TL;DR: Simply use vector<basic_string<int>> adj(n);
instead of vector<vector<int>> adj(n);
for graphs. Don't use it anywhere else.
Hey Codeforces! I learned from our template lord nor about basic_string. Contrary to vector, it has memory optimization. When you use a vector, it will allocate on heap and the structure of vector is similar to this:
struct vector {
size_t size;
size_t capacity;
T* data;
}
/*
64 bits - size
64 bits - capacity
64 bits - data
*/
(Not to mention, the overhead of malloc)
Which means if you are using vector<int>
with size 1, it will be using at least 28 bytes and accessing it requires indirection to a completely different part of memory, which is bad for cache.
basic_string has Short string optimization, where it uses 1 bit flag for short or long mode. In long mode it behaves like vector, but in short mode it has different memory layout. For example, basic_string in short form is similar to this (Note that capacity isn't needed as there is no allocation):
/*
1 bit - the flag
7 bits - size
32 bits - int
32 bits - int
32 bits - int
32 bits - int
32 bits - int
24 bits - unused
*/
(I'm simplifying and not including memory alignment)
So in short form, basic_string stores elements directly inside the struct when the size is small! With int, it stores up to 5 ints without allocating on heap, which makes DFS much more cache friendly and uses less memory.
How much would you ask?
Problem 1 vector<edge> 138 ms 25.1 Mib
Problem 1 basic_string<edge> 95 ms 24.2 Mib
Problem 2 vector<int> 62 ms 4.5 MB
Problem 2 basic_string<int> 62 ms 2.9 MB
edge
is a struct of 2 ints, so it's bigger and makes the optimization little less useful.
(I'm sure most of the memory consumed for problem 1 is for the IO template; also, prolbem 2 doesn't require storing adjacency list but I guessed it's a good enough benchmark)
Bear in mind that basic_string requires the element types to be "simple" types, don't use it for vectors, sets and maps, only for ints, simple structs of ints or pairs of these (pair is a bit nuanced but it works).
More about it here