CSC/ECE 506 Fall 2007/wiki1 2 sk

Topic for Discussion

Section 1.1.1, second half: Commercial application trend

• What characterizes present-day applications?
• How much memory, processor time, etc.?
• How high is the speedup?

Overview

Parallel Computer Architecture has been an active research area for almost 40 years and commercial parallel computers have been available for more than 35 years. After getting off to a slow start, this area has now taken off. Shared memory multiprocessors have dominated this development. This is an area that has sprung out of tireless research and numerous published breakthrough results.

The degree of parallelism in case of commercial applications is not as high as in scientific applications. But, use of parallel computing in commercial application is even more wide spread.

Transaction Processing Performance Council(TPC) has setup benchmarks that measure the performance of a system in terms of Throughput Per Second (tps)on a typical workload.

The TPC-E benchmark uses a database to model a brokerage firm with customers who generate transactions related to trades, account inquiries, and market research. The brokerage firm in turn interacts with financial markets to execute orders on behalf of the customers and updates relevant account information.

The benchmark is “scalable,” meaning that the number of customers defined for the brokerage firm can be varied to represent the workloads of different-size businesses. The benchmark defines the required mix of transactions the benchmark must maintain. The TPC-E metric is given in transactions per second (tps). It specifically refers to the number of Trade-Result transactions the server can sustain over a period of time.

Results of the benchmark tests run on various systems can be found at: http://www.tpc.org/tpce/tpce_perf_results.asp

Multiprocessor architecture is widely employed in the commerical environment

Below are the examples for a few sectors.

Applications in Engineering and Design

• Design of airfoils (optimizing lift, drag, stability), internal

combustion engines (optimizing charge distribution, burn), high-speed circuits (layouts for delays and capacitive and inductive effects), and structures (optimizing structural integrity, design parameters, cost, etc.).

• Design and simulation of micro- and nano-scale systems.
• Process optimization, operations research

Commercial Applications

• Some of the largest parallel computers power the wall street!
• Data mining and analysis for optimizing business and marketing

decisions.

• Large scale servers (mail and web servers) are often

implemented using parallel platforms.

• Applications such as information retrieval and search are

typically powered by large clusters.

Applications in Computer Systems

• Network intrusion detection, cryptography, multiparty computations

are some of the core users of parallel computing techniques.

• Embedded systems increasingly rely on distributed control

algorithms.

• A modern automobile consists of tens of processors communicating

to perform complex tasks for optimizing handling and performance.

• Conventional structured peer-to-peer networks impose overlay

networks and utilize algorithms directly from parallel computing.

http://top500.org/stats/list/29/apparea/