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Home/ Questions/Q 7738029
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Editorial Team
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Editorial Team
Asked: June 1, 20262026-06-01T08:09:23+00:00 2026-06-01T08:09:23+00:00

I am working on a mathematical problem that has the advantage of being able

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I am working on a mathematical problem that has the advantage of being able to “pre-compute” about half of the problem, save this information to file, and then reuse it many times to compute various ‘instances’ of my problem. The difficulty is that uploading all of this information in order to solve the actual problem is a major bottleneck.

More specifically:
I can pre-compute a huge amount of information – tons of probabilities (long double), a ton of std::map<int,int>, and much more – and save all this stuff to disk (several Gb).

The second half of my program accepts an input argument D. For each D, I need to perform a great many computations that involve a combination of the pre-computed data (from file), and some other data that are specific to D (so that the problem is different for each D).

Sometimes I will need to pick out certain pieces of pre-computed information from the files. Other times, I will need to upload every piece of data from a (large) file.

Are there any strategies for making the IO faster?

I already have the program parallelized (MPI, via boost::mpi) for other reasons, but regardless, accessing files on the disk is making my compute time unbearable.

Any strategies or optimizations?

Currently I am doing everything with cstdio, i.e. no iostream. Will that make a big difference?

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  1. Editorial Team
    Editorial Team
    2026-06-01T08:09:24+00:00Added an answer on June 1, 2026 at 8:09 am

    The stuff that isn’t in a map is easy. You put everything in one contiguous chunk of memory that you know (like a big array, or a struct/class with no pointers), and then use write() to write it out. Later use read() to read it in, in a single operation. If the size might vary, then use one operation to read a single int with the size, allocate the memory, and then use a single read() to pull it in.

    The map part is a bit harder, since you can’t do it all in one operation. Here you need to come up with a convention for serializing it. To make the i/o as fast as possible, your best bet is to convert it from the map to an in-memory form that is all in one place and you can convert back to the map easily and quickly. If, for example your keys are ints, and your values are of constant size then you could make an array of keys, and an array of values, copy your keys into the one array and values into the other, and then write() the two arrays, possibly writing out their size as well. Again, you read things in with only two or three calls to read().

    Note that nothing ever got translated to ASCII, and there are a minimum number of system calls. The file will not be human readable, but it will be compact, and fast to read in. Three things make i/o slow: 1) system calls, if you use small reads/writes; 2) translation to/from ASCII (printf, scanf); 3) disk speed. Hard to do much about 3) (other than an SSD). You can do the read in a background thread, but you might need to block waiting for the data to be in.

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