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http://hdl.handle.net/1813/11065
| Title: | Profiling Infrastructure for the Performance Evaluation of Asynchronous Systems |
| Authors: | Fang, David |
| Keywords: | asynchronous circuits profiling trace analysis |
| Issue Date: | 3-Jul-2008 |
| Abstract: | Designing and optimizing large-scale, asynchronous circuits is often an iterative
process that cycles through synthesis, simulating, benchmarking, and program
rewriting. Asynchronous circuits are usually specified by high-level, sequential or
concurrent programs that prescribe the intended behavior. The self-timed nature
of the interface gives designers much freedom to refine and rewrite equivalent specifications
for improved circuit synthesis. However, at any step in the design cycle,
one faces an uncountable number of choices for program rewriting ? one simply
cannot afford to explore all possible transformations. Informed optimizations and
design space pruning can require detailed knowledge of the run-time behavior of
the program, which is what our simulation trace analysis infrastructure provides.
Tracing entire simulations gives users the opportunity to understand program execution
in great detail. Most importantly, trace profiling captures typical run-time
behavior and input-dependent behavior that cannot always be inferred from static
analysis. Profiling provides valuable feedback for optimizing both high-level transformations
and low-level netlist synthesis.
To address this need for profiling, we present a framework for analyzing the
simulated execution of high-level, concurrent programs, as a foundation for iterative
optimization and synthesis of asynchronous circuits. The framework includes a
Scheme environment and a library of primitive procedures for handling and querying
trace data. Interactivity is essential for analysis sessions where the sequence of queries to execute is not known a priori. The initial library also includes procedures
for some frequently run analyses (built on top of the primitives). Providing
an interface for working directly with the simulation and trace data structures
makes analysis development within our framework both flexible and convenient.
The extensibility of our framework enables compilation-free development and prototyping
of custom analysis routines, so users can easily share and build upon the
work of others. The primary purpose of this analysis framework is to enable future
tools to use profile-driven feedback in automating iterative optimization and
design-space exploration. |
| URI: | http://hdl.handle.net/1813/11065 |
| Appears in Collections: | Theses and Dissertations (OPEN)
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