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Do you plan upgrading your platform to newer one which supports Skylake CPU if so will you be willing to buy 64GB of RAM?
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Actually I bought SSD drive with the capacity of 120 GB. Page file consumes exactly 100GB and I started to test computation of large data sets up to 10e+9 elements of type double. For that purpose I base my code on STXXL library.
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Yes , it is understood pretty well that the performance will be worse when the virtual memory is in use.
For my own purpose as I physically cannot upgrade to more than 32GB I decided to at least partially compensate over low HDD R/W speed by using 120 GB SSD.
Why are you locked so on mobile workstations? Can not you invest in second hand WS platform where you can easily upgrade to >128 GB of RAM?
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This is a good approach.
In my case usually a reference solution is provided by the Mathematica 8 routines to which my implementation or in some case a tiny C++ wrapper around Fortran 77 code is compared. Of course this is in the case of numerical quadrature, ODE solvers and special functions evaluations.
Yes I plan to test stxxl::vector against pure C-style array and I do not expect from stxxl to be faster.
P.s
Was your intention to allocate 128GB or 128MB in static array declaration?
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I actually plan to create a thread for the Quadrature tests which I conduct now.
STXXL is based on the External Memory concept so it can be slower than std::vector or C-style array test when working on data set lying in physical memory. The more interested part will be when you are crossing into the realm of Virtual Memory.
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>>>I could submit some performance numbers which demostrate how processing times are increasing as soon as VM is used.>>>
I would like to see it.
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Honestly, there is nothing interesting here because processing will get slower and I guarantee it for 100%.
Yes that is expected.
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