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Model to Hardware Matching for nm Scale
Technologies Sani Nassif, IBM
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Abstract:
Our ability to reliably predict the outcome of a semiconductor
manufacturing process has been steadily deteriorating. This is happening
because of two important factors.
- First, the overall CMOS technology slowdown has led to rapidly
increasing complexity in the process and in its interaction with design.
This has in turn caused an increase in the number and magnitude of
systematic sources of mismatch between simulation models (both at the
circuit simulation and timing levels) and hardware measurements.
- Second, manufacturing variability -long a source of concern only for
analog design- is becoming important for digital designs as well and
thus its prediction is now a first order priority. However, it is
competing for the attention of researchers and CAD developers with a
host of other so-called nm effects, thus slowing down the delivery of
needed solutions.
The result is (a) our ability to arbitrarily compose a design out of
disparate components is compromised because of a high degree of
interaction between these components , and (b) our ability to predict
the nominal performance of a design as well as its tolerances and
sensitivities is in danger. Phenomena like SRAM stability and leakage
power variations are the first of many problems we are facing at 65nm
and below.
In this talk, we will review these issues and show how they are all
related to the core issue of model to hardware matching. We will also
show examples of potential solutions to this problem some of which are
currently being developed in IBM, and some which are longer term and
would benefit greatly from the attention of the academic community.
Sani Nassif is Manager of the Tools and Technology
Department at IBM Austin Research Laboratory. Sani received his PhD from Carnegie-Mellon university in the eighties. He worked for ten years at Bell Laboratories on various aspects of design and technology coupling including device modeling, parameter extraction, worst case analysis, design optimization and circuit simulation. He joined the IBM Austin Research Laboratory in January 1996 where he is presently managing the tools and technology department, which is focused on design/technology coupling and includes activities in: model to hardware matching, simulation and modeling, physical design, statistical modeling, statistical technology characterization and similar areas.