How much time do you want to spend making this decision? You can SWAG it or run relatively simple benchmarks. At most it would yield a 50% boost and probably not that much. I am not familiar with the details of the 3.7 GHz Turbo Boost but is sounds sexy. Ignore the processor speed differences, even the Turbo Boost. So that limits you to a $600 decision on if you need more than 8 GB of RAM. Given Mathematica uses several GB just for the code, the 4 GB solution is likely to be too small. Keeping the data in RAM is likely to have a biggest impact on speed than any other factor but as with with most HPC applications, the answer is 'it depends' if the cost justifies the benefit. These other factors probably won't matter in the end, given the large RAM and SSD tipping point differences.

SSD) for which you may need to benchmark them on the actual target hardware. Then there are harder questions (CPU speed, memory bandwidth, disk vs. Will the faster expected execution speed be worth the higher price? How much are the applications expected to grow if you have a more hefty machine? What is the run time difference currently if they fit in RAM vs. Are you willing to increase the RAM so it covers the current virtual memory sizeĪ factor for a more accurate measurement with a relatively easy benchmark: Great informatoin in the graph for deciding between disk and SSD, which is important and was not part of my analysis.īefore I get going too deeply I'll try to bring this down to earth. I get to put on my high-performance computing hat.

R most likely has similar memory characteristics. Mathematica uses several GB for just the code.Ħ4-bit MATLAB on 64-bit Windows or OS X will support an 8 TB process limit! (not a typo) Mathematica, MATLAB and Octave will use all the memory you can throw at them but will you actually use that much memory in your particular applications? More memory is usually a good thing for faster response times but 8 GB is alreday a hefty amount of memory. Note, twice the number of cores does not necessarily get you a full 2x speedup but it usually does run significantly faster (on multicore applications).Īs you have already implied, the flash memory will speedup the virtualization. I would be surprised if R does not run in parallel. Mathematica, MATLAB and Octave will speedup, using all the cores: These applications will run faster on the quad-core 15' MBP.ġ6 GB faster? Depends on your actual usage. Serious applications require serious resources.

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