Thursday, September 11, 1997
CPS-615 Assignment 1
David
Figatner
Assignment Instructions: Please spend some time examining work
that you are interested in within your own department, out there on the
web, or wherever. Pick a particular problem where parallel computing has
been applied. Build a web page describing briefly the application, the
use of parallelism, and your assessment of its success, weaknesses, and
challenges. If it is not known whether or not parallelism has been applied
to your problem, then describe why simulation of the problem would be important.
Also, if the problem can be parallelized, what would be the advantages
of this parallelism, etc.
Complete assignment and parallel computing links: http://osprey4.npac.syr.edu:7777/cps615-fall97/index.html
EXAMINED DEPARTMENT
Legal Document Databases (e.g., WestLaw and Lexis-Nexis)
-
Search, storage and retrieval of data within legal
database
-
Possibility of more indepth searches ("smart" searching)
STATUS OF PARALLELIZATION
OF EXAMINED DEPARTMENT
Unknown. Although, there has been some work
done on parallel searches through large databases, I do not think this
has been applied to any legal document databases.
IMPORTANCE OF PROBLEM
Legal research is of paramount importance for law
firms to successfully represent their clients. The first step in
litigation or contract formation is research. Today, research has
been mostly computerized onto large databases such as WestLaw
and Lexis-Nexis.
Although these databases allow quick searches and retrievals, there is
always a place for even faster and more advanced searches. One way
that this can be done is through the use of parallel computers and algorithms
on the document servers and clients. Since time is money, and the
more time the computer spends searching the less time the lawyer has to
look over the found documents, the use of parallelization for queries into
the database could result in better utilization of a law firm's time and
money.
PARALLELIZATION OF THE PROBLEM
As of now, databases are contained on servers and
searched through client machines. Although this is in a small way
a parallel setup, it does not utilize true parallelizational algorithms
to improve speed. By having client computers which can concurrently
conduct a single search, query times could be drastically cut down, and
more advanced searches can be conducted on larger and larger sets of documents.
Legal documents (i.e., cases, law journals and
statutes) are being continuously added to these legal databases.
In order to keep up with this continuous stream of new documents, there
is a need for faster computers and faster searches. Currently, computers
are still improving in speed and can handle the mounting number of documents.
But, when computer engineering slows down in 10 years, there will be a
need for more advanced computer systems to handle the ever increasing legal
document load. The computer system will have to be designed to exploit
parallelization to increase speed and robustness of the search.
DISADVANTAGES OF PARALLELIZATION
The advantages of parallelization have already been
mentioned above. The disadavantages of using parallel algorithms
and computers on this problem is the same as on other simulation and computer
problems. There is a lack of successful and easy to implement programming
language and hardware capabilities to implement this technology.
Furthermore, because the speed of searching is currently so high, legal
database companies do not see the future advantage of researching and developing
parallel algorithms and computers to improve search time. Until computers
stop advancing in speed and functionality, it will be difficult for parallelization
to become an important part of the legal and business community.
NOTES
The parallelization of legal databases is only an
example of how parallel machines/systems could exploit this developing
technology. Any type of database can be improved by parallelization
(e.g., business databases, financial history databases). Of course,
simulation on top of these databases would also be a valid use of this
technology. An example of this would be to have a large database
containing financial history which is accessed in parallel connecting with
a running parallel simulation which does future financial forecasting.