I want to implement a very long boolean array (as a binary genome) and access some intervals to check if that interval is all true or not, and in addition I want to change some intervals value,
For example, I can create 4 representations:
boolean binaryGenome1[10e6]={false};
vector<bool> binaryGenome2; binaryGenome2.resize(10e6);
vector<char> binaryGenome3; binaryGenome3.resize(10e6);
bitset<10e6> binaryGenome4;
and access this way:
inline bool checkBinGenome(long long start , long long end){
for(long long i = start; i < end+1 ; i++)
if(binaryGenome[i] == false)
return false;
return true;
}
inline void changeBinGenome(long long start , long long end){
for(long long i = start; i < end+1 ; i++)
binaryGenome[i] = true;
}
vector<char> and normal boolean array (ass stores every boolean in a byte) both seem to be a poor choice as I need to be efficient in space. But what are the differences between vector<bool> and bitset?
Somewhere else I read that vector has some overhead as you can choose it's size and compile time - "overhead" for what - accessing? And how much is that overhead?
As I want to access array elements many times using CheckBinGenome() and changeBinGenome(), what is the fastest implementation?
Use std::bitset It's the best.
If the length of the data is known at compile time, consider std::array<bool> or std::bitset. The latter is likely to be more space-efficient (you'll have to measure whether the associated extra work in access times outweighs the speed gain from reducing cache pressure - that will depend on your workload).
If your array's length is not fixed, then you'll need a std::vector<bool> or std::vector<char>; there's also boost::dynamic_bitset but I've never used that.
If you will be changing large regions at once, as your sample implies, it may well be worth constructing your own representation and manipulating the underlying storage directly, rather than one bit at a time through the iterators. For example, if you use an array of char as the underlying representation, then setting a large range to 0 or 1 is mostly a memset() or std::fill() call, with computation only for the values at the start and end of the range. I'd start with a simple implementation and a good set of unit tests before trying anything like that.
It is (at least theoretically) possible that your Standard Library has specialized versions of algorithms for the iterators of std::vector<bool>, std::array<bool> and/or std::bitset that do exactly the above, or you may be able to write and contribute such specializations. That's a better path if possible - the world may thank you, and you'll have shared some of the maintenance responsibility.
Important note
If using std::array<bool>, you do need to be aware that, unlike other std::array<> instantiations, it does not implement the standard container semantics. That's not to say it shouldn't be used, but make sure you understand its foibles!
E.g., checking whether all the elements are true
I am really NOT sure whether this will give us more overheads than speedup or not. Actually I think that nowadays CPU can do this quite fast, are you really experiencing a poor performance? (or is this just a skeleton of your real problem?)
#include <omp.h>
#include <iostream>
#include <cstring>
using namespace std;
#define N 10000000
bool binaryGenome[N];
int main() {
memset(binaryGenome, true, sizeof(bool) * N);
int shouldBreak = 0;
bool result = true;
cout << result << endl;
binaryGenome[9999995] = false;
bool go = true;
uint give = 0;
#pragma omp parallel
{
uint start, stop;
#pragma omp critical
{
start = give;
give += N / omp_get_num_threads();
stop = give;
if (omp_get_thread_num() == omp_get_num_threads() - 1)
stop = N;
}
while (start < stop && go) {
if (!binaryGenome[start]) {
cout << start << endl;
go = false;
result = false;
}
++start;
}
}
cout << result << endl;
}
I have an if statement that is currently never executed, however if I print something to the screen it takes over ten times longer for the program to run than if a variable is declared. Doing a bit of research online this seems to be some kind of branch prediction issue. Is there anything I can do to improve the program speed?
Basically both myTest and myTest_new return the same thing except one is a macro and one is a function. I am just monitoring the time it takes for bitTest to execute. and it executes in 3 seconds with just declaration in if statement but takes over a minute when Serial.print is in if statement even though neither are executed.
void bitTest()
{
int count = 0;
Serial1.println("New Test");
int lastint = 0;
Serial1.println("int");
for (int index = -2147483647; index <= 2147483647; index+=1000) {
if (index <= 0 && lastint > 0) {
break;
}
lastint = index;
for (int num = 0; num <= 31; num++) {
++1000;
int vcr1 = myTest(index, num);
int vcr2 = myTest_new(index, num);
if (vcr1 != vcr2) {
Serial1.println("Test"); // leave this println() and it takes 300 seconds for the test to run
//int x = 0;
}
} // if (index)
} // for (index)
Serial1.print("count = ");
Serial1.println(count);
return;
}
It is much less likely to be caused by a branch prediction (that branch prediction shouldn't be influenced by what you do inside your code) but by the fact that
{
int x = 0;
}
simply does nothing, because the scope of x ends at }, so that the compiler simply ditches the whole if clause, including the check. Note that this is only possible because the expression that if checks has no side effects, and neither does the block that would get executed.
By the way, the code you showed would usually directly be "compiled away", because the compiler, at compile time, can determine whether the if clause could ever be executed, unless you explicitly tell the compiler to omit such safe optimizations. Hence, I kind of doubt your "10 times as slow" measurement. Either the code you're showing isn't the actual example on which you demonstrate this, or you should turn on compiler optimization prior to doing performance comparisons.
The reason why your program takes forever is that it's buggy:
for (int index = -2147483647; index <= 2147483647; index+=1000) {
simply: at a very large index close to the maximum integer value, a wrap-around will occur. There's no "correct" way for your program to terminate. Hence you invented your strange lastint > 0 checking.
Now, fix up the loop (I mean, you're really just using every 1000th element, so why not simply loop index from 0 to 2*2147483?)
++1000;
should be illegal in C, because you can't increase a constant numeral. This is very much WTF.
All in all, your program is a mess. Re-write it, and debug a clean, well-defined version of it.
I happen to notice that in C++ the first random number being called with the std rand() method is most of the time significant smaller than the second one. Concerning the Qt implementation the first one is nearly always several magnitudes smaller.
qsrand(QTime::currentTime().msec());
qDebug() << "qt1: " << qrand();
qDebug() << "qt2: " << qrand();
srand((unsigned int) time(0));
std::cout << "std1: " << rand() << std::endl;
std::cout << "std2: " << rand() << std::endl;
output:
qt1: 7109361
qt2: 1375429742
std1: 871649082
std2: 1820164987
Is this intended, due to error in seeding or a bug?
Also while the qrand() output varies strongly the first rand() output seems to change linearly with time. Just wonder why.
I'm not sure that could be classified as a bug, but it has an explanation. Let's examine the situation:
Look at rand's implementation. You'll see it's just a calculation using the last generated value.
You're seeding using QTime::currentTime().msec(), which is by nature bounded by the small range of values 0..999, but qsrand accepts an uint variable, on the range 0..4294967295.
By combining those two factors, you have a pattern.
Just out of curiosity: try seeding with QTime::currentTime().msec() + 100000000
Now the first value will probably be bigger than the second most of the time.
I wouldn't worry too much. This "pattern" seems to happen only on the first two generated values. After that, everything seems to go back to normal.
EDIT:
To make things more clear, try running the code below. It'll compare the first two generated values to see which one is smaller, using all possible millisecond values (range: 0..999) as the seed:
int totalCalls, leftIsSmaller = 0;
for (totalCalls = 0; totalCalls < 1000; totalCalls++)
{
qsrand(totalCalls);
if (qrand() < qrand())
leftIsSmaller++;
}
qDebug() << (100.0 * leftIsSmaller) / totalCalls;
It will print 94.8, which means 94.8% of the time the first value will be smaller than the second.
Conclusion: when using the current millisecond to seed, you'll see that pattern for the first two values. I did some tests here and the pattern seems to disappear after the second value is generated. My advice: find a "good" value to call qsrand (which should obviously be called only once, at the beginning of your program). A good value should span the whole range of the uint class. Take a look at this other question for some ideas:
Recommended way to initialize srand?
Also, take a look at this:
PCG: A Family of Better Random Number Generators
Neither current Qt nor C standard run-time have a quality randomizer and your test shows. Qt seems to use C run-time for that (this is easy to check but why). If C++ 11 is available in your project, use much better and way more reliable method:
#include <random>
#include <chrono>
auto seed = std::chrono::system_clock::now().time_since_epoch().count();
std::default_random_engine generator(seed);
std::uniform_int_distribution<uint> distribution;
uint randomUint = distribution(generator);
There is good video that covers the topic. As noted by commenter user2357112 we can apply different random engines and then different distributions but for my specific use the above worked really well.
Keeping in mind that making judgments about a statistical phenomena based on a small number of samples might be misleading, I decided to run a small experiment. I run the following code:
int main()
{
int i = 0;
int j = 0;
while (i < RAND_MAX)
{
srand(time(NULL));
int r1 = rand();
int r2 = rand();
if (r1 < r2)
++j;
++i;
if (i%10000 == 0) {
printf("%g\n", (float)j / (float)i);
}
}
}
which basically printed the percentage of times the first generated number was smaller than the second. Below you see the plot of that ratio:
and as you can see it actually approaches 0.5 after less than 50 actual new seeds.
As suggested in the comment, we could modify the code to use consecutive seeds every iteration and speed up the convergence:
int main()
{
int i = 0;
int j = 0;
int t = time(NULL);
while (i < RAND_MAX)
{
srand(t);
int r1 = rand();
int r2 = rand();
if (r1 < r2)
++j;
++i;
if (i%10000 == 0) {
printf("%g\n", (float)j / (float)i);
}
++t;
}
}
This gives us:
which stays pretty close to 0.5 as well.
While rand is certainly not the best pseudo random number generator, the claim that it often generates a smaller number during the first run does not seem to be warranted.
For example, assuming a string s is this:
for(int x = 0; x < s.length(); x++)
better than this?:
int length = s.length();
for(int x = 0; x < length; x++)
Thanks,
Joel
In general, you should avoid function calls in the condition part of a loop, if the result does not change during the iteration.
The canonical form is therefore:
for (std::size_t x = 0, length = s.length(); x != length; ++x);
Note 3 things here:
The initialization can initialize more than one variable
The condition is expressed with != rather than <
I use pre-increment rather than post-increment
(I also changed the type because is a negative length is non-sense and the string interface is defined in term of std::string::size_type, which is normally std::size_t on most implementations).
Though... I admit that it's not as much for performance than for readability:
The double initialization means that both x and length scope is as tight as necessary
By memoizing the result the reader is not left in the doubt of whether or not the length may vary during iteration
Using pre-increment is usually better when you do not need to create a temporary with the "old" value
In short: use the best tool for the job at hand :)
It depends on the inlining and optimization abilities of the compiler. Generally, the second variant will most likely be faster (better: it will be either faster or as fast as the first snippet, but almost never slower).
However, in most cases it doesn't matter, so people tend to prefer the first variant for its shortness.
It depends on your C++ implementation / library, the only way to be sure is to benchmark it. However, it's effectively certain that the second version will never be slower than the first, so if you don't modify the string within the loop it's a sensible optimisation to make.
How efficient do you want to be?
If you don't modify the string inside the loop, the compiler will easily see than the size doesn't change. Don't make it any more complicated than you have to!
Although I am not necessarily encouraging you to do so, it appears it is faster to constantly call .length() than to store it in an int, surprisingly (atleast on my computer, keeping in mind that I'm using an MSI gaming laptop with i5 4th gen, but it shouldn't really affect which way is faster).
Test code for constant call:
#include <iostream>
using namespace std;
int main()
{
string g = "01234567890";
for(unsigned int rep = 0; rep < 25; rep++)
{
g += g;
}//for loop used to double the length 25 times.
int a = 0;
//int b = g.length();
for(unsigned int rep = 0; rep < g.length(); rep++)
{
a++;
}
return a;
}
On average, this ran for 385ms according to Code::Blocks
And here's the code that stores the length in a variable:
#include <iostream>
using namespace std;
int main()
{
string g = "01234567890";
for(unsigned int rep = 0; rep < 25; rep++)
{
g += g;
}//for loop used to double the length 25 times.
int a = 0;
int b = g.length();
for(unsigned int rep = 0; rep < b; rep++)
{
a++;
}
return a;
}
And this averaged around 420ms.
I know this question already has an accepted answer, but there haven't been any practically tested answers, so I decided to throw my 2 cents in. I had the same question as you, but I didn't find any helpful answers here, so I ran my own experiment.
Is s.length() inline and returns a member variable? then no, otherwise cost of dereferencing and putting stuff in stack, you know all the overheads of function call you will incur for each iteration.
I believe (from some research reading) that counting down in for-loops is actually more efficient and faster in runtime. My full software code is C++
I currently have this:
for (i=0; i<domain; ++i) {
my 'i' is unsigned resgister int,
also 'domain' is unsigned int
in the for-loop i is used for going through an array, e.g.
array[i] = do stuff
converting this to count down messes up the expected/correct output of my routine.
I can imagine the answer being quite trivial, but I can't get my head round it.
UPDATE: 'do stuff' does not depend on previous or later iteration. The calculations within the for-loop are independant for that iteration of i. (I hope that makes sense).
UPDATE: To achieve a runtime speedup with my for-loop, do I count down and if so remove the unsigned part when delcaring my int, or what other method?
Please help.
There is only one correct method of looping backwards using an unsigned counter:
for( i = n; i-- > 0; )
{
// Use i as normal here
}
There's a trick here, for the last loop iteration you will have i = 1 at the top of the loop, i-- > 0 passes because 1 > 0, then i = 0 in the loop body. On the next iteration i-- > 0 fails because i == 0, so it doesn't matter that the postfix decrement rolled over the counter.
Very non obvious I know.
I'm guessing your backward for loop looks like this:
for (i = domain - 1; i >= 0; --i) {
In that case, because i is unsigned, it will always be greater than or equal to zero. When you decrement an unsigned variable that is equal to zero, it will wrap around to a very large number. The solution is either to make i signed, or change the condition in the for loop like this:
for (i = domain - 1; i >= 0 && i < domain; --i) {
Or count from domain to 1 rather than from domain - 1 to 0:
for (i = domain; i >= 1; --i) {
array[i - 1] = ...; // notice you have to subtract 1 from i inside the loop now
}
This is not an answer to your problem, because you don't seem to have a problem.
This kind of optimization is completely irrelevant and should be left to the compiler (if done at all).
Have you profiled your program to check that your for-loop is a bottleneck? If not, then you do not need to spend time worrying about this. Even more so, having "i" as a "register" int, as you write, makes no real sense from a performance standpoint.
Even without knowing your problem domain, I can guarantee you that both the reverse-looping technique and the "register" int counter will have negligible impact on your program's performance. Remember, "Premature optimization is the root of all evil".
That said, better spent optimization time would be on thinking about the overall program structure, data structures and algorithms used, resource utilization, etc.
Checking to see if a number is zero can be quicker or more efficient than a comparison. But this is the sort of micro-optimization you really shouldn't worry about - a few clock cycles will be greatly dwarfed by just about any other perf issue.
On x86:
dec eax
jnz Foo
Instead of:
inc eax
cmp eax, 15
jl Foo
It has nothing to do with counting up or down. What can be faster is counting toward zero. Michael's answer shows why — x86 gives you a comparison with zero as an implicit side effect of many instructions, so after you adjust your counter, you just branch based on the result instead of doing an explicit comparison. (Maybe other architectures do that, too; I don't know.)
Borland's Pascal compilers are notorious for performing that optimization. The compiler transforms this code:
for i := x to y do
foo(i);
into an internal representation more akin to this:
tmp := Succ(y - x);
i := x;
while tmp > 0 do begin
foo(i);
Inc(i);
Dec(tmp);
end;
(I say notorious not because the optimization affects the outcome of the loop, but because the debugger displays the counter variable incorrectly. When the programmer inspects i, the debugger may display the value of tmp instead, causing no end of confusion and panic for programmers who think their loops are running backward.)
The idea is that even with the extra Inc or Dec instruction, it's still a net win, in terms of running time, over doing an explicit comparison. Whether you can actually notice that difference is up for debate.
But note that the conversion is something the compiler would do automatically, based on whether it deemed the transformation worthwhile. The compiler is usually better at optimizing code than you are, so don't spend too much effort competing with it.
Anyway, you asked about C++, not Pascal. C++ "for" loops aren't quite as easy to apply that optimization to as Pascal "for" loops are because the bounds of Pascal's loops are always fully calculated before the loop runs, whereas C++ loops sometimes depend on the stopping condition and the loop contents. C++ compilers need to do some amount of static analysis to determine whether any given loop could fit the requirements for the kind of transformation Pascal loops qualify for unconditionally. If the C++ compiler does the analysis, then it could do a similar transformation.
There's nothing stopping you from writing your loops that way on your own:
for (unsigned i = 0, tmp = domain; tmp > 0; ++i, --tmp)
array[i] = do stuff
Doing that might make your code run faster. Like I said before, though, you probably won't notice. The bigger cost you pay by manually arranging your loops like that is that your code no longer follows established idioms. Your loop is a perfectly ordinary "for" loop, but it no longer looks like one — it has two variables, they're counting in opposite directions, and one of them isn't even used in the loop body — so anyone reading your code (including you, a week, a month, or a year from now when you've forgotten the "optimization" you were hoping to achieve) will need to spend extra effort proving to himself or herself that the loop is indeed an ordinary loop in disguise.
(Did you notice that my code above used unsigned variables with no danger of wrapping around at zero? Using two separate variables allows that.)
Three things to take away from all this:
Let the optimizer do its job; on the whole it's better at it than you are.
Make ordinary code look ordinary so that the special code doesn't have to compete to get attention from people reviewing, debugging, or maintaining it.
Don't do anything fancy in the name of performance until testing and profiling show it to be necessary.
If you have a decent compiler, it will optimize "counting up" just as effectively as "counting down". Just try a few benchmarks and you'll see.
So you "read" that couting down is more efficient? I find this very difficult to believe unless you show me some profiler results and the code. I can buy it under some circumstances, but in the general case, no. Seems to me like this is a classic case of premature optimization.
Your comment about "register int i" is also very telling. Nowadays, the compiler always knows better than you how to allocate registers. Don't bother using using the register keyword unless you have profiled your code.
When you're looping through data structures of any sort, cache misses have a far bigger impact than the direction you're going. Concern yourself with the bigger picture of memory layout and algorithm structure instead of trivial micro-optimisations.
You may try the following, which compiler will optimize very efficiently:
#define for_range(_type, _param, _A1, _B1) \
for (_type _param = _A1, _finish = _B1,\
_step = static_cast<_type>(2*(((int)_finish)>(int)_param)-1),\
_stop = static_cast<_type>(((int)_finish)+(int)_step); _param != _stop; \
_param = static_cast<_type>(((int)_param)+(int)_step))
Now you can use it:
for_range (unsigned, i, 10,0)
{
cout << "backwards i: " << i << endl;
}
for_range (char, c, 'z','a')
{
cout << c << endl;
}
enum Count { zero, one, two, three };
for_range (Count, c, three, zero)
{
cout << "backwards: " << c << endl;
}
You may iterate in any direction:
for_range (Count, c, zero, three)
{
cout << "forward: " << c << endl;
}
The loop
for_range (unsigned,i,b,a)
{
// body of the loop
}
will produce the following code:
mov esi,b
L1:
; body of the loop
dec esi
cmp esi,a-1
jne L1
Hard to say with information given but... reverse your array, and count down?
Jeremy Ruten rightly pointed out that using an unsigned loop counter is dangerous. It's also unnecessary, as far as I can tell.
Others have also pointed out the dangers of premature optimization. They're absolutely right.
With that said, here is a style I used when programming embedded systems many years ago, when every byte and every cycle did count for something. These forms were useful for me on the particular CPUs and compilers that I was using, but your mileage may vary.
// Start out pointing to the last elem in array
pointer_to_array_elem_type p = array + (domain - 1);
for (int i = domain - 1; --i >= 0 ; ) {
*p-- = (... whatever ...)
}
This form takes advantage of the condition flag that is set on some processors after arithmetical operations -- on some architectures, the decrement and testing for the branch condition can be combined into a single instruction. Note that using predecrement (--i) is the key here -- using postdecrement (i--) would not have worked as well.
Alternatively,
// Start out pointing *beyond* the last elem in array
pointer_to_array_elem_type p = array + domain;
for (pointer_to_array_type p = array + domain; p - domain > 0 ; ) {
*(--p) = (... whatever ...)
}
This second form takes advantage of pointer (address) arithmetic. I rarely see the form (pointer - int) these days (for good reason), but the language guarantees that when you subtract an int from a pointer, the pointer is decremented by (int * sizeof (*pointer)).
I'll emphasize again that whether these forms are a win for you depends on the CPU and compiler that you're using. They served me well on Motorola 6809 and 68000 architectures.
In some later arm cores, decrement and compare takes only a single instruction. This makes decrementing loops more efficient than incrementing ones.
I don't know why there isn't an increment-compare instruction also.
I'm surprised that this post was voted -1 when it's a true issue.
Everyone here is focusing on performance. There is actually a logical reason to iterate towards zero that can result in cleaner code.
Iterating over the last element first is convenient when you delete invalid elements by swapping with the end of the array. For bad elements not adjacent to the end we can swap into the end position, decrease the end bound of the array, and keep iterating. If you were to iterate toward the end then swapping with the end could result in swapping bad for bad. By iterating end to 0 we know that the element at the end of the array has already been proven valid for this iteration.
For further explanation...
If:
You delete bad elements by swapping with one end of the array and changing the array bounds to exclude the bad elements.
Then obviously:
You would swap with a good element i.e. one that has already been tested in this iteration.
So this implies:
If we iterate away from the variable bound then elements between the variable bound and the current iteration pointer have been proven good. Whether the iteration pointer gets ++ or -- doesn't matter. What matters is that we're iterating away from the variable bound so we know that the elements adjacent to it are good.
So finally:
Iterating towards 0 allows us to use only one variable to represent the array bounds. Whether this matters is a personal decision between you and your compiler.
What matters much more than whether you're increasing or decreasing your counter is whether or not you're going up memory or down memory. Most caches are optimized for going up memory, not down memory. Since memory access time is the bottleneck that most programs today face, this means that changing your program so that you go up memory can result in a performance boost even if this requires comparing your counter to a non-zero value. In some of my programs, I saw a significant improvement in performance by changing my code to go up memory instead of down it.
Skeptical? Here's the output that I got:
sum up = 705046256
sum down = 705046256
Ave. Up Memory = 4839 mus
Ave. Down Memory = 5552 mus
sum up = inf
sum down = inf
Ave. Up Memory = 18638 mus
Ave. Down Memory = 19053 mus
from running this program:
#include <chrono>
#include <iostream>
#include <random>
#include <vector>
template<class Iterator, typename T>
void FillWithRandomNumbers(Iterator start, Iterator one_past_end, T a, T b) {
std::random_device rnd_device;
std::mt19937 generator(rnd_device());
std::uniform_int_distribution<T> dist(a, b);
for (auto it = start; it != one_past_end; it++)
*it = dist(generator);
return ;
}
template<class Iterator>
void FillWithRandomNumbers(Iterator start, Iterator one_past_end, double a, double b) {
std::random_device rnd_device;
std::mt19937_64 generator(rnd_device());
std::uniform_real_distribution<double> dist(a, b);
for (auto it = start; it != one_past_end; it++)
*it = dist(generator);
return ;
}
template<class RAI, class T>
inline void sum_abs_up(RAI first, RAI one_past_last, T &total) {
T sum = 0;
auto it = first;
do {
sum += *it;
it++;
} while (it != one_past_last);
total += sum;
}
template<class RAI, class T>
inline void sum_abs_down(RAI first, RAI one_past_last, T &total) {
T sum = 0;
auto it = one_past_last;
do {
it--;
sum += *it;
} while (it != first);
total += sum;
}
template<class T> std::chrono::nanoseconds TimeDown(
std::vector<T> &vec, const std::vector<T> &vec_original,
std::size_t num_repititions, T &running_sum) {
std::chrono::nanoseconds total{0};
for (std::size_t i = 0; i < num_repititions; i++) {
auto start_time = std::chrono::high_resolution_clock::now();
sum_abs_down(vec.begin(), vec.end(), running_sum);
total += std::chrono::high_resolution_clock::now() - start_time;
vec = vec_original;
}
return total;
}
template<class T> std::chrono::nanoseconds TimeUp(
std::vector<T> &vec, const std::vector<T> &vec_original,
std::size_t num_repititions, T &running_sum) {
std::chrono::nanoseconds total{0};
for (std::size_t i = 0; i < num_repititions; i++) {
auto start_time = std::chrono::high_resolution_clock::now();
sum_abs_up(vec.begin(), vec.end(), running_sum);
total += std::chrono::high_resolution_clock::now() - start_time;
vec = vec_original;
}
return total;
}
int main() {
std::size_t num_repititions = 1 << 10;
{
typedef int ValueType;
auto lower = std::numeric_limits<ValueType>::min();
auto upper = std::numeric_limits<ValueType>::max();
std::vector<ValueType> vec(1 << 24);
FillWithRandomNumbers(vec.begin(), vec.end(), lower, upper);
const auto vec_original = vec;
ValueType sum_up = 0, sum_down = 0;
auto time_up = TimeUp(vec, vec_original, num_repititions, sum_up).count();
auto time_down = TimeDown(vec, vec_original, num_repititions, sum_down).count();
std::cout << "sum up = " << sum_up << '\n';
std::cout << "sum down = " << sum_down << '\n';
std::cout << "Ave. Up Memory = " << time_up/(num_repititions * 1000) << " mus\n";
std::cout << "Ave. Down Memory = "<< time_down/(num_repititions * 1000) << " mus"
<< std::endl;
}
{
typedef double ValueType;
auto lower = std::numeric_limits<ValueType>::min();
auto upper = std::numeric_limits<ValueType>::max();
std::vector<ValueType> vec(1 << 24);
FillWithRandomNumbers(vec.begin(), vec.end(), lower, upper);
const auto vec_original = vec;
ValueType sum_up = 0, sum_down = 0;
auto time_up = TimeUp(vec, vec_original, num_repititions, sum_up).count();
auto time_down = TimeDown(vec, vec_original, num_repititions, sum_down).count();
std::cout << "sum up = " << sum_up << '\n';
std::cout << "sum down = " << sum_down << '\n';
std::cout << "Ave. Up Memory = " << time_up/(num_repititions * 1000) << " mus\n";
std::cout << "Ave. Down Memory = "<< time_down/(num_repititions * 1000) << " mus"
<< std::endl;
}
return 0;
}
Both sum_abs_up and sum_abs_down do the same thing and are timed they same way with the only difference being that sum_abs_up goes up memory while sum_abs_down goes down memory. I even pass vec by reference so that both functions access the same memory locations. Nevertheless, sum_abs_up is consistently faster than sum_abs_down. Give it a run yourself (I compiled it with g++ -O3).
FYI vec_original is there for experimentation, to make it easy for me to change sum_abs_up and sum_abs_down in a way that makes them alter vec while not allowing these changes to affect future timings.
It's important to note how tight the loop that I'm timing is. If a loop's body is large then it likely won't matter whether its iterator goes up or down memory since the time it takes to execute the loop's body will likely completely dominate. Also, it's important to mention that with some rare loops, going down memory is sometimes faster than going up it. But even with such loops it's rarely ever the case that going up was always slower than going down (unlike loops that go up memory, which are very often always faster than the equivalent down-memory loops; a small handful of times they were even 40+% faster).
The point is, as a rule of thumb, if you have the option, if the loop's body is small, and if there's little difference between having your loop go up memory instead of down it, then you should go up memory.