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performance map c++ find (g++ (GCC) 4.4.7 20120313 (Red Hat 4.4.7-3))


performance map c++ find (g++ (GCC) 4.4.7 20120313 (Red Hat 4.4.7-3))

By : user2956543
Date : November 22 2020, 10:56 AM
should help you out Answering my own questions as this problem might be occurring to other users as well. I was able to improve perf using the recommendations in the comments section of my question .
@RetiredNinja suggested me to use boost unordered map
code :


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Change in precision due to use of inline function in C++ std::vector with g++ 4.4.7 20120313 in 32 bit

Change in precision due to use of inline function in C++ std::vector with g++ 4.4.7 20120313 in 32 bit


By : Zac Zhang
Date : March 29 2020, 07:55 AM
I hope this helps . Probably the old x87 fun feature again, 80 bits registers. Spilling that register to memory causes a rounding to 64 bits, and happens at unpredictable moments. Not at all unique to C++, C has the same issue. In Java it's "complicated"
Fixed by moving to 64 bit builds and SSE.
Performance hit from using std::find

Performance hit from using std::find


By : bboutaire
Date : March 29 2020, 07:55 AM
Any of those help With good optimizing compiler which knows how to unroll loops, you will end up with the pretty much same assembly and same performance.
Proof:
code :
#include <algorithm>
#include <initializer_list>

template<typename T1,typename T2>
bool contains(const T1 &container,const T2 &item) {
    return(std::find(container.begin(),container.end(),item)!=container.end());
}

bool foo(int a, int b, int c, int d, int e) {
  return contains(std::initializer_list<int>({a, b, c, d, e}), 5);
}
foo(int, int, int, int, int):
        cmpl    $5, %edi        #, a
        je      .L6 #,
        cmpl    $5, %esi        #, b
        je      .L6 #,
        cmpl    $5, %edx        #, c
        je      .L6 #,
        cmpl    $5, %ecx        #, d
        je      .L6 #,
        cmpl    $5, %r8d        #, e
        sete    %al     #, D.75010
        ret
bool foo(int a, int b, int c, int d) {
  if (a == 5)
    return true;
  else if (b == 5)
    return true;
  else if (c == 5)
    return true;
  else if (d == 5)
    return true;
  return false;
}
foo(int, int, int, int):
        cmpl    $5, %edx        #, c
        sete    %dl     #, D.74611
        cmpl    $5, %ecx        #, d
        sete    %al     #, D.74611
        orl     %edx, %eax        # D.74611, D.74611
        cmpl    $5, %esi        #, b
        sete    %dl     #, D.74611
        orl     %edx, %eax        # D.74611, D.74611
        cmpl    $5, %edi        #, a
        sete    %dl     #, D.74611
        orl     %edx, %eax        # D.74611, D.74611
        ret
Which find gives better performance in Rails, Child.find(child_id) or parent.children.find(child_id)?

Which find gives better performance in Rails, Child.find(child_id) or parent.children.find(child_id)?


By : Muhammad Umair
Date : March 29 2020, 07:55 AM
I hope this helps . They are calling the same method.
http://apidock.com/rails/ActiveRecord/FinderMethods/find
MongoDB unwind in find()? and Performance better in find() queries?

MongoDB unwind in find()? and Performance better in find() queries?


By : Julia
Date : March 29 2020, 07:55 AM
wish helps you If all you need is filtering out, simply use the $filter operator:
code :
db.cms.aggregate([
{
    $project: {
        values : {
            $filter: {
                input: "$values",
                as: "value",
                cond: {
                    $and: [
                        { $ifNull: [ "$$value.type", false ] },
                        { $eq: [ "$$value.sensor", "V1" ] },
                        { $eq: [ "$$value.timestamp", "2018-02-07 14:00:16.163" ] },
                    ]
                }
            }
        }
    }
}
])
Performance difference between set::find and <algorithm> find

Performance difference between set::find and <algorithm> find


By : Tony
Date : September 24 2020, 07:00 AM
this one helps. std::find is just a linear search as it assumes nothing on the iterators.
std::set::find utilizes set's tree structure to achieve log-fast performance.
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