Advantages of Multi-core programming

Russell Hitchcock

J2EE

Application technology is something that perhaps some of you may know is J2EE, J2EE is an environment used to build enterprise-level applications. Applications built on J2EE technology can take advantage of the use of multi-core CPUs.

Using J2EE for enterprise applications will allow developers to code application code without the need for detailed knowledge of the thread; This is indeed the real power behind J2EE. J2EE applications are converted into multithread by changing the settings in the application server; Multithread implementation is managed by one item (container). So how does it work? Basically, business logic can be coded and then developed into the server in a logical section. Then the settings can also assign the number of how many instances of enterprise logic can be run. The item can also identify connections to resources such as databases that can be used once. The properties managed by these items are completely separate from multithread for application code. This is a good sign because it allows multithreads to be adjusted based on the hardware of the running application without changing the application code. This is appropriate for enterprise hardware; computers can be added to the cluster of servers (server clusters), or perhaps microprocessors can be added or extracted from existing computers on the cluster, each with a change This affects the multi-thread capabilities of applications running on the hardware.

OpenMP

Remembering that multithread logic is completely separate from business logic will be a major goal for software developers to write parallel applications. There are many reasons for this problem; Easy to develop, easy to debug and easy to change applications. When a software developer is developing an application in C / C ++ or FORTRAN, a common implementation used for this process is OpenMP. OpenMP is an API used to write multi-threaded application code effectively and practically.

In essence, OpenMP is used by grouping a set of instructions in code as comments or annotations. The code is written and then the annotations are added to the appropriate positions later. When the code has been compiled with the appropriate OpenMP compiler, the annotations will be read and the code compiled in such a way as to make use of the thread directly by the annotations.

This parallel programming method has many advantages. Since a program is coded to be able to run sequentially and annotations are merely code comments then if the code is compiled in a regular compiler, the compiler will ignore the comments. OpenMP. This code will then be compiled with the OpenMP compiler and run multithreaded in parallel. This means that developers will not have to change the code if the program is run in two different hardware architectures: one for multi-threading and one for multi-threading.

Another advantage of OpenMP is that the code can be annotated with more code. That allows for easier inspection in ensuring proper code functions. This issue is also very significant because developers can handle multi-threaded parts of code to then use the result in another implementation; however, this is very difficult to test by a compiler so it needs to be tested through testing.

Figure 1: Example of an application thread using multithread

The dangers of Multithread

One of the most common errors created by developers when designing multi-threaded applications is their handling of loops. For example, if someone wants to repeat an entire array of integers and simply populate each of those values, this can be multi-threaded to perform each iteration in the thread. by itself at the same time. OpenMP will do this (in C / C ++) by annotating #pragma omp parallel for . However, if someone wants to repeat a similar array, but changing each value by adding the value of the previous component, in this case, there will be an error of handling this multi-threaded loop; If all loop iterations appear simultaneously, you cannot guarantee that the previous component has been changed to contain new values. Running such a loop during multithreading will create another array of integers.

Another common mistake is with variables used by simultaneous multithreading. OpenMP is basically used for programs that run in shared memory mode and therefore requires developers to ensure that these streams do not alter the variables used by other threads. . However, in this case, OpenMP has supported annotations to ensure that does not happen within a certain multithreaded code block. However, experts still have to learn about this to use the right notes where needed.

Efficiency

When done carefully, handling multi-threaded applications can significantly increase performance. Obviously to do this, you must run on hardware that supports multithreading. However, when implemented with appropriate hardware, there are still certain limitations to this processing, such as having blocks of code that cannot handle multithreading. Many pieces of code that cannot be implemented in multi-threading will increase the execution time of those pieces of code and thereby affect the performance of the entire program.

However, there are many advantages to performance performance to run a multithreaded application on multi-core CPUs that have more memory for the application. For example, Tilera's Tile64 processor was introduced in the article about multi-fault CPUs containing a logical cache L3. In many cases, this way of processing will significantly increase cache utilization, thus reducing the amount of memory time required to read and increasing performance.