7,287 research outputs found

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

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    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

    Programmable Logic Devices in Experimental Quantum Optics

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    We discuss the unique capabilities of programmable logic devices (PLD's) for experimental quantum optics and describe basic procedures of design and implementation. Examples of advanced applications include optical metrology and feedback control of quantum dynamical systems. As a tutorial illustration of the PLD implementation process, a field programmable gate array (FPGA) controller is used to stabilize the output of a Fabry-Perot cavity

    Micro-threading and FPGA implementation of a RISC microprocessor : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Palmerston North, New Zealand

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    Appendix E removed due to copyright restrictions. Articles are available in the print copy held in the libraryThis thesis is the outcome of research in two areas of computer technology: microprocessor and multi-processor architectures (specifically from the perspective of how differently they tolerate highly-latent and non-deterministic events), and hardware design of complex digital systems containing both datapath and control (particularly microprocessors). This thesis starts by pointing out that in order to achieve high processing speeds, current popular superscalar microprocessors (e.g. Intel Pentiums, Digital Alpha, etc) rely heavily on the technique of speculating the outcome of instruction flow in order to predict the behaviour of non-deterministic computing operations (as in loading operands from high-latency memory into the processor). This is fine only if the speculation is correct. But, what if it isn't? If the speculation fails, this would mean that the processor has to abandon its current decision (which now proved to be the wrong one) for the instruction flow path taken and to start all over again with the other path (the actual correct one). This is a waste of valuable processing time and hardware resources and a reduction of performance when speculation fails. Therefore, these processors can achieve high performance only when the majority of speculations are successful (being able to predict the right path). In an attempt to overcome the above shortcomings, the first part of this thesis is an investigation of the novel vector micro-threading architecture as an alternative approach to the current superscalar-based speculative microprocessor designs. Micro-threading is based on the not-so-novel multithreading technique, which avoids speculation altogether and instead, starts running a different thread of instructions while waiting for the non-determinism to be resolved. This utilizes the chip resources more efficiently without waste of any processing power. The rest of this thesis focuses on the baseline RISC processor platform, the MIPS R2000, which is reviewed first then partially synthesized from the RTL (Register Transfer Level) description using VHDL and then simulated and tested. This is conducted in order for future research to build upon and add the micro-threading architectural add-ons and modifications. Keywords: Micro-threading, Latency Tolerance, FPGA Synthesis, RISC Architecture, MIPS R2000 processor, VHDL

    Experimental study of artificial neural networks using a digital memristor simulator

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    © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a fully digital implementation of a memristor hardware simulator, as the core of an emulator, based on a behavioral model of voltage-controlled threshold-type bipolar memristors. Compared to other analog solutions, the proposed digital design is compact, easily reconfigurable, demonstrates very good matching with the mathematical model on which it is based, and complies with all the required features for memristor emulators. We validated its functionality using Altera Quartus II and ModelSim tools targeting low-cost yet powerful field programmable gate array (FPGA) families. We tested its suitability for complex memristive circuits as well as its synapse functioning in artificial neural networks (ANNs), implementing examples of associative memory and unsupervised learning of spatio-temporal correlations in parallel input streams using a simplified STDP. We provide the full circuit schematics of all our digital circuit designs and comment on the required hardware resources and their scaling trends, thus presenting a design framework for applications based on our hardware simulator.Peer ReviewedPostprint (author's final draft

    A Scalable Correlator Architecture Based on Modular FPGA Hardware, Reuseable Gateware, and Data Packetization

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    A new generation of radio telescopes is achieving unprecedented levels of sensitivity and resolution, as well as increased agility and field-of-view, by employing high-performance digital signal processing hardware to phase and correlate large numbers of antennas. The computational demands of these imaging systems scale in proportion to BMN^2, where B is the signal bandwidth, M is the number of independent beams, and N is the number of antennas. The specifications of many new arrays lead to demands in excess of tens of PetaOps per second. To meet this challenge, we have developed a general purpose correlator architecture using standard 10-Gbit Ethernet switches to pass data between flexible hardware modules containing Field Programmable Gate Array (FPGA) chips. These chips are programmed using open-source signal processing libraries we have developed to be flexible, scalable, and chip-independent. This work reduces the time and cost of implementing a wide range of signal processing systems, with correlators foremost among them,and facilitates upgrading to new generations of processing technology. We present several correlator deployments, including a 16-antenna, 200-MHz bandwidth, 4-bit, full Stokes parameter application deployed on the Precision Array for Probing the Epoch of Reionization.Comment: Accepted to Publications of the Astronomy Society of the Pacific. 31 pages. v2: corrected typo, v3: corrected Fig. 1

    FPGA implementation of online finite-set model based predictive control for power electronics

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    Recently there has been an increase in the use of model based predictive control (MBPC) for power-electronic converters. MBPC allows fast and accurate control of multiple controlled variables for hybrid systems such as a power electronic converter and its load. The computational burden for this control scheme however is very high and often restrictive for a good implementation. This means that a suitable technology and design approach should be used. In this paper the implementation of finite-set MBPC (FS-MBPC) in field-programmable gate arrays (FPGAs) is discussed. The control is fully implemented in programmable digital logic by using a high-level design tool. This allows to obtain very good performances (both in control quality, speed and hardware utilization) and have a flexible, modular control configuration. The feasibility and performance of the FPGA implementation of FS-MBPC is discussed in this paper for a 4-level flying-capacitor converter (FCC). This is an interesting application as FS-MBPC allows the simultaneous control of the output current and the capacitor voltages, yet the high number of possible switch states results in a high computational load. The good performance is obtained by exploiting the FPGA’s strong points: parallelism and pipe-lining. In the application discussed in this paper the parallel processing for the three converter phases and a fully pipelined calculation of the prediction stage allow to realize an area-time efficient implementation

    An automatic tool flow for the combined implementation of multi-mode circuits

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    A multi-mode circuit implements the functionality of a limited number of circuits, called modes, of which at any given time only one needs to be realised. Using run-time reconfiguration of an FPGA, all the modes can be implemented on the same reconfigurable region, requiring only an area that can contain the biggest mode. Typically, conventional run-time reconfiguration techniques generate a configuration for every mode separately. To switch between modes the complete reconfigurable region is rewritten, which often leads to very long reconfiguration times. In this paper we present a novel, fully automated tool flow that exploits similarities between the modes and uses Dynamic Circuit Specialization to drastically reduce reconfiguration time. Experimental results show that the number of bits that is rewritten in the configuration memory reduces with a factor from 4.6X to 5.1X without significant performance penalties
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