|
Will Plishker
Bio:
William Plishker is presently working towards a Ph.D. in Electrical
Engineering at the University of California, Berkeley. His research
interests include design automation techniques for programmable
embedded systems. In 2000, he received his B.S. degree in Computer
Engineering from the Georgia Institute of Technology. He is a
member of IEEE.
Abstract:
Application specific programmable systems are capable of high
performance implementations while remaining flexible enough to support
a range of applications. Architects of these systems achieve high
performance through domain specific optimizations such as multiple
programmable elements, dedicated logic, and specialized memory and
interconnection. However, these features are often introduced at the
expense of programming productivity. For
application specific programmable systems to succeed, programmers must
be able to deliver high performance
implementations quickly. We examine one of the most
performance critical, time consuming, manual steps to arriving at
efficient implementations on these platforms: the mapping of an
application to the target architecture. To accelerate this
step, we construct a model of the architecture which captures its key
features, while being amenable to automated mapping. We
construct an analogous representation of the application which may be
mapped to the architectural model. We formulate this as an
integer linear programming (ILP) problem, which considers the
computation, data, and communication aspects of the mapping problem
simultaneously. We demonstrate this approach using a common
high performance networking multiprocessor, the Intel's
network processor line the IXP2xx series. This
method finds optimal solutions with respect to these models with and
produces high performance implementations on representative network
applications.
Links:
|
