| Περίληψη: | On-line monitoring is an important challenge in future biotechnology applications,
for instance in the domain of precision livestock farming where a strong need is
present for low-cost intelligent sensors to monitor animal welfare. On-line poultry
monitoring can significantly improve living conditions of hens in industrial farms.
A very low-cost low-energy solution needs to be provided though due to the stringent
battery limitations. Domain-specific ASIPs can be an ideal solution when
they cover enough submarkets to increase the production volume (reducing the
price) and ultra-low energy concepts are used for their realization.
This work is a part of a larger project and aiming to high energy-efficiency.
The current study implements data parallelization, using a recently introduced
software-controlled SIMD realization in an innovative way. The approaches that
have been employed for the determination of the final instruction set of the architecture
that has been created for the mapping of the critical Gauss loop of the
detection application, are thoroughly explored. The re-design of the data-parallel
data path, also referred to as Soft-SIMD architecture, has been necessary in order
to achieve instruction encoding optimization.
Furthermore, we have explored the capabilities that a commercial compiler retargetable
Tool, like Target, can offer for our target design and we have suggested
some potential modifications that would help the tool to become more efficient and
useful for a designer’s needs in such architecture. Thereby, this study also demonstrates
the promising results obtained by experimenting with detours around the
current Target tool design limitations.
Finding the right balance between efficiency and flexibility requires the ability to
quickly evaluate alternative architectures through simulations and testing techniques.
The methods developed for exactly this purpose, with the help of Target’s
IP Designer retargetable tool-suite, are discussed in detail. By exploiting the profiling
information produced by the ISS, and by reading the assembly code produced
by the C compiler, it is possible to identify the instructions in the critical loop, and
optimize them by using a number of techniques discussed. The main purpose of
this optimization is to reduce the cycle count of the application, in order to reduce
the overall power consumption. VHDL files of the optimized and un-optimized
processor are automatically generated using the HDL generation tool.
However, examining a bio-imaging application, instantiated from the ULP-ASIP
architectural template [FEENECS book], many other issues are present too. In
particular, the way that these kinds of implementations have to be tested should
be taken into consideration. Preferably, the testability has not only to be sufficient
and efficient but also reusable, in the sense that test patterns should be able to
be generated not only for a specific application or for a group of applications
but for the entire architectural template. Therefore, this study also illustrates a
Systematic Test Vector generation process for the ULP-ASIP template. Our goal
is to make generalized principles, because such principles are reusable and can be
applied to any instances, such as our present processor for the Gauss Filter.
Finally, this study is completed by presenting some realistic power numbers based
on layout back-annotation, which concern the data path components of the processor.
Based on all the advanced optimizations and broad search space explorations
that are presented in this thesis, a heavily optimized ASIP architecture has been
fully implemented which results in a low-cost ultra low-energy consumption while
still meeting all the performance requirements.
|
|---|
