I'm interested in buying a new workstation for my lab and in the process I encountered a lot of options which some I did not fully understand.
The main function this workstation is for numerical simulations which mainly involve: solving large eigenvalue problems and algebraic equations, large lists manipulations and setting (symbolic and numeric) and analyzing large databases.
I am not sure which hardware is needed for each usage (more memory, more CPU speed, more processing cores. etc.), so I can't really tell which system I need.
Furthermore, I am using parallel-computations in my simulations which cuts of a great deal of time for it to run. Thus, I was offered two alternatives: using coprocessors (such as Intel Xeon Phi) or using GPU processing (nVidia Tesla or Titan). I would like the advantages and disadvantages of each hardware while using Mathematica for my purposes (including the price issues). Moreover, I know that for complicated calculations CUDA programming is necessary for exploiting the most of GPU processing, are there any adjustments I need to make in order to use coprocessors with Mathematica or does it automatically using all available processing-cores?
After my little internet searching I was thinking to get something like the following:
- Intel Xeon 8 core 2.4GHz processors X2
- 128Gb RAM memory
- Intel Xeon Phi coprocessor 51XX or 71XX (depending on price) X2/X3
- OS SSD drive
- 2Tb data drive X2
Is it too much? too little?
Thank you all in advance
MaxMemoryUsed[]
how much you are using? I personally never go beyond 16GB, with what I consider large datasets, but your definition could be different. $\endgroup$ – Feyre Aug 16 '16 at 11:00