Speeding up iostreams in C++

Recipes for speeding up I/O operations in C++
C++
Language
Authors

Rohan Mark Gomes

Ayan Das

Published

April 6, 2019

We often come across situations where we need to process large files. Clearly interactive input-output is not helpful in all situations. It is a common practice to use cin and cout for input-output in C++ because of it’s flexibility and ease of use. But there is quite a big problem with iostream, which is by default, much slower than standard IO functions in other languages. In this tutorial, I will quantitatively demonstrate the slowness of iostreams in C++, explain some of the reasons for its slowness and share some tips to speed it up.

Sample problem

Let’s take a simple problem to demonstrate my point. I am given a text file and I want to calculate the number of lines in it. The contents of the text file will be directed as standard input to the code so that the filename cannot be hardcoded or taken as input. This clearly rules out file input-output methods because in this tutorial I will be focusing on standard input (stdin) methods.

I will be sharing codes in JAVA, Python and C++. I have used standard functions in all the 3 languages which will be quite obvious while coding the solutions to the question. I haven’t tried to code the most optimized way of doing it as I am concerned mainly with the standard IO functions. The tests have been conducted on a text file test.txt of size 153.1 MB. My special thanks to Soumyojit Chatterjee for providing a fast and concise Python code and it’s explanation.

JAVA Solution

import java.io.*;
class test
{
    public static void main(String[] args)throws IOException
    {
        BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
        int lines = 0; String line = "";
        while(true)
        {
            line = br.readLine();
            if(line != null)
                lines++;
            else
                break;
        }
        System.out.println("Number of lines = " + lines);
    }
}

This is a simple solution to the line counting problem and since BufferedReader is used widely, I have used it here as well. The code in itself is self explanatory where, I am reading the input line by line and if no characters are read then break out of the loop and print the value of lines else increment the value of lines by 1.

Result:
[rohan@archlinux BlogCodes]$ javac test.java
[rohan@archlinux BlogCodes]$ time java -cp . test < test.txt 
Number of lines = 3031040

real    0m0.595s
user    0m0.801s
sys     0m0.094s

Subsequent runs give more or less the same time.

Python solution

import sys
print('Number of lines is =', sum(1 for _ in sys.stdin))

This solution given by Soumyojit Chatterjee is also very intuitive where a generator expression returns 1 for every line in the standard input. The number of 1’s are summed over to obtain the total number of lines.

Result:
[rohan@archlinux BlogCodes]$ time python test.py < test.txt 
Number of lines = 3031040

real    0m0.516s
user    0m0.485s
sys     0m0.027s

C++ Solution

#include <iostream>
int main()
{
    size_t lines = 0; std::string line = "";
    while(getline(std::cin, line))
        lines++;
    std::cout << "Number of lines: " << lines << '\n';
}

In this C++ solution, I am using the getline function to extract every line of the input and store it in a string variable and increment a counter by one as long as there are tokens in the standard input stream.

Result:
[rohan@archlinux BlogCodes]$ c++ test.cpp -O3
[rohan@archlinux BlogCodes]$ time ./a.out < test.txt 
Number of lines: 3031040

real    0m1.792s
user    0m1.767s
sys     0m0.023s

Final results to sample problem:

Language Time
Java 0.595s
Python 0.516s
C++ 1.792s

From the results, it is evident that C++ is lagging a lot behind here which is very bad considering the fact that C++ is a fast, compiled language used in performance critical situations and is a lower level programming language than both Python and JAVA.

Improving the C++ solution:

Before trying to explain the reason for it’s slowness, let’s look at the optimized code first:

#include <iostream>
int main()
{
    std::ios_base::sync_with_stdio(false);
    std::cin.tie(0);
    size_t lines = 0; std::string line = "";
    while(getline(std::cin, line))
        lines++;
    std::cout << "Number of lines: " << lines << '\n';
}

Testing this code we obtain:

[rohan@archlinux BlogCodes]$ c++ test.cpp -O3
[rohan@archlinux BlogCodes]$ time ./a.out < test.txt 
Number of lines: 3031040

real    0m0.111s
user    0m0.080s
sys     0m0.030s

A drastic 16x improvement just by adding two more lines!!! Let’s try to understand what’s going on here which brings such a massive improvement.

The real reason for it’s slowness

Historically C++ was designed as an extension to C. So much so that, C++ was initially known as C with Classes before being renamed to C++ in 1983. Till today, backwards compatibility with C and the older standards of C++ is of big importance to the ISO C++ Committee. Due to this reason, the C-streams for input-output and the C++ iostreams also need to be synchronized so that when both of them are used in the same code, no undefined behaviour occurs. By default C++ streams are synchronized with their C-stream counterparts, i.e., the moment any operation is applied to any C++ stream, the same operation is also applied to the corresponding C-stream. This allows the free mixing of C and C++ streams in the same code but that comes at a big performance penalty as seen in the above case. The IO operations are unbuffered and are thread-safe by default when they’re synchronized. Thus the unbuffered nature of the iostreams and their synchronization with C-streams is the real reason why C++ iostreams are very slow. The line std::ios_base::sync_with_stdio(false); removes this very synchronization between C and C++ streams. Then the C++ streams and the C streams maintain their buffers independently. Thus the removal of this synchronization and the conversion from an unbuffered to buffered behaviour gives a big speedup. The next line std::cin.tie(0); is generally not required because in this case the removal of synchronization is generally enough to get the big speedup, but the next line removes the synchronization between the C++ input and output buffers which gives a slight more speedup in most cases.

On reading the above paragraph, it might appear to us that if we get such a big speedup why not add these two lines everytime we use C++ iostreams to speed up our input and output operations. Sounds too good to be true??? Had it been so, the synchronization would have been turned off by default. Let’s look at some big caveats on removing the synchronization to get a better understanding of the concept.

First Caveat

Here I will show the problem which arises on removing synchronization between C and C++ streams. Let’s investigate a seemingly innocent-looking code:

#include <iostream>
#include <stdio.h>
int main()
{
    std::ios_base::sync_with_stdio(false);
    for(int i = 0; i < 10; i++)
        if(i % 2 == 0)
            std::cout << i << '\n';
        else
            printf("%d\n", i);
}

Can you try to predict the output by yourself without looking at the answer below??? If you guessed the program to print the digits from 0 to 9 sequentially with one digit per line, you are surely mistaken!!!

[rohan@archlinux BlogCodes]$ c++ test.cpp 
[rohan@archlinux BlogCodes]$ ./a.out 
1
3
5
7
9
0
2
4
6
8

The reason for this strange output should become obvious by now. Since the synchronization between C and C++ streams have been removed, both of them maintain their buffers independent of each other. So when we are writing printf("%d\n", i); or std::cout << i << '\n'; the respective buffer is filled. After the loop is terminated, before the program ends, the output buffer needs to be emptied. So while putting the data to the output stream, the C stream gets the preference and so the odd numbers which were present in the output buffer of printf gets printed followed by the data in the output buffer of cout. This preference is purely implementation dependant and might vary across different platforms.

Second Caveat

Let’s now try to understand the problem faced on using std::cin.tie(0);. To do that, let us investigate another piece of code:

#include <iostream>
int main()
{
    std::ios_base::sync_with_stdio(false);
    std::cin.tie(0);
    std::string name; int age;
    std::cout << "Enter your name: \n";
    std::cin >> name;
    std::cout << "Enter your age: \n";
    std::cin >> age;
    std::cout << "Your name: " << name << '\n';
    std::cout << "Your age: " << age << '\n';
}

Please try to predict the input-output behaviour of the program before going forward. As you expected, the behaviour won’t be straightforward. If you thought that the program will first promt you to Enter your name: and then you enter your name, then prompts you to Enter your age: and then you enter your age and after that your name and age are printed with Your name: and Your age: prompts respectively; you are wrong again!!! Please look at the video carefully to understand the peculiar behaviour:

The Second Caveat

The Second Caveat

The video should be self explanatory. The pecularity occurs because with std::cin.tie(0) the synchronization between cin and cout has been removed. Thus the data of the output buffer of cout is not printed as long as it is not full or the or the program has not reached it’s end. This is why the prompts Enter your name: and Enter your age: are sent to the output buffer but does not get printed and the program asks for input from the standard input stream. When all the input operations have been completed and there is no other job left other than printing the data to the standard output stream, the data gets printed.

These two programs should be enough to demonstrate the strange behaviour when IO synchronization is turned off. So please be careful and think twice before using these functions. With all these knowledge gained, let’s try to solve a problem which needs high speed input processing.

Pro tip: Never turn off synchronization in a header file. Else it might be included unknowingly leading to strange behaviour and may God help us all.

The Problem

Let’s have a look at the Enormous Input Test problem in Codechef. This is one of the earliest beginner problems in Codechef and I feel that this is a great problem to start our discussion. The problem statement basically states that in the first line there will be two space separated integers n and k. The next n lines will have one integer (t[i]) each not exceeding 10^9. It’s also given that both n and k are positive integers <= 10^7. Our job is to find the number of integers t[i] which are divisible by k. To make it a bit more interesting, we will design our own code to generate the test cases and increase the bounds of n and k to 10^8.

Designing our test case generator

#include <iostream>
#include <random>

int main()
{
    std::ios_base::sync_with_stdio(false);
    std::cin.tie(0);
    int n, k;
    std::cin >> n >> k;
    std::mt19937_64 rng; rng.seed(std::random_device()());
    std::uniform_int_distribution<int> dis(1, 1000000000);
    std::cout << n << ' ' << k << '\n';
    for(int i = 1; i <= n; i++)
        std::cout << dis(rng) << '\n';
}

Integers n and k are taken as input and the Mersenne Twister Engine is used as our Random Number Generator. With these, we are preparing our test case generator and saving our code to a file generator.cpp and compiling with the following commands:

[rohan@archlinux BlogCodes]$ c++ --version
c++ (GCC) 8.2.1 20181127
Copyright (C) 2018 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

[rohan@archlinux BlogCodes]$ c++ generator.cpp -std=c++17 -Ofast -march=native -o generator

I am using GCC 8.2.1 which has support for C++17. In case you are using older compilers, adjust your flags accordingly. To understand the optimization flags, have a look at the GCC optimization flags. In this case, I do not care about synchronization, so I have turned it off to speed up the generation process. Let us now generate three text files test1.txt, test2.txt and test3.txt with the bounds of n and k being 10^6, 10^7 and 10^8 respectively.

[rohan@archlinux BlogCodes]$ ./generator > test1.txt 
1000000 3
[rohan@archlinux BlogCodes]$ ./generator > test2.txt 
10000000 4
[rohan@archlinux BlogCodes]$ ./generator > test3.txt 
100000000 5
[rohan@archlinux BlogCodes]$ ls -l
total 1071980
-rwxr-xr-x 1 rohan rohan     19792 Apr  8 03:22 generator
-rw-r--r-- 1 rohan rohan       384 Apr  8 03:20 generator.cpp
-rw-r--r-- 1 rohan rohan   9888480 Apr  8 03:48 test1.txt
-rw-r--r-- 1 rohan rohan  98890665 Apr  8 03:48 test2.txt
-rw-r--r-- 1 rohan rohan 988890850 Apr  8 03:49 test3.txt

Hurray!!! So we have created the three text files of size 9.4 MB, 94.3 MB and 943.1 MB for testing. Let’s now start our attempts at solving this problem. We will be using the time command in Linux to maintain uniformity which gives reasonably accurate results for our purpose.

Attempt 1: cin

#include <iostream>
int main()
{
    int n, k, count = 0;
    std::cin >> n >> k;
    for(int i = 1; i <= n; i++)
    {
        int x; std::cin >> x;
        if(x % k == 0)
            count++;
    }
    std::cout << count << '\n';
}

The code is straight-forward and doesn’t need any explanation. Let’s compile it and then verify that it is correct before testing it with our big text files.

[rohan@archlinux BlogCodes]$ c++ cin.cpp -O3 -march=native -o cin
[rohan@archlinux BlogCodes]$ ./generator > tmp.txt
7 5
[rohan@archlinux BlogCodes]$ cat tmp.txt 
7 5
7852651
987500822
941299498
165101286
342858592
854548561
978235080
[rohan@archlinux BlogCodes]$ ./cin < tmp.txt 
1

Thus the code is correct!!! Because it is clearly evident that there is just one number which is divisible by 5. Let’s now test it against our big guns :)

[rohan@archlinux BlogCodes]$ time ./cin < test1.txt 
333392

real    0m0.292s
user    0m0.286s
sys     0m0.004s
[rohan@archlinux BlogCodes]$ time ./cin < test2.txt 
2500370

real    0m2.664s
user    0m2.623s
sys     0m0.024s
[rohan@archlinux BlogCodes]$ time ./cin < test3.txt 
20002602

real    0m27.761s
user    0m27.563s
sys     0m0.163s

Thus our timings for the big guns are 0.292s, 2.664s and 27.761s. The timings for subsequent runs give more or less same timings. So there goes cin, can we do better???

Attempt 2: cin with synchronization turned off

#include <iostream>
int main()
{
    std::ios_base::sync_with_stdio(false);
    std::cin.tie(0);
    int n, k, count = 0;
    std::cin >> n >> k;
    for(int i = 1; i <= n; i++)
    {
        int x; std::cin >> x;
        if(x % k == 0)
            count++;
    }
    std::cout << count << '\n';
}

I am sure that you guessed that this was coming. Turning off synchronization is an obvious solution, because we do not want the output to be interactive here and neither do we need interoperability with C streams. Let’s compile this code and test it against our big guns.

[rohan@archlinux BlogCodes]$ c++ cin_nosync.cpp -O3 -march=native -o cin_nosync
[rohan@archlinux BlogCodes]$ time ./cin_nosync < test1.txt 
333392

real    0m0.122s
user    0m0.118s
sys     0m0.004s
[rohan@archlinux BlogCodes]$ time ./cin_nosync < test2.txt 
2500370

real    0m0.911s
user    0m0.896s
sys     0m0.013s
[rohan@archlinux BlogCodes]$ time ./cin_nosync < test3.txt 
20002602

real    0m8.865s
user    0m8.684s
sys     0m0.173s

That’s a decent performance boost over normal cin and cout!!! But this was expected. We have improved our timings to 0.122s, 0.911s and 8.865s. Let’s try scanf and printf which are often recommended as alternatives when cin and cout perform slow.

Attempt 3: scanf and printf

#include <cstdio>

int main()
{
    int n, k, count = 0;
    scanf("%d %d", &n, &k);
    for(int i = 1; i <= n; i++)
    {
        int x; scanf("%d", &x);
        if(x % k == 0)
            count++;
    }
    printf("%d\n", count);
}

Testing it:

[rohan@archlinux BlogCodes]$ c++ scanf.cpp -O3 -march=native -o scanf
[rohan@archlinux BlogCodes]$ time ./scanf < test1.txt 
333392

real    0m0.088s
user    0m0.081s
sys     0m0.007s
[rohan@archlinux BlogCodes]$ time ./scanf < test2.txt 
2500370

real    0m0.802s
user    0m0.791s
sys     0m0.010s
[rohan@archlinux BlogCodes]$ time ./scanf < test3.txt 
20002602

real    0m8.244s
user    0m7.989s
sys     0m0.216s

The results are quite impressive!!! And we have further improved our timings by a slight margin. We have reached 0.088s, 0.802s and 8.244s. Here we have seen that scanf and printf have outperformed cin and cout. But the results may vary slightly on other platforms and compilers.

Till now, we have been dealing with buffered input with scanf and unsynchronized cin where the data read from the standard input stream is stored internally in a buffer. Let’s now try a new approach where the data from the standard input stream are read one character at a time and instead of storing it in a buffer, it will be put to use immediately. We will use getchar_unlocked for this purpose.

Attempt 4: getchar_unlocked

It is to be kept in mind that, getchar_unlocked is a POSIX function and is available for POSIX systems (Linux, Mac etc). If you are using Windows, use getchar which is cross platform and is part of the C++ Standard. I will be using getchar_unlocked here because it is faster as it is not thread-safe, which does not matter as these are sequential programs, moreover I am using a Linux distribution, so I have this function available. Let’s look at the usage of this function for our use-case:

#include <iostream>

int input()
{
    char c;
    c = getchar_unlocked();
    while(c <= ' ')
        c = getchar_unlocked();
    int s = 0;
    while(c > ' ')
    {
        s = s * 10 + (c - '0');
        c = getchar_unlocked();
    }
    return s;
}
int main()
{
    int a, b, count = 0;
    a = input();
    b = input();
    while(a--)
    {
        int x = input();
        if(!(x % b))
            ++count;
    }
    std::cout << count << '\n';
    return 0;
}

The input function takes in a positive integer using getchar_unlocked and returns it. If you have to use this function for taking input floating points, numbers or any other formats, modify the input function accordingly. I have deliberately not generalized the input function to keep it absolutely simple and specific for this problem. ASCII value of space is 32. The digits 0 - 9 have ASCII values from 48 to 57. In the input function, we input one character and as long as it is a space or any character before that, we keep on taking input as it is redundant data. The moment we get a character with ASCII value greater than 32, we break out of the while loop. We initialize an integer variable s with 0 which will store the final integer being entered by the user. So we enter another loop where we keep on taking input character by character as long as the ASCII value is greater than 32. Since we are dealing with numbers only, I need not give any other long if condition. The input character is then changed to the appropriate digit and appended at the end of s. For example, let’s say the user entered 956. Initially, s = 0, so s = 0 * 10 + (57 - 48) => s = 0 * 10 + 9 => s = 9, as the ASCII value of 9 is 57 and that of 0 is 48. Then when 5 is input, s = 9 * 10 + (53 - 48) => s = 90 + 5 => s = 95. Continuing in this manner, s = 95 * 10 + (54 - 48) => s = 95 * 10 + 6 => s = 956. This is how the input function works. The main function is same as before. Let’s look at how this solution performs:

[rohan@archlinux BlogCodes]$ c++ getchar.cpp -O3 -march=native -o getchar
[rohan@archlinux BlogCodes]$ time ./getchar < test1.txt 
333392

real    0m0.023s
user    0m0.016s
sys     0m0.007s
[rohan@archlinux BlogCodes]$ time ./getchar < test2.txt 
2500370

real    0m0.173s
user    0m0.159s
sys     0m0.014s
[rohan@archlinux BlogCodes]$ time ./getchar < test3.txt 
20002602

real    0m1.648s
user    0m1.499s
sys     0m0.147s

That’s quite FAST and is a big improvement over the previous methods. We have processed a text file of size 943 MB in 1.65s, which gives a processing speed of about 572 MB/s. Hence, this approach works like a charm. We have improved our timings to 0.023s, 0.173s and 1.648s. Can we do any better???

Let’s pause for a moment and think about what we have done till now. We started out with cin which was synchronized with C-streams and unbuffered. We improved it by removing the synchronization, making it thread-unsafe and buffered. Then we tried scanf which gives nearly the same performance. In both these approaches, the Input Buffer is maintained internally. We have very less control over it. In our next approach with getchar_unlocked we completely removed the concept of buffers and are taking input character by character and processing it directly. This significantly reduced the input time.

Let’s take one more shot at buffered input with the subtle difference that, now we are going to manage the buffer manually. We will create and maintain our own buffer of a specific size. We will read a chunk of characters with every read operation and store that data in the buffer we are maintaining. And now we will iterate over that buffer and access the chunk of characters and process them. In this way, we are reducing the number of disk read operations, and are accessing the characters in the buffer which are stored in the RAM which is way faster. But then it might come to your mind that why not load the entire file into the RAM and then iterate over it? This is clearly a good possibility but is limited to small files only. For very large files, say a file of size 5 GB or more, loading it into my 8 GB RAM is clearly not a good idea. So the file is loaded into the RAM in chunks at each time which can fit into the memory easily. It’s obvious that the choice of the buffer size which holds the chunk of data changes with the amount of RAM available.

Attempt 5: fread

To implement the idea of the manual buffered input, we will use fread. Let’s have a look at the code to get a proper insight:

#include <iostream>
#include <vector>

int main()
{
    int n, k, count = 0, num = 0, ans = 0; std::cin >> n >> k;
    std::cin.get();
    size_t size = 1024 * 1024;
    std::vector<char> vec(size);
    while(count < n)
    {
        size_t len = std::fread(vec.data(), sizeof(char), size, stdin);
        if(len == 0)
            break;
        for(size_t i = 0; i < len; i++)
        {
            const char &ch = vec[i];
            if(ch >= '0' && ch <= '9')
            num = num*10+ch-'0';
            else
            {
            if(num % k == 0)
                ans++;
            num = 0;
            count++;
            }
        }
    }
    std::cout << ans << '\n';
}

I have used cin to take input for n and k. Now before using fread directly, we should keep in mind that, the trailing newline after k is not input by cin, so it will remain in the stream and will cause problems in our processing if taken in by fread. So I have used cin.get to grab that trailing newline and let fread deal with the other characters. After a lot of experimentation, I have found out that on my machine a buffer size of 1024 * 1024 (a million), works best in most cases. The rest of the code is quite straightforward and can be understood after a careful inspection. The vector of characters vec is the buffer we are maintaining. After every character is read, it is appended to num which is the number being created. The moment a newline is encountered, it denotes the end of a line, as well as a number. So the value of count is increased by 1 and since num is now complete, it is checked for divisibility by k and the value of ans is increased accordingly. Then the value of num is set to 0 again and reused. Let’s now have a look at fread in action:

[rohan@archlinux BlogCodes]$ c++ fread.cpp -O3 -march=native -o fread
[rohan@archlinux BlogCodes]$ time ./fread < test1.txt 
333392

real    0m0.018s
user    0m0.007s
sys     0m0.011s
[rohan@archlinux BlogCodes]$ time ./fread < test2.txt 
2500370

real    0m0.120s
user    0m0.090s
sys     0m0.030s
[rohan@archlinux BlogCodes]$ time ./fread < test3.txt 
20002602

real    0m1.033s
user    0m0.952s
sys     0m0.080s

That’s even faster than getchar_unlocked!!! The effort of maintaining a manual buffer has actually paid off. We have now improved our timings to 0.018s, 0.120s and 1.033s. Let’s have a look at a pure C++ way of managing buffered input with a manual buffer just like fread.

Note: For getchar_unlocked and fread, never remove the synchronization between C and C++ streams as these are functions from the C standard library using C streams internally. We have used these functions in our C++ code.

Attempt 6: cin.read

#include <iostream>
#include <vector>
#include <string>

int main()
{
    int n, k, count = 0, num = 0, ans = 0; std::cin>>n>>k;
    const size_t buffer_size=1024*1024;
    std::vector<char> buffer(buffer_size);
    std::cin.get();
    while(count < n)
    {
        std::cin.read(buffer.data(), buffer_size);
        int len = std::cin.gcount();
        if(len == 0)
            break;
        for(int i = 0; i < len; i++)
        {
            const char &ch = buffer[i];
            if(ch >= '0' && ch <= '9')
                num = num * 10 + ch - '0';
            else
            {
                if(num % k == 0)
                    ans++;
                num = 0;
                count++;
            }
        }
    }
    std::cout << ans <<"\n";
}

The code is almost exactly like fread with the only exception that the number of parameters to cin.read are lesser and it does not return the number of characters read unlike fread. Instead we have to use another function cin.gcount for that purpose. Let’s test this solution against our big guns:

[rohan@archlinux BlogCodes]$ c++ cin_read.cpp -O3 -march=native -o cin_read
[rohan@archlinux BlogCodes]$ time ./cin_read < test1.txt 
333392

real    0m0.034s
user    0m0.027s
sys     0m0.006s
[rohan@archlinux BlogCodes]$ time ./cin_read < test2.txt 
2500370

real    0m0.111s
user    0m0.097s
sys     0m0.014s
[rohan@archlinux BlogCodes]$ time ./cin_read < test3.txt 
20002602

real    0m1.024s
user    0m0.909s
sys     0m0.113s

That’s slightly faster than fread, but on an average, fread is almost as fast as cin.read for practical purposes. Thus we have improved our timings to 0.034s, 0.111s and 1.024s. That’s a big improvement considering the fact that we had started out with a timing of 27.761s for our 943.1 MB text file.

Summary of timings:

IO Method Size = 9.4 MB Size = 94.3 MB Size = 943.1 MB
cin 0.292s 2.664s 27.761s
cin_nosync 0.122s 0.911s 8.865s
scanf 0.088s 0.802s 8.244s
getchar_unlocked 0.023s 0.173s 1.648s
fread 0.018s 0.120s 1.033s
cin.read 0.034s 0.111s 1.024s

But then, I won’t be surprised if you are a bit disappointed with the last three solutions where the timings are almost equal. So to quench this thurst for differentiating between them let’s go beyond the limits and increase the value of n to 3 * 108, let alone the Codechef limit of 107 because even our big guns have fallen short of the potential of these methods. The limit of 10 * 7 is really dwarfed by our current limit of 3 * 10^8 which creates a gigantic text file of size 2.8 GB. Let’s generate the file and begin our testing:

[rohan@archlinux BlogCodes]$ ./generator > test4.txt 
300000000 120
[rohan@archlinux BlogCodes]$ time ./getchar < test4.txt 
2500623

real    0m4.864s
user    0m4.369s
sys     0m0.490s
[rohan@archlinux BlogCodes]$ time ./fread < test4.txt 
2500623

real    0m3.069s
user    0m2.789s
sys     0m0.277s
[rohan@archlinux BlogCodes]$ time ./cin_read < test4.txt 
2500623

real    0m2.961s
user    0m2.622s
sys     0m0.323s

From the above results, it is pretty evident that cin.read ends up to be the fastest among the three followed by fread and then getchar_unlocked. But there was a small peculiarity that I noticed with cin.read. You’ll find that I have not removed the synchronization between C and C++ streams in the cin.read code despite using C++ streams only. In fact, removing the synchronization actually slowed it down a bit and puts it behind fread. This is mainly implementation dependant and might be different in your case.

By now you should have got a fair idea about speeding up your input methods in C++. If cin appears to be slow, you know you have a lot of other good options to fall back upon. That’s pretty much everything I had to say about the topic. For further reading have a look at fgets and sscanf and try using these functions alongwith the methods described above to suit your purpose. Also have a look at file input-output in C++ and memory mapping techniques for getting big benefits in file IO.

Citation

BibTeX citation:
@online{mark_gomes2019,
  author = {Mark Gomes, Rohan and Das, Ayan},
  title = {Speeding up Iostreams in {C++}},
  date = {2019-04-06},
  url = {https://ayandas.me/blogs/2019-04-06-speeding-up-iostreams-in-c++.html},
  langid = {en}
}
For attribution, please cite this work as:
Mark Gomes, Rohan, and Ayan Das. 2019. “Speeding up Iostreams in C++.” April 6, 2019. https://ayandas.me/blogs/2019-04-06-speeding-up-iostreams-in-c++.html.