Parallel Processing in Visual Studio 2010


Introduction

The .Net Framework 4.0 introduces a new programming architecture for doing multiple processes asynchronously that greatly simplifies the application load and gets better performance.  The new programming architecture helps developers to write a scalable and more efficient code in order to achieve better performance for the application development. Parallel LINQ (PLINQ) is a parallel implementation of LINQ to Objects; it enables similar functionality for developers through declarative coding.

You can have in your mind how a multi-core processor is related with a multi-threaded application. The concept would be like application development processes based on the environment the application is running. Even though the application runs in a multi-core processor, fewer resources will be used by the application to run the process. Say for example a multi-core processor has the ability to handle n number of processes; the code will work step by step in any one of the processors leaving remaining processors unused. Now the developers can make use of this particularly when working on complex algorithms or when multiple processes are needed asynchronously.

Multi-threaded programming is one of the ways which gives developers an option to work with multiple threads concurrently. Even though this concept has been available since .Net 1.1, it's been avoided due to the complexity and developers need to write clean code in order to get betterr performance using multithreading rather than spending most of the time with business and functionality.

Using Normal Process

Consider a real time example of a web page having a Tab Control; normaly each tab will be loaded sequentially as needed by the business and not in parallel. Definitely it takes more time to load the contents to different tabs from each data source.

Normal Process

Using Parallel Process

Normal processing uses only a single processor even though the other processors are idle. But when using parallel processing (using the Parallel Library) the other processors are also used to execute the core functionality which gives applications better performance.

Finally a multi-threaded application works on both multi core and also on a single core processor as it's based on the hardware configuration. Underneath the code will be working on the single thread if it goes to a single processor and multiple threads if it goes to a multi processor.

Parallel Process

Concurrent Processing vs Parallel Processing

Concurrent Processing

In Concurrent programming several streams of functionality may be executed concurrently. Each one of the functionality operated in a sequential order process except that it communicate and interfere with one another. For Example: Two thread tasks Task1 and Task2 are concurrent if the order in which the tasks are executed is not predetermined. The possible execution is as follows.
  • Task1 may be executed and completed before Task2
  • Task2 may be executed and completed before Task1
  • Task1 and Task2 may need to be executed alternatively
  • Task1 and Task2 may be executed and completed simultaneously at the same time period (Parallelism)

Parallel Processing

In parallel Programming, it's the process of executing the functionality by dividing into sub functionalities that are to be operated as concurrent programs. For Example: If two concurrent thread tasks are scheduled to run by OS and if these threads run on a single-core processor we will get concurrency if the same is running on a multi-core processor we will get parallelism.

So we can't say which is more efficient programming than the other, but neither is the superset of the other programming process. Based on the business requirement the processor can be selected and used in the application development process.

Parallel Programming Architecture


Architecture


Above architecture diagram explains in detail on how the parallel processing will takes and gets scheduled based on the needs. The main components of this architecture are as follow.
  • Task Parallel Library
  • Parallel LINQ (PLINQ)
  • Task Schedulers
  •  Lambda Expressions in PLINQ

Conclusion

We will get into detail of each component and see how the process takes place in each component in the next upcoming article.

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