Multiprocessing War A Draw? -- Users seek to balance performance and speed in the SMP-vs.-MPP debate

Speed isn't everything. If a fast system's complexity prevents users from getting the benefits they want, performance can actually be a hindrance.

That issue is at the heart of a debate in the user community over two fast, multiprocessing architectures: MPP (massively parallel processing) and SMP (symmetric multiprocessing).

In an MPP system, each node has its own operating system and memory. Thus, the system must contend with latency and overhead when transaction-processing requests need to hop among multiple nodes. By contrast, SMP systems have a common operating system and common memory. Speed is slowed for applications that require large volumes of data and a lot of interaction, which is typical for data-warehouse applications. Such issues made many people believe that SMP would slowly fade away. But it's not happening.

Case in point: General Accident Insurance in Philadelphia. The insurer knew that an enterprise data warehouse it wanted to build would hold data that spanned multiple years. More important, General Accident expected that the data warehouse would grow from 100 Gbytes to 3 terabytes very quickly. An MPP system seemed the natural solution. But that's not what the company chose.

"To handle so many joins for data mining, we decided we had to use a parallel system," says Charlie Drumm, a senior business consultant at General Accident. "We're not a high-technology shop, and to bring in MPP on Day 1 would have brought us to our knees."

Specifically, Drumm doesn't think enough MPP-specific tools are available yet, or that MPP is mature enough for commercial applications yet. The MPP architecture carries complexities relating to its "shared nothing" (memory and operating system) architecture. "I knew we'd be safe with SMP," reasons Drumm. "It's widely used, less complex, and there are many more tools."

Because they're on a common node, General Accident's NCR WorldMark systems can migrate from SMP to MPP in the future.

"I see convergence of the two technologies," says Drumm. "MPP is for very large data warehouses, but SMP has TP {transaction processing} and data-mart life cycles."

Industry analysts say General Accident's decision is no accident. "SMP came a long way during the quasi-religious war," says Howard Richmond, a VP and analyst with Gartner Group Inc., an IT advisory firm in...