High throughput spatial convolution filters on FPGAs

Digital signal processing (DSP) on field- programmable gate arrays (FPGAs) has long been appealing because of the inherent parallelism in these computations that can be easily exploited to accelerate such algorithms. FPGAs have evolved significantly to further enhance the mapping of these algorithms, included additional hard blocks, such as the DSP blocks found in modern FPGAs. Although these DSP blocks can offer more efficient mapping of DSP computations, they are primarily designed for 1-D filter structures. We present a study on spatial convolutional filter implementations on FPGAs, optimizing around the structure of the DSP blocks to offer high throughput while maintaining the coefficient flexibility that other published architectures usually sacrifice. We show that it is possible to implement large filters for large 4K resolution image frames at frame rates of 30–60 FPS, while maintaining functional flexibility

Digital Signal Processing Education: Technology and Tradition

In this paper we discuss a DSP course presented to both University students and to participants on industrial short courses. The "traditional" DSP course will typically run over one to two semesters and usually cover the fundamental mathematics of z-, Laplace and Fourier transforms, followed by the algorithm and application detail. In the course we will discuss, the use of advanced DSP software and integrated support software allow the presentation time to be greatly shortened and more focussed algorithm and application learning to be introduced. By combining the traditional lecture with the use of advanced DSP software, all harnessed by the web, we report on the objectives, syllabus, and mode of teaching

Digital signal processing: the impact of convergence on education, society and design flow

Design and development of real-time, memory and processor hungry digital signal processing systems has for decades been accomplished on general-purpose microprocessors. Increasing needs for high-performance DSP systems made these microprocessors unattractive for such implementations. Various attempts to improve the performance of these systems resulted in the use of dedicated digital signal processing devices like DSP processors and the former heavyweight champion of electronics design – Application Specific Integrated Circuits. The advent of RAM-based Field Programmable Gate Arrays has changed the DSP design flow. Software algorithmic designers can now take their DSP algorithms right from inception to hardware implementation, thanks to the increasing availability of software/hardware design flow or hardware/software co-design. This has led to a demand in the industry for graduates with good skills in both Electrical Engineering and Computer Science. This paper evaluates the impact of technology on DSP-based designs, hardware design languages, and how graduate/undergraduate courses have changed to suit this transition

A novel approach to the design of DSP systems using minimum complexity Finite State Machines

The paper presents a new and different approach to the design and realisation of Digital Signal Processing (DSP)systems by utilising Finite State Machines (FSM). The DSP system is modelled by mapping all its potential states into an FSM, whose complexity is usually very high. The FSM mirrors the complete functionality of the system and thus describes its behaviour in full detail. Examples for FSMs of first and second order digital recursive filters are provided and the current version of the software simulating the FSM corresponding to any linear time-invariant DSP system is described. The potential of this approach including state reduction techniques as well as the inclusion of non-linear DSP systems is also outlined, and further future research intentions are briefly explored

The development of a portable Earth's field NMR system for the study of Antarctic sea ice : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Electronics at Massey University

A portable Nuclear Magnetic Resonance (NMR) spectrometer based on digital signal processor (DSP) technology has been developed and applied to the study of the structure of Antarctic sea ice. The portability of this system means that external sources of noise can be minimised and remote sites can be investigated. A new sea-ice probe has been developed in conjunction with the spectrometer allowing in-situ measurement of water content, relaxation times and self diffusion. The new probe minimises disturbances to the sea ice sample which have been a problem with previous techniques. The core of the spectrometer consists of a Motorola DSP56303 DSP which controls the NMR experiment under the supervison of a host computer which in this case is a PC laptop. Communication between host and DSP is via either a PCMCIA card or USB interface. DSP software runs the experiment, controls acquisition and performs digital filtering of the NMR data before sending it to the PC for analysis and display. The flexibility of the DSP based core means that this system could be adapted to other control applications with relative ease

A Dual Digital Signal Processor VME Board For Instrumentation And Control Applications

A Dual Digital Signal Processing VME Board was developed for the Continuous Electron Beam Accelerator Facility (CEBAF) Beam Current Monitor (BCM) system at Jefferson Lab. It is a versatile general-purpose digital signal processing board using an open architecture, which allows for adaptation to various applications. The base design uses two independent Texas Instrument (TI) TMS320C6711, which are 900 MFLOPS floating-point digital signal processors (DSP). Applications that require a fixed point DSP can be implemented by replacing the baseline DSP with the pin-for-pin compatible TMS320C6211. The design can be manufactured with a reduced chip set without redesigning the printed circuit board. For example it can be implemented as a single-channel DSP with no analog I/O.Comment: 3 PDF page