I’m working with large multidimensional dataset (> 10 dimensions and > 100,000 points). One particular problem I have is the use of virtual memory (for example, via new). When I input dataset with more than 6 dimensions and 100,000 points, the program halts with the message: “virtual memory exceeded in new()”. Can you provide me with some general guidelines when working with large datasets?
The program I create uses dynamic linklist structure, a fixsize lookup table (= datasize), and creation of dynamic array in a loop (I use new and delete within the loop so that the memory can be refreshed and reused).
It’s hard to be very specific without more information, but, basically, it sounds like you are simply running out of memory.
While I don’t know how much memory each item in your dataset takes, if each one were only 1 byte (very unlikely), the number of bytes you’d need to allocate would be something like 1 with 30 zeros following. It sounded like you were even trying to allocate memory on top of that!
I know you provided more details but it wasn’t entirely clear exactly how those elements came together, and without understanding the task, I really can’t be more specific.
You need to rethink your approach; see if there are ways to use less memory; see if you can allocate only small portions of your data at a time. Either that, or move to a purely disk-based approach and wait about five or 10 years for hard disks that will handle that much memory.