What are the Advantages and disadvantages of Symmetric multiprocessing?  

The advantages of SMP include a large global memory and better performance per Watt, important for SWaP (size, weight and power) sensitive applications thanks to the use of fewer memory controllers. Instead of splitting memory between multiple CPUs, SMP’s large global memory is accessible to all of the processor cores. Data intensive applications, such as image processing and data acquisition systems, often prefer large global memories that can be accessed at data rates up to 100s of Mbytes/sec. These large memory applications benefit from the single large memory common in most multi-core designs.

SMP also provides simpler node-to-node communication, and SMP applications can be programmed to be independent of node count. SMP especially lends itself to the use of new multi-core processor designs. The disadvantages of SMP include the fact that the memory latency and bandwidth of a given node can be affected by other nodes, and cache “thrashing” may occur in some applications.

SMP architectures differ from AMP in that a single block of memory is shared by the multiple processors or by multiple cores on a single multi-core processor. A single OS image runs across all the cores enabling truly parallel processing. A big advantage of SMP operating systems is that they perform load-balancing for the tasks between all available cores.

Asymmetric multiprocessing designs use SMP hardware architecture where a common global memory is shared between the various processors. To the system software, this makes the SMP architecture look like a DP architecture. In AMP designs, application tasks are sent to the system’s separate processors. These processors may all be located on different boards or collocated on the same board, but each is essentially a separate computing system with its own OS and memory partition within the common global memory. One advantage of an AMP design is that asymmetric memory partitions can be assigned from one large global memory, making more efficient use of memory resources and potentially reducing system cost.

Answered by Keshto Patel at 9:25 PM on December 27, 2008

SMP has many uses in science, industry, and business which often use custom-programmed software for multithreaded processing. However, most consumer products such as word processors and computer games are written in such a manner that they cannot gain large benefits from SMP systems. For games this is usually because writing a program to increase performance on SMP systems can produce a performance loss on uniprocessor systems. Recently, however, multi-core chips have become the norm in new computers, and the balance between installed uni- and multi-core computers may change in the coming years.

The nature of the different programming methods would generally require two separate code-trees to support both uniprocessor and SMP systems with maximum performance. Programs running on SMP systems may experience a performance increase even when they have been written for uniprocessor systems. This is because hardware interrupts that usually suspend program execution while the kernel handles them can run on an idle processor instead. The effect in most applications (e.g. games) is not so much a performance increase as the appearance that the program is running much more smoothly. In some applications, particularly compilers and some distributed computing projects, one will see an improvement by a factor of (nearly) the number of additional processors.

In situations where more than one program runs at the same time, an SMP system will have considerably better performance than a uni-processor because different programs can run on different CPUs simultaneously.

Systems programmers must build support for SMP into the operating system: otherwise, the additional processors remain idle and the system functions as a uniprocessor system.

In cases where an SMP environment processes many jobs, administrators often experience a loss of hardware efficiency. Software programs have been developed to schedule jobs so that the processor utilization reaches its maximum potential. Good software packages can achieve this maximum potential by scheduling each CPU separately, as well as being able to integrate multiple SMP machines and clusters.

Access to RAM is serialized; this and cache coherency issues causes performance to lag slightly behind the number of additional processors in the system.

Answered by Alok Gupta at 5:29 PM on December 27, 2008