MULTICORE ARCHITECTURE AND SOA

With the success of multi-core architectures, enterprise applications derive benefits by executing the code in parallel. By definition, a multi-core microprocessor is one that combines two or more independent processors into a single package, often a single integrated circuit (IC). This architecture allows software applications to perform thread-level parallelism (chip-level multiprocessing) without including multiple microprocessors in separate physical packages. Now the question arises "why multi-core?" The answer lies in scalability, division of labor, specialization of labor, increased demands for performance and reduced power consumption.

Keeping aside hardware implications, we will look into the software implications of multi-core computing. The emergence of multi-core processor marks a revised thinking from a software perspective too. Applications won't be able to leverage processor enhancements unless software is highly concurrent. Code components which can be run concurrently benefit the most from multi-core architectures and even multiple applications can benefit a lot from multi-core architectures. Then you can run each virtual machine independently of others.

The basic steps in designing parallel applications are:

Partitioning: Decomposing the design into smaller chunks.

Communication: One chunk may require data from another chunk for its smooth execution. This information flow is specified in the communication phase.

Agglomeration: Obtain an algorithm to execute efficiently on a parallel computer. In this phase we combine or agglomerate tasks identified by the partitioning phase to provide a smaller number of useful tasks.

Mapping: Here, we specify where each task is to be executed.

The requirements of a business application do not lend themselves to either grid or parallel environment. 

The three main reasons are:

Order of processing: Business logic must be performed in a particular sequence to ensure the integrity of a business process. Each transaction waits for the previous transaction to be completed before it gets processed. This order of processing is difficult to maintain in a parallel grid environment.

Centrally shared resources: Applications have a centralized resource throughout the application. This creates a bottleneck.

Unpredictable behavior and resource needs: The size and processing requirements of business processes vary through out the day or within a given hour. This makes the division of an application into equal-sized blocks difficult, as well as the allocation of resources.

Multi-core computing in SOA

Service-oriented architectures are gaining popularity due to their inherent flexibility. SOA is an enterprise driven, complex, managed, standards-based and highly customizable architecture to enable maximum flexibility and control. SOA is compositional, meaning new applications are built by plugging services together. However, SOA solutions need higher computational resources due to the dependence upon XML-like or JSON-like languages. To truly benefit from SOA, a parallel processing approach to software design and implementation for SOA is required.

In context of SOA, multi-core computing can be exploited in the following areas

• Scalability via distributed instances of the same logical service
• Parallelizing service execution by detecting scope for parallelism
• Multi-service processes/service orchestration scalability by distributing different services over different threads
• Separation of different processes in SOA computing – marshalling, schema processing, validation, demarshalling into separate threads for maximizing throughputs for services

Parallel processing.

XML, SOAP, JSON and WSDL are major industry standards used to build SOA applications. However, processing of XML or JSON is computationally demanding and a number of optimization techniques have been developed to address the performance problem, but none of them are quite satisfactory. XML or JSON has turned out to be the major bottleneck for SOA applications. With the emergence of multi-core architectures, concurrent processing of XML or JSON could be one of the solutions to enhance the performance.

SOA can benefit from multi-core architectures, however a set of associated tools and programmer-usable artifacts should be created and made popular so that you do not lay the burden on programmer to create parallel XML or JSON processing code.