Analysis of Multicore CPU and GPU toward Parallelization of Total Focusing Method ultrasound reconstruction

International audienceUltrasonic imaging and reconstruction tools are commonly used to detect, identify and measure defects in different mechanical parts. Due to the complexity of the underlying physics, and due to the ever growing quantity of acquired data, computation time is becoming a limitation to the optimal inspection of a mechanical part. This article presents the performances of several implementations of a computational heavy algorithm, named Total Focusing Method, on both Graphics Processing Units (GPU) and General Purpose Processors (GPP). The scope of this study is narrowed to planar parts tested in immersion for defects. Using algorithmic simplifications and architectural optimizations, the algorithm has been drastically accelerated resulting in memory-bound implementations. On GPU, high performances can be achieved by profiting from GPU long memory transactions and from hand managed memory. Whereas on GPP, computations cost are overrun by memory access resulting in less efficient performances compared to the computing capabilities available. The following study constitutes the first step toward analyzing the target algorithm for diverse hardware in the non-destructive testing environment

Symbol Synchronization for SDR Using a Polyphase Filterbank Based on an FPGA

This paper is devoted to the proposal of a highly efficient symbol synchronization subsystem for Software Defined Radio. The proposed feedback phase-locked loop timing synchronizer is suitable for parallel implementation on an FPGA. The polyphase FIR filter simultaneously performs matched-filtering and arbitrary interpolation between acquired samples. Determination of the proper sampling instant is achieved by selecting a suitable polyphase filterbank using a derived index. This index is determined based on the output either the Zero-Crossing or Gardner Timing Error Detector. The paper will extensively focus on simulation of the proposed synchronization system. On the basis of this simulation, a complete, fully pipelined VHDL description model is created. This model is composed of a fully parallel polyphase filterbank based on distributed arithmetic, timing error detector and interpolation control block. Finally, RTL synthesis on an Altera Cyclone IV FPGA is presented and resource utilization in comparison with a conventional model is analyzed

Increasing the autonomy of Wireless Sensor Node by effective use of both DPM and DVFS methods

International audienceThe use of ubiquitous computing devices like Wireless Sensor Networks (WSNs) has increased with an exponential growth in recent years, due its low-cost, portability, easy deployment, self-organization. Since WSNs are battery-powered devices, thus main challenge faced by designers is reduction of energy consumption in WSNs. This paper presents an effective implementation of Dynamic Power Manager (DPM) and Dynamic Voltage and Frequency Scaling (DVFS) technics to increase the autonomy of wireless sensor node by reducing dynamic power dissipation. Simulation with the application of hazardous gas detection using Capnet-PE tool indicates significant energy-saving, which allows us to evaluate and validate our approach for WSN

How to stretch system reliability exploiting mission constraints: A practical roadmap for industries

Reliability analysis can be committed to companies by customers willing to verify whether their products comply with the major international standards or simply to verify the design prior of market deployment. Nevertheless, these analyses may be required at the very preliminary stages of design or when the design is already in progress due to low organizational capabilities or simple delay in the project implementation process. The results sometime maybe be far from the market or customer target with a subsequent need to redesign the whole asset. Of course, not all the cases fall in the worst scenario and maybe with some additional consideration on mission definition it is possible to comply with the proposed reliability targets. In this paper the author will provide an overview on the approach which could be followed to achieve the reliability target even when the project is still on-going providing a practical case study

A cross-platform OpenVX library for FPGA accelerators

FPGAs are an excellent platform to implement computer vision applications, since these applications tend to offer a high level of parallelism with many data-independent operations. However, the freedom in the solution design space of FPGAs represents a problem because each solution must be individually designed, verified, and tuned. The emergence of High Level Synthesis (HLS) helps solving this problem and has allowed the implementation of open programming standards as OpenVX for computer vision applications on FPGAs, such as the HiF1ipVX library developed exclusively for Xilinx devices. Although with the HiF1ipVX library, designers can develop solutions efficiently on Xilinx, they do not have an approach to port and run their code on FPGAs from other manufacturers. This work extends the HiFlipVX capabilities in two significant ways: supporting Intel FPGA devices and enabling execution on discrete FPGA accelerators. To provide both without affecting user-facing code, the new carried out implementation combines two HLS programming models: C++, using Intel''s system of tasks, and OpenCL, which provides the CPU interoperability. Comparing with pure OpenCL implementations, this work reduces kernel dispatch resources, saving up to 24% of ALUT resources for each kernel in a graph, and improves performance 2.6 x and energy consumption 1.6 x on average for a set of representative applications, compared with state-of-the-art frameworks

Cognitive Radio Programming: Existing Solutions and Open Issues

Software defined radio (sdr) technology has evolved rapidly and is now reaching market maturity, providing solutions for cognitive radio applications. Still, a lot of issues have yet to be studied. In this paper, we highlight the constraints imposed by recent radio protocols and we present current architectures and solutions for programming sdr. We also list the challenges to overcome in order to reach mastery of future cognitive radios systems.La radio logicielle a évolué rapidement pour atteindre la maturité nécessaire pour être mise sur le marché, offrant de nouvelles solutions pour les applications de radio cognitive. Cependant, beaucoup de problèmes restent à étudier. Dans ce papier, nous présentons les contraintes imposées par les nouveaux protocoles radios, les architectures matérielles existantes ainsi que les solutions pour les programmer. De plus, nous listons les difficultés à surmonter pour maitriser les futurs systèmes de radio cognitive

FPGA-based real-time moving target detection system for unmanned aerial vehicle application

Moving target detection is the most common task for Unmanned Aerial Vehicle (UAV) to find and track object of interest from a bird's eye view in mobile aerial surveillance for civilian applications such as search and rescue operation. The complex detection algorithm can be implemented in a real-time embedded system using Field Programmable Gate Array (FPGA). This paper presents the development of real-time moving target detection System-on-Chip (SoC) using FPGA for deployment on a UAV. The detection algorithm utilizes area-based image registration technique which includes motion estimation and object segmentation processes. The moving target detection system has been prototyped on a low-cost Terasic DE2-115 board mounted with TRDB-D5M camera. The system consists of Nios II processor and stream-oriented dedicated hardware accelerators running at 100 MHz clock rate, achieving 30-frame per second processing speed for 640 × 480 pixels' resolution greyscale videos

A Survey of Fault-Tolerance Techniques for Embedded Systems from the Perspective of Power, Energy, and Thermal Issues

The relentless technology scaling has provided a significant increase in processor performance, but on the other hand, it has led to adverse impacts on system reliability. In particular, technology scaling increases the processor susceptibility to radiation-induced transient faults. Moreover, technology scaling with the discontinuation of Dennard scaling increases the power densities, thereby temperatures, on the chip. High temperature, in turn, accelerates transistor aging mechanisms, which may ultimately lead to permanent faults on the chip. To assure a reliable system operation, despite these potential reliability concerns, fault-tolerance techniques have emerged. Specifically, fault-tolerance techniques employ some kind of redundancies to satisfy specific reliability requirements. However, the integration of fault-tolerance techniques into real-time embedded systems complicates preserving timing constraints. As a remedy, many task mapping/scheduling policies have been proposed to consider the integration of fault-tolerance techniques and enforce both timing and reliability guarantees for real-time embedded systems. More advanced techniques aim additionally at minimizing power and energy while at the same time satisfying timing and reliability constraints. Recently, some scheduling techniques have started to tackle a new challenge, which is the temperature increase induced by employing fault-tolerance techniques. These emerging techniques aim at satisfying temperature constraints besides timing and reliability constraints. This paper provides an in-depth survey of the emerging research efforts that exploit fault-tolerance techniques while considering timing, power/energy, and temperature from the real-time embedded systems’ design perspective. In particular, the task mapping/scheduling policies for fault-tolerance real-time embedded systems are reviewed and classified according to their considered goals and constraints. Moreover, the employed fault-tolerance techniques, application models, and hardware models are considered as additional dimensions of the presented classification. Lastly, this survey gives deep insights into the main achievements and shortcomings of the existing approaches and highlights the most promising ones

A PUF-and biometric-based lightweight hardware solution to increase security at sensor nodes

Security is essential in sensor nodes which acquire and transmit sensitive data. However, the constraints of processing, memory and power consumption are very high in these nodes. Cryptographic algorithms based on symmetric key are very suitable for them. The drawback is that secure storage of secret keys is required. In this work, a low-cost solution is presented to obfuscate secret keys with Physically Unclonable Functions (PUFs), which exploit the hardware identity of the node. In addition, a lightweight fingerprint recognition solution is proposed, which can be implemented in low-cost sensor nodes. Since biometric data of individuals are sensitive, they are also obfuscated with PUFs. Both solutions allow authenticating the origin of the sensed data with a proposed dual-factor authentication protocol. One factor is the unique physical identity of the trusted sensor node that measures them. The other factor is the physical presence of the legitimate individual in charge of authorizing their transmission. Experimental results are included to prove how the proposed PUF-based solution can be implemented with the SRAMs of commercial Bluetooth Low Energy (BLE) chips which belong to the communication module of the sensor node. Implementation results show how the proposed fingerprint recognition based on the novel texture-based feature named QFingerMap16 (QFM) can be implemented fully inside a low-cost sensor node. Robustness, security and privacy issues at the proposed sensor nodes are discussed and analyzed with experimental results from PUFs and fingerprints taken from public and standard databases.Ministerio de Economía, Industria y Competitividad TEC2014-57971-R, TEC2017-83557-