With the advances in very large scale integration (VLSI) technology, hardware is going
parallel. Software, which was traditionally designed to execute on single core microprocessors,
now faces the tough challenge of taking advantage of this parallelism, made available
by the scaling of hardware. The work presented in this dissertation studies the acceleration
of electronic design automation (EDA) software on several hardware platforms such
as custom integrated circuits (ICs), field programmable gate arrays (FPGAs) and graphics
processors. This dissertation concentrates on a subset of EDA algorithms which are heavily
used in the VLSI design flow, and also have varying degrees of inherent parallelism
in them. In particular, Boolean satisfiability, Monte Carlo based statistical static timing
analysis, circuit simulation, fault simulation and fault table generation are explored. The
architectural and performance tradeoffs of implementing the above applications on these
alternative platforms (in comparison to their implementation on a single core microprocessor)
are studied. In addition, this dissertation also presents an automated approach to
accelerate uniprocessor code using a graphics processing unit (GPU). The key idea is to
partition the software application into kernels in an automated fashion, such that multiple
instances of these kernels, when executed in parallel on the GPU, can maximally benefit
from the GPU?s hardware resources.
The work presented in this dissertation demonstrates that several EDA algorithms can
be successfully rearchitected to maximally harness their performance on alternative platforms
such as custom designed ICs, FPGAs and graphic processors, and obtain speedups upto 800X. The approaches in this dissertation collectively aim to contribute towards enabling
the computer aided design (CAD) community to accelerate EDA algorithms on arbitrary
hardware platforms.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2009-12-7471 |
| Date | 2009 December 1900 |
| Creators | Gulati, Kanupriya |
| Contributors | Khatri, Sunil |
| Source Sets | Texas A and M University |
| Language | English |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | application/pdf |
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