Parallel Processing

Parallel Processing is a computing method to be performed on systems containing two or more processors operating simultaneously. The processors may work on different aspects of the same program at the same time. The benefit of using the parallel processing is to save time in solving large and complex problems.

To take advantage of parallel processing, it is necessary to parallelise the program by assigning parts of the job to the different processors. The main problem is that parallelisation is problem-dependent and cannot yet be automated, furthermore, speedup is not guaranteed. A program being executed across n processors might execute n times faster than it would using a single processor. Only some applications can take advantages of parallel processing with the following conditions met:

Your application has enough parallelism to make good use of multiple processors.
The target application program should be parallelized (or you need to do some new coding to take advantage of parallel processing.)

Traditionally, multiple processors were provided within a specially designed "parallel computer"; along these lines, Linux now supports SMP Pentium systems in which multiple processors share a single memory and bus interface within a single computer. It is also possible for a group of machines each running Linux to be interconnected by a network to form a parallel-processing cluster. The third alternative uses a Linux system as a "host" for a specialized attached parallel processor. A "new" fourth alternative is SIMD parallelism within a register, which is facilitated by the MMX (MultiMedia eXtensions). The typical Hardware environment for Parallel processing:

Single partition on a single processor (uniprocessor)
Single partition with multiple processors (SMP)
Multiple partition configurations
- Partitions with one processor (MPP)
- Partitions with multiple processors (cluster of SMPs)
- Logical database partitions (also known as Multiple Logical Nodes, or MLN, in DB2 Parallel Edition for AIX Version 1)

Types of Parallelism Possible in Each Hardware Environment.

Hardware Environment	I/O Parallelism	Intra-Query Parallelism
Hardware Environment	I/O Parallelism	Intra- Partition Parallelism	Inter- Partition Parallelism
Single Partition, Single Processor	Yes	No	No
Single Partition, Multiple Processors (SMP)	Yes	Yes	No
Multiple Partitions, One Processor (MPP)	Yes	No	Yes
Multiple Partitions, Multiple Processors (cluster of SMPs)	Yes	Yes	Yes
Logical Database Partitions	Yes	Yes	Yes