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MS Thesis Defense: Abhay Raina
Friday, March 31, 2017
11:00 a.m.
CSS 2115 (In the CSS Building)
For More Information:
Maria Hoo
301 405 3681


Name: Abhay Raina

Professor Shuvra Bhattacharyya, Chair
Professor Gang Qu
Professor Rance Cleaveland

Date/Time: Friday, March 31, 2017 at 11:00 a.m.

Place: CSS 2115 (In the CSS Building)


In the design and implementation of digital signal processing (DSP) systems,
dataflow is recognized as a natural model for specifying applications, and
dataflow enables useful model-based methodologies for analysis, synthesis, and
optimization of implementations. A wide range of embedded signal processing
applications can be designed efficiently using the high level abstractions that
are provided by dataflow programming models. In addition to their use in
parallelizing computations for faster execution, dataflow graphs have
additional advantages that stem from their modularity and formal foundation.
An important problem in the development of dataflow-based design tools is the
automated synthesis of software from dataflow representations.

In this thesis, we develop new software synthesis techniques for dataflow based
design and implementation of signal processing systems. An important task in
software synthesis from dataflow graphs is that of scheduling. Scheduling
refers to the assignment of actors to processing resources and the ordering of
actors that share the same resource. Scheduling typically involves very complex
design spaces, and has a significant impact on most relevant implementation
metrics, including latency, throughput, energy consumption, and memory
requirements.  In this thesis, we integrate a model-based representation,
called the dataflow schedule graph [DSG], into the software
synthesis process. The DSG approach allows designers to model a schedule for a
dataflow graph as a separate dataflow graph, thereby providing a formal,
abstract (platform- and language-independent) representation for the schedule.

While we demonstrate this DSG-integrated software synthesis capability by
translating DSGs into OpenCL implementations, the use of a model-based schedule
representation makes the approach readily retargetable to other implementation
languages. We also investigate a number of optimization techniques to improve
the efficiency of software that is synthesized from DSGs.
Through experimental evaluation of the generated software, we demonstrate the
correctness and efficiency of our new techniques for dataflow-based
software synthesis and optimization.


This Event is For: Graduate • Faculty

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