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Modern C++ Features – User-Defined Literals--Arne Mertz

By Adrien Hamelin | Oct 27, 2016 11:56 AM | Tags: intermediate c++11

Learn more about litterals.

Modern C++ Features – User-Defined Literals

by Arne Mertz

From the article:

User-defined literals are a convenient feature added in C++11.

C++ always had a number of built-in ways to write literals: Pieces of source code that have a specific type and value. They are part of the basic building blocks of the language:

32 043 0x34   //integer literals, type int
4.27 5E1      //floating point literals, type double
'f', '\n'     //character literals, type char
"foo"         //string literal, type const char[4]
true, false   //boolean literals, type bool

These are only the most common ones, there are many more, including some newcomers in the newer standards. Other literals are nullptr and different kinds of prefixes for character and string literals. There also are suffixes we can use to change the type of a built-in numeric literal:

32u     //unsigned int
043l    //long
0x34ull //unsigned long long
4.27f   //float
5E1l    //long double

Quick Q: Is std::vector so much slower than plain arrays?

By Adrien Hamelin | Oct 27, 2016 11:23 AM | Tags: performance intermediate

Quick A: A vector isn’t slower than an array when they do the same things. But it lets you do much more…

Some time ago on SO:

Is std::vector so much slower than plain arrays?

Using the following:

g++ -O3 Time.cpp -I <MyBoost>
./a.out
UseArray completed in 2.196 seconds
UseVector completed in 4.412 seconds
UseVectorPushBack completed in 8.017 seconds
The whole thing completed in 14.626 seconds


So array is twice as quick as vector.

But after looking at the code in more detail this is expected; as you run across the vector twice and the array only once. Note: when you resize() the vector you are not only allocating the memory but also running through the vector and calling the constructor on each member.

Re-Arranging the code slightly so that the vector only initializes each object once:

std::vector<Pixel>  pixels(dimensions * dimensions, Pixel(255,0,0));

Now doing the same timing again:

g++ -O3 Time.cpp -I <MyBoost>
./a.out
UseVector completed in 2.216 seconds


The vector now performance only slightly worse than the array. IMO this difference is insignificant and could be caused by a whole bunch of things not associated with the test.

I would also take into account that you are not correctly initializing/Destroying the Pixel object in the UseArrray() method as neither constructor/destructor is not called (this may not be an issue for this simple class but anything slightly more complex (ie with pointers or members with pointers) will cause problems.

Tutorial: Emulating strong/opaque typedefs in C++--Jonathan Müller

By Adrien Hamelin | Oct 20, 2016 12:36 PM | Tags: intermediate community

Who would like this feature?

Tutorial: Emulating strong/opaque typedefs in C++

by Jonathan Müller

From the article:

Last week, I’ve released my type_safe library. I described it’s features in the corresponding blog post but because the blog post got rather long, I couldn’t cover one feature: strong typedefs.

Strong or opaque typedefs are a very powerful feature if you want to prevent errors with the type system - and as I’ve been advocating for, you want that. Unlike “normal” typedefs, they are a true type definition: they create a new type and allow stuff like overloading on them and/or prevent implicit conversions.

DLib 19.2 released

By Meeting C++ | Oct 11, 2016 05:57 AM | Tags: intermediate efficiency deep learning cuda basics advanced

Today a new version of DLib is available:

DLib 19.2 released

Release notes

by Davis King

From the article:

... So the obvious thing to do was to add an implementation of MMOD with the HOG feature extraction replaced with a convolutional neural network.  The new version of dlib, v19.2, contains just such a thing.  On this page you can see a short tutorial showing how to train a convolutional neural network using the MMOD loss function.  It uses dlib's new deep learning API to train the detector end-to-end on the very same 4 image dataset used in the HOG version of the example program.  Happily, and very much to the surprise of myself and my colleagues, it learns a working face detector from this tiny dataset.

Optimizing return values--Marco Foco

By Marco Arena | Oct 11, 2016 12:46 AM | Tags: intermediate

Marco Foco shows different solutions and tradeoffs to a dangling reference problem:

Optimizing return values

    by Marco Foco

From the article:

As you can see, class C contains a function get() which returns a reference to its internal state. In normal code, we must take care not to use this reference after our class has been destroyed...

C++ in Competitive Programming: compromises--Marco Arena

By Marco Arena | Sep 30, 2016 10:27 AM | Tags: intermediate

In this installment I'll explain what I consider the essence of Competitive Programming:

C++ in Competitive Programming: compromises

by Marco Arena

From the article:

Crafting software is about balancing competing trade-offs. It’s impossible to optimize every factor of a system, as speed, usability, accuracy, etc at the same time. Moreover, solutions of today impact decisions and solutions of tomorrow. On the other hand, in Competitive Programming, the best solution is one that just makes each test-case pass...