Automatic FPGA Synthesis of Memory Intensive C-based Kernels

Realising high performance image and signal processing
applications on modern FPGA presents a challenging implementation problem due to the large data frames streaming through these systems. Specifically, to meet the high bandwidth and data storage demands of these applications, complex hierarchical memory architectures must be manually specified
at the Register Transfer Level (RTL). Automated approaches which convert high-level operation descriptions, for instance in the form of C programs, to an FPGA architecture, are unable to automatically realise such architectures. This paper
presents a solution to this problem. It presents a compiler to automatically derive such memory architectures from a C program. By transforming the input C program to a unique dataflow modelling dialect, known as Valved Dataflow (VDF), a mapping and synthesis approach developed for this dialect can
be exploited to automatically create high performance image and video processing architectures. Memory intensive C kernels for Motion Estimation (CIF Frames at 30 fps), Matrix Multiplication (128x128 @ 500 iter/sec) and Sobel Edge Detection (720p @ 30 fps), which are unrealisable by current state-of-the-art C-based synthesis tools, are automatically derived from a C description of the algorithm.

An automatic COLREGs-compliant obstacle avoidance system for an unmanned surface vehicle

Unmanned surface vehicles are becoming increasingly vital tools in a variety of maritime applications. Unfortunately, their usability is severely constrained by the lack of a reliable obstacle detection and avoidance system. In this article, one such experimental platform is proposed, which performs obstacle detection, risk assessment and path planning (avoidance) tasks autonomously in an integrated manner. The detection system is based on a vision-LIDAR (light detection and ranging) system, whereas a heuristic path planner is utilised. A unique property of the path planner is its compliance with the marine collision regulations. It is demonstrated through hardware-in-the-loop simulations that the proposed system can be useful for both uninhabited and manned vessels.

Chloroplast microsatellites: new tools for studies in plant ecology and systematics

The nonrecombinant, uniparentally inherited nature of organelle genomes
makes them useful tools for evolutionary studies. However, in plants, detecting
useful polymorphism at the population level is often difficult because of the
low level of substitutions in the chloroplast genome, and because of the slow
substitution rates and intramolecular recombination of mtDNA. Chloroplast
microsatellites represent potentially useful markers to circumvent this problem
and, to date, studies have demonstrated high levels of intraspecific variability.
Here,we discuss the use of these markers in ecological and evolutionary
studies of plants, as well as highlighting some of the potential problems
associated with such use.

A neural network based tool for semi-automatic code transformation

A neural network based tool has been developed to assist in the process of code transformation. The tool offers advice on appropriate transformations within a knowledge-driven, semi-automatic parallelisation environment. We have identified the essential characteristics of codes relevant to loop transformations. A Kohonen network is used to discover structure in the characterised codes thus revealing new knowledge that may be brought to bear on the mapping between codes and transformations or transformation sequences. A transform selector based on this process has been developed and successfully applied to the parallelisation of sequential codes.

Assistive software tools for secondary-level students with literacy difficulties.

Study conducted to evaluate the effectiveness of four assistive technology (AT) tools on literacy: (1) speech synthesis, (2) spellchecker, (3) homophone tool, and (4) dictionary. All four of these programs are featured in TextHelp’s Read&Write Gold software package. A total of 93 secondary-level students with reading disabilities participated in the study. The participants completed a number of computer-based literacy tests after being assigned to a Read&Write group or a control group that utilized Microsoft Word. The results indicated that improvements in the following areas for the Read&Write group: (1) reading comprehension, (2) homophone error detection, (3) spelling error detection, and (4) word meanings. The Microsoft Word group also improved in the areas of word meanings and error detection, though performed worse on homophone error detection. The authors contend that these results indicate that speech synthesis, spell checkers, homophone tools, and dictionary programs have a positive effect on literacy among students with reading disabilities. This study was conducted by researchers at the Queen’s University in Belfast, Ireland.