From:

=?ISO-8859-1?Q?Erik_Wikstr=F6m?= <Erik-wikstrom@telia.com>

Newsgroups:

comp.lang.c++

Date:

Tue, 26 Jun 2007 07:34:50 GMT

Message-ID:

<uk3gi.2955$ZA.1372@newsb.telia.net>

Zachary Turner wrote:

But would that not show the asymptotic difference and not the "constant"

difference in time to execute a single operation?

On Jun 25, 3:51 pm, desktop <f...@sss.com> wrote:

sure, just write a benchmark test. There is no more precise way,

because of course the time depends on your CPU, your compiler, your

operating system, and what appliactions are running at the time. A

simple test like the following should work (on windows).

std::vector<int> intVector;

populateIntVector(&intVector);

std::set<int> intSet;

populateIntSet(&intSet);

DWORD d = timeGetTime();

for (int i=0; i < 1000000; ++i)

{

// Perform Vector operation

}

DWORD d2 = timeGetTime();

for (int i=0; i < 1000000; ++i)

{

// Perform set operation

}

DWORD d3 = timeGetTime();

DWORD millisecondsForVector = d2 - d;

DWORD millisecondsForSet = d3 - d2;

double millisecondsForSingleVectorOp = (double)millisecondsForVector /

(double)1000000;

double millisecondsForSingleSetOp = (double)millisecondsForSet /

(double)1000000;

Erik Wikstr?m wrote:

Is it possible to make an exact measurement in the difference in time

for 1 operation for a set and a list?- Hide quoted text -

- Show quoted text -

On 2007-06-25 22:21, desktop wrote:

In operations yes, not necessarily in time. If the operations on the

list takes 1 time and the operations on the set takes 50,000 then

they'll be equally fast. This will of course not be true in any

implementation (the set will be significantly faster than the list) but

it shows that just because one container/algorithm has a better

asymptotic running time it will in fact perform better. All it says is

that for a sufficiently large set of input, the algorithm will perform

better.

In practice you'll often find that using a vector for small sets will be

faster than most other containers, even if you need to traverse the

whole vector.

If I have a sorted std::list with 1.000.000 elements it takes

1.000.000 operations to find element with value = 1.000.000 (need to

iterator through the whole list).

In comparison, if I have a std::set with 1.000.000 element it will

only take approx lg 1.000.000 = 20 operations! Can it really be true

that the difference is a factor of 1.000.000/20 = 50.000 in this case?

1.000.000 operations to find element with value = 1.000.000 (need to

iterator through the whole list).

In comparison, if I have a std::set with 1.000.000 element it will

only take approx lg 1.000.000 = 20 operations! Can it really be true

that the difference is a factor of 1.000.000/20 = 50.000 in this case?

In operations yes, not necessarily in time. If the operations on the

list takes 1 time and the operations on the set takes 50,000 then

they'll be equally fast. This will of course not be true in any

implementation (the set will be significantly faster than the list) but

it shows that just because one container/algorithm has a better

asymptotic running time it will in fact perform better. All it says is

that for a sufficiently large set of input, the algorithm will perform

better.

In practice you'll often find that using a vector for small sets will be

faster than most other containers, even if you need to traverse the

whole vector.

Is it possible to make an exact measurement in the difference in time

for 1 operation for a set and a list?- Hide quoted text -

- Show quoted text -

sure, just write a benchmark test. There is no more precise way,

because of course the time depends on your CPU, your compiler, your

operating system, and what appliactions are running at the time. A

simple test like the following should work (on windows).

std::vector<int> intVector;

populateIntVector(&intVector);

std::set<int> intSet;

populateIntSet(&intSet);

DWORD d = timeGetTime();

for (int i=0; i < 1000000; ++i)

{

// Perform Vector operation

}

DWORD d2 = timeGetTime();

for (int i=0; i < 1000000; ++i)

{

// Perform set operation

}

DWORD d3 = timeGetTime();

DWORD millisecondsForVector = d2 - d;

DWORD millisecondsForSet = d3 - d2;

double millisecondsForSingleVectorOp = (double)millisecondsForVector /

(double)1000000;

double millisecondsForSingleSetOp = (double)millisecondsForSet /

(double)1000000;

But would that not show the asymptotic difference and not the "constant"

difference in time to execute a single operation?

No, that would give you an average (from one million tries) of the time

needed to perform the operation (under the best circumstances), or as a

statistician would say, the expected running time of the operation.

--

Erik Wikstr?m

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