READIT - 2009 - Indira Gandhi Centre for Atomic Research

Symmetric Multi Processing (SMP) Servers and Clusters, come under highly
available and highly reliable systems for fewer prices. SMP provides the parallel processing
mechanism with shared disk space and shared memory concept. Each processor reaches the
shared memory through a common bus. Communication between the processors occurs
through common memory. Disk controllers are accessible to all processors. The knowledge
warehousing technique can be employed in the SMP clusters. Since a variety of users and
knowledge users are involved in the library system the architecture should be capable to hold
all types of parallel transactions. SMP clusters Provides high concurrency. User can run many
concurrent requests with the better workload balances. SMP gives scalable performance to
fulfill the user or analyst need.
Core 1
Core 2
Core 1
Core 2
Core 1
Core 2
L2 Cache
L2 Cache
L2 Cache
CPU CPU CPU
Common Bus
Knowledge
Shared Memory
Warehouse
data
SMP Architecture
Access gateway
Depositing
Query
Processing
Downloading
Knowledge warehouse for Library
A knowledge staff in the library can deposit or store the exact files to the warehouse
hard disk through a gateway. The files can be of different formats like document files, video,
audio and image files of different sizes. Query processing is for analysis and report
generation. This is done by the management to take the necessary decision. A user or users at
the desktop can download a required file. These are some of the actions which are taking
place regularly in the knowledge warehousing. All these operations may occur
simultaneously and the requests are sent to the CPU scheduler. The scheduler checks the
availability of the free CPU and the job is allocated to that CPU. So the jobs are served in a
parallel manner there will not be a big queue in the scheduler.
Most of the current database software can parallelize a large number of operations.
These operations include mass loading of data, full table search, queries with exclusion
conditions, multiple queries, selection with distinct values, aggregation, sorting, creation of
tables using sub queries, creating and rebuilding indexes, inserting rows into a table from
other tables, enabling constraints, star transformation and so on. Remarkable list of
operations can be processed in parallel with the DBMS.
SMP cluster provides parallel processing which in turn improves performance for
query processing, data loading and downloading compared to the single processing. The
scalability option, allows the addition of CPUs and memory modules without any change to
the existing application. Fault tolerance enables the availability of database even when some