Overview
Topic status: We're looking for students to study this topic.
Random Number Generators (RNGs) are needed for a wide range of computational problems in Science and Engineering which require statistically random input. In this project you will examine the widely used Mersenne Twister RNG algorithm, written in a high level language (e.g. C). The intended use of your RNG is for one of two possible applications, the first being as random input to a UAV Evolutionary algorithm based path planner running on an FPGA, and the second being for a Monte Carlo based analysis of data from QUT's Biofuel Engineering Research Facility. You will start by understanding and profiling the RNG software to identify parts suitable for FPGA co-processing, and also conduct a literature review to identify previous efforts in this area. Thereafter, you will attempt to design and simulate custom FPGA instructions using the VHDL programming language and Xilinx software tools, and implement your design on one of the available Xilinx FPGA computing platforms. If time permits, you will also explore the use of a higher level FPGA application development tool for this purpose (e.g. Mitrion-C, Impulse-C, DIME-C, ROCCC2.0, FpgaC, System Generator, ISE Schematic Design, or similar), and compare and contrast the use of a higher level tool with development in VHDL. You will be supervised by both Faculty and High Performance Computing staff.
Find out more about this scholarship
- Study level
- Honours
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Contact
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Please contact the supervisor.
Dr Ross Hayward
Associate Professor Shlomo Geva
