Nikolaos Vassiliadis

Real-time canny edge detection parallel implementation for FPGAs

Edge detection is one of the most fundamental algorithms in digital image processing. The Canny edge detector is the most implemented edge detection algorithm because of its ability to detect edges even in images that are intensely contaminated by noise. However, this is a time consuming algorithm and therefore its implementations are difficult to reach real time response speeds. Especially nowadays where the demand for high resolution image processing is constantly increasing, the need for fast and efficient edge detector implementations is ever so present. A new parallel Canny edge detector FPGA implementation is proposed in this paper to answer this demand. This design takes advantage of 4-pixel parallel computations to achieve high throughput without increasing the on-chip memory demands. Synthesis and simulation results are presented to prove the designs efficiency and high frames per second rate.

A compact hybrid-multiplexed potentiostat for real-time electrochemical biosensing applications.

The architecture and design of a compact, multichannel, hybrid-multiplexed potentiostat for performing electrochemical measurements on continuously-biased electrode arrays is presented. The proposed architecture utilises a combination of sequential and parallel measurements, to enable high performance whilst keeping the system low-cost and compact. The accuracy of the signal readout is maintained by following a special multiplexing approach, which ensures the continuous biasing of all the working electrodes of an array. After sampling the results, a digital calibration technique factors out errors from component inaccuracies. A prototype printed circuit board (PCB) was designed and built using off-the-shelf components for the real-time measurement of the amperometric signal of 48 electrodes. The operation and performance of the PCB was evaluated and characterised through a wide range of testing conditions, where it exhibited high linearity (R(2)>0.999) and a resolution of 400pA. The effectiveness of the proposed multiplexing scheme is demonstrated through electrochemical tests using KCl and [Fe(CN)6](3-) in KCl solutions. The applicability of the prototype multichannel potentiostat is also demonstrated using real biosensors, which were applied to the detection of IgA antibodies.

The ARISE Approach for Extending Embedded Processors With Arbitrary Hardware Accelerators

ARISE introduces a systematic approach for extending once an embedded processor to support thereafter the coupling of an arbitrary number of custom computing units (CCUs). A CCU can be a hardwired or a reconfigurable unit, which can be utilized following a tight and/or loose model of computation. By selecting the appropriate model of computation for each part of the application, the complete application space is considered for acceleration, resulting in significant performance improvements. Also, ARISE offers modularity and scalability and is not restricted by the opcode space and operands limitation problems that exist in such type of machines. To support these features we introduce a machine organization that allows the cooperation of a processor and a set of CCUs. To control the CCUs we extend once the instruction set of the processor with eight instructions. To efficiently incorporate these features to an embedded processor, we propose a micro-architecture implementation that minimizes the control and communication overhead between the processor and the CCUs. To evaluate our proposal, we extended a MIPS processor with the ARISE infrastructure and implemented it on a Xilinx field-programmable gate array (FPGA). Implementation results, demonstrate that the timing model of the processor is not affected. Also, we implemented a set of benchmarks on the ARISE evaluation machine. Performance results prove significant improvements and reduced communication overhead compared to a typical coprocessor approach.

A RISC architecture extended by an efficient tightly coupled reconfigurable unit

In this paper, the architecture of an embedded processor extended with a tightly-coupled coarse-grain reconfigurable functional unit (RFU) is proposed. The efficient integration of the RFU with the control unit and the datapath of the processor eliminate the communication overhead between them. To speed up execution, the RFU exploits instruction level parallelism (ILP) and spatial computation. Also, the proposed integration of the RFU efficiently exploits the pipeline structure of the processor, leading to further performance improvements. Furthermore, a development framework for the introduced architecture is presented. The framework is fully automated, hiding all reconfigurable hardware related issues from the user. The hardware model of the architecture was synthesized in a 0.13 µm process and all information regarding area and delay were estimated and presented. A set of benchmarks is used to evaluate the architecture and the development framework. Experimental results prove performance improvements in addition to potential energy reduction.

A complete platform and toolset for system implementation on fine-grain reconfigurable hardware

In this paper a complete system for the implementation of digital logic in a fine-grain reconfigurable platform is introduced. The system is composed of two parts: the fine-grain reconfigurable hardware platform (FPGA) on which the logic is implemented and the set of CAD tools for mapping logic to the FPGA platform. It is the first such complete academic system. The novel energy efficient FPGA architecture was designed and simulated in STM 0.18 mm CMOS technology. The detailed design and circuit characteristics of the Configurable Logic Block as well as the interconnection network are determined and evaluated for energy, delay and area. Concerning the tool flow, each tool can operate as a standalone program as well as part of a complete design framework, composed by existing and new tools. q 2004 Elsevier B.V. All rights reserved.

The ARISE Reconfigurable Instruction Set Extensions Framework

In this paper, we introduce the ARISE framework for the systematic extension of typical processors with the necessary infrastructure to support arbitrary number and type of reconfigurable hardware units. ARISE extends the micro-architecture of the processor with an interface to allow the coupling of the hardware units. Furthermore, the instruction set of the processor is extended with instructions which expose to the programmer/compiler the full control of the interface. This control includes the configuration of operations on the hardware units, execution of these operations, and communication of data between the processor and the units. The new instructions are incorporated without the need to redesign the processor instruction set architecture. To evaluate our proposal a model of an ARISE extended MIPS processor has been designed. Using a turbodecoder algorithm as benchmarking application a simulation of the ARISE model has been performed. Performance results show impressive application speedups up to times7.5.

An automated development framework for a RISC processor with reconfigurable instruction set extensions

By coupling a reconfigurable hardware to a standard processor, high levels of flexibility and adaptability are achieved. However, this approach requires modifications to the compiler of the processor to take into account reconfigurable aspects. In this paper, a development framework for a RISC processor with reconfigurable instruction set extensions is presented. The framework is fully automated, hiding all reconfigurable related issues from the user and can be used for both program and fine-tune the architecture at design time. We demonstrate the above issues using a set of benchmarks. Experimental results show an x2.9 average speedup in addition to potential energy reduction

A Novel FPGA Architecture and an Integrated Framework of CAD Tools for Implementing Applications

A complete system for the implementation of digital logic in a Field-Programmable Gate Array (FPGA) platform is introduced. The novel power-efficient FPGA architecture was designed and simulated in STM 0.18 μm CMOS technology. The detailed design and circuit characteristics of the Configurable Logic Block, the interconnection network, the switch box and the connection box were determined and evaluated in terms of energy, delay and area. A number of circuit-level low-power techniques were employed because power consumption was the primary concern. Additionally, a complete tool framework for the implementation of digital logic circuits in FPGA platforms is introduced. Having as input VHDL description of an application, the framework derives the reconfiguration bitstream of FPGA. The framework consists of: i) non-modified academic tools, ii) modified academic tools and iii) new tools. Furthermore, the framework can support a variety of FPGA architectures. Qualitative and quantitative comparisons with existing academic and commercial architectures and tools are provided, yielding promising results.

Real-Time Machine Vision FPGA Implementation for Microfluidic Monitoring on Lab-on-Chips

A machine vision implementation on a field-programmable gate array (FPGA) device for real-time microfluidic monitoring on Lab-On-Chips is presented in this paper. The machine vision system is designed to follow continuous or plug flows, for which the menisci of the fluids are always visible. The system discriminates between the front or “head” of the flow and the back or “tail” and is able to follow flows with a maximum speed of 20 mm/sec in circular channels of a diameter of 200 μm (corresponding to approx. 60 μl/sec). It is designed to be part of a complete Point-of-Care system, which will be portable and operate in non-ideal laboratory conditions. Thus, it is able to cope with noise due to lighting conditions and small LoC displacements during the experiment execution. The machine vision system can be used for a variety of LoC devices, without the need for fiducial markers (such as redundancy patterns) for its operation. The underlying application requirements called for a complete hardware implementation. The architecture uses a variety of techniques to improve performance and minimize memory access requirements. The system input is 8 bit grayscale uncompressed video of up to 1 Mpixel resolution. The system uses an operating frequency of 170 Mhz and achieves a computational time of 13.97 ms (worst case), which leads to a throughput of 71.6 fps for 1 Mpixel video resolution.

FPGA-based machine vision implementation for Lab-on-Chip flow detection

This paper presents an FPGA-based machine vision implementation for flow detection on Lab-on-Chip (LoC) experiments. The proposed machine vision system is designed to provide real-time information to the LoC user about the state of the flows (flow coordinates and points of interest) as well as input to the LoC controller. It is uniquely designed to compensate noise in the input video originating from non ideal lighting conditions or LoC movement. This machine vision implementation achieves real time response for input videos of 1Mpixel resolution and frame-rates exceeding 60fps for microfluidic flows with a maximum speed of 20mm/sec.