.

Video: Required: 1024 x 768 pixels 32-bit color palette, Recommended: 1920 x 1080 pixels 32-bit color palette

Usually with the increase in the processor speed and the number of cores, the decrease of computational time is NOT linearly proportional. It depends on how much portion of the code is parallelized. Above all there is the overhead cost of message passing while computing on multiple cores/processors. So you get faster computation but not as you expected. 

To get quick operations in the program:

• make sure the Windows TEMP is stored on a fast disk, e.g. an SSD. During the calculations, the calculation will need to read and write a lot of data so having a fast drive will help overall for the calculation; 
• storing the final data on a normal hard drive does not influence the calculation time: only when you tell PLAXIS to save the data, the data from the Windows TEMP folder will be moved to the final save location; 
• have enough RAM. For models up to 500,000 elements not doing dynamic calculations, 16 GB should work. For larger models, get at least 32 GB. Only when you have models with roughly more than 1 million elements 32 GB RAM would be required; 
• For visualization, get a recent (gaming) graphics card that supports OpenGL 2 or higher with at least 1 GB of dedicated, not shared, RAM. Preferably from NVIDIA; Note that the Finite Element calculation does not use the graphics card to execute the calculations, this is still all done on the CPU;
• From our benchmarking, we do not see a conclusive speed increase for all kinds of calculation types (Plastic, Consolidation, Dynamics, etc.) in the calculation when you have more than 8 cores; 
• Note that we do not use hyper-threading, but PLAXIS will utilize all physically available cores. If the processor uses hyper-threading, this is not used. What hyper-threading does, is that it splits a core usage into two virtual cores. For a PLAXIS calculation, this means that it will try to use 1 at 100% and the other at about 20% (this is managed by Windows and the processor architecture). Then for the Plaxis calculation, the performance of the first one drops a bit too, since one processor cannot be used for 120% (so to run 120% of calculation operations per second). So, the total performance drops a bit too. In general, for a PLAXIS calculation, this runs slower than using the e.g. 4 physical cores to the max, compared to a setup with 4 hyper-threaded cores (8 logical cores). 
• And of course, a faster CPU will mean faster calculations.  

 If you need to make a choice between more CPU cores or faster CPU cores, I would go for the faster cores if your main concern is the Plaxis calculation speed. We have seen once you have at least quad-core processors, you benefit more from a faster CPU than from more cores.

 PLAXIS does not enforce limits on the number of items in a 3D calculation, but of course, the more elements you have, the more memory the program needs, and then you can run into hardware limitations.

 Of course, this is the experience we have with the current program.

 See more details here:

• Hardware: https://communities.bentley.com/products/geotechnical1/w/wiki/45817/multicore-cpu-and-32-64-bit
• Setting up phases efficiently: https://communities.bentley.com/products/geotechnical1/w/wiki/45816/is-plaxis-3d-enabled-for-multicore
  includes info about running parallel phases simultaneously