>Name of institution: Computer Science Department
		      Rochester Institute of Technology
		      Rochester, NY  14623-0887

>Name of contact person:  Nan Schaller/Andrew Kitchen
>Address for contact person: Ross Memorial Bldg., 1 Lomb Memorial Dr.
>E-mail Address:   ncs@cs.rit.edu/atk@cs.rit.edu
>Telephone number:  (716) 475-2139/(716) 475-6540

>Access to what computers?  various workstations/88 node transputer system

>Degree offered?  B.S./M.S. Computer Science

>Short Curricul(um)(a) Statement:  The RIT computer science degrees offer
				   broad core of courses with concentrations
				   available in a variety of areas including
				   parallel computing.

>Remarks relevant to courses offered (e.g., to list courses rather than
> Research activities:

Parallel computing topics are being integrated throughout the curriculum.

The parallel computing concentration consists of two courses:

The first course, Introduction to Parallel Computing, is designed to provide 
students with the flavor of parallel computing.  The course presents the basic 
issues of parallel computing: parallel architectures, algorithms, languages, 
network topology, and granularity.  The inter-relationship between architecture 
and algorithm design, and the effect of this relationship on efficiency is also 
discussed.  This course encourages the student to implement parallel algorithms 
and experiment with them, to understand the influence of such issues as 
connection topology on problem solution, and to discover the practical 
limitations of parallel computing.

The second course, Parallel Algorithms and Program Design, presents the 
principal trends in parallel algorithm design and investigates the interplay 
between architecture and algorithmic structure.  This material is developed
through the study of specific applications, focusing on the algorithms that 
have proved valuable in these areas. Some of the topics covered in this course 
are: the influence of models of parallel computation on program design, metrics 
for the analysis of parallel algorithms, one-dimensional versus 
multi-dimensional problems, algorithmic complexity, sorting and searching,
matrix operations, combinatorial and graph theoretic problems, graphics
processing, Fourier transforms, and dynamical systems.  The relationship between
algorithmic topology and hardware topology in distributed memory systems is 
investigated in some detail.