Assertions and Multi-threading in Eigen

Assertion

In Eigen, a statement that states or asserts that an expression must be true is called an assertion.

It is used to examine situations that are impossible to occur without a bug. Due to the fact that it ends the programme when the assertion is false, it is used as a debugging tool.

For instance, the assumption would be true if we were to get the average of non-empty vector numbers

number.size() > 0

It must be true unless there is a programming error.

Assertion in Eigen Library

Many Assertions in Eigen are contained in the Eigen library to avoid programming errors both during compilation and during execution. These assertions can, however, be disabled and can take up time.

EIGEN_NO_DEBUG - Unless the NDEBUG macro is declared, which is a common C++ macro that disables all assertions, it is not defined by default.

EIGEN_NO_STATIC_ASSERT - It is preferred to use compile-time static rather than runtime assertions. Eigen assertions are faster to compile if they are initially declared. 

EIGEN_ASSERT - Assertions inside Eigen are made using a one-argument macro. It is essentially specified by default to assert, which terminates the programme if the assertion is broken. If you wish to change what this macro does, like throw an exception, you must redefine it.

EIGEN_MPL2_ONLY - Deactivate features that are not MPL2 compliant, or in other words, disable features that are still covered by the LGPL.

Redefining Assertions

In Macros.h, the terms eigen_assert and eigen_plain_assert are also defined. You can modify eigen_assertt behaviour by indirectly defining it. If you wish to change what this macro does, such as throw an exception, you may redefine it and use eigen_plain_assert to revert to the default behaviour.

Eigen Code for Runtime Error

#undef eigen_assert
#include <stdexcept>
#define eigen_assert(var) \

  if (!(var)) { throw (std::runtime_error("Your Error")); }

Output as Error

Disabling Assertions

Run-time Assertions in Eigen can be disabled. Before adding Eigen headers, define EIGEN_NO_DEBUG to disable eigen_assert. Unless NDEBUG is specified, EIGEN_NO_DEBUG is undefined by default.

Static Assertions in Eigen

Before C++11, static Assertions in Eigen were not standardised. However, there are several conditions in the Eigen library that can and ought to be found at compile time. In StaticAssert.h, static Assertions in Eigen are defined. We utilise native static assert if it exists.

Simple static assertions without messages include the following:

#define STATIC_ASSERT(t) \
  switch(1) { case 1: case t:; }

The above example, however, clearly cannot explain why the code was wrong. To handle the available messages, we construct a struct under namespace Eigen::internal.

template<bool condition>
struct static_assertion {};
 
	template<>
	struct static_assertion<true>
{
     enum {
         YOU_TRIED_CALLING_A_VECTOR_METHOD_ON_A_MATRIX,
         YOU_MIXED_VECTORS_OF_DIFFERENT_SIZES,
	};
};

There are two Static Assertions in Eigen:

• Derived Static Assertions.
   
• Disabling Static Assertions.

Derived Static Assertions

To improve readability, further macros are derived from EIGEN_STATIC_ASSERT. Their names speak for themselves.

Disabling Static Assertions

Static assertions become Eigen assert if EIGEN_NO_STATIC_ASSERT is specified, functioning as follows:

#define EIGEN_STATIC_ASSERT(CONDITION,MSG) eigen_assert((CONDITION) && #MSG);

This takes longer to execute but takes less time to compile. By default, EIGEN_NO_STATIC_ASSERT is undefined.

Multi-threading

A style of programme execution known as "multithreading" enables the creation of many threads that can run concurrently and independently while sharing process resources. If allocated to their own CPU core, threads may be able to operate in complete parallel, depending on the hardware.

Thread: A thread in computer programming is a brief sequence of instructions that are intended to be scheduled and carried out by the CPU apart from the parent process.

Performance is the key justification for adding threads to a programme.

Multiple threads will be used by a web server to handle data requests concurrently.

In order to apply filtering to a picture, an image analysis algorithm will split the image into quadrants and start many threads at once.

Make Eigen in Parallel Mode

Some of Eigen's algorithms can make use of your hardware's many cores. To do this, just turn on OpenMP in your compiler, for example,

By using the EIGEN_DONT_PARALLELIZE preprocessor token, you may turn off multi-threading in Eigen's at compile time.

The following algorithms are now capable of using multi-threading in Eigen:

• LeastSquaresConjugateGradient.
   
• PartialPivLU.
   
• BiCGSTAB with a row-major sparse matrix format.
   
• Row-major-sparse * dense vector/matrix products.
   
• General dense matrix-matrix products.
   
• ConjugateGradient with Lower|Upper as the UpLo template parameter.

Related Article Multithreading Operating System

Application of Eigen in a Multi-Threaded Environment

You must initialise Eigen by executing the following function before generating the threads if your programme is multithreaded and several threads call Eigen.

#include <Eigen/Core>
 
int main(int argument_count, char** argument_vector)
{
          Eigen::initParallel();

            // Write your Code.
}

Try and compile by yourself with the help of online C++ Compiler for better understanding.

You can also check out Multithreading in C#, Multithreading in Python

Frequently Asked Questions

What is the purpose of Eigen?

Eigen is a powerful open-source C++ framework for numerical solvers, geometric transformations, matrix and vector operations, and related algorithms.

What is OpenGL?

OpenGL is a cross-platform and cross-interface library that renders 2D and 3D vector graphics. The OpenGL API is typically used to interact with the graphics processing unit to achieve hardware-accelerated rendering.

Is C++ language good for multithreading?

This not only makes use of many CPU cores, but it also gives the developer the ability to control the number of tasks that are executed by adjusting the thread pool size. The computer resources may then be used by the software properly without getting overloaded.

Does Eigen make use of OpenMP?

Eigen utilises the number of threads supplied by OpenMP unless setNbThreads is called.

What are the different types of libraries in C++?

Static libraries and dynamic libraries are the two types of libraries.

Conclusion

In this article, we briefly discussed Assertions in Eigen and Multi-threading in Eigen. We have also covered Application  Multi-Threading in Eigen.

For more information on Eigen and related topics, refer to the following articles:

• Eigen’s Geometry
   
• Eigen's class hierarchy
   
• What are the different Matrix Operations?

Also, check out some of the Guided Paths available on Coding Ninjas Studio on topics such as the Basics of C++, Operating Systems, and Computer Networks along with some Interview Experiences and Interview Bundles for placement preparation.