Field Programmable Gate Array Fabric Research Articles

FPGA Correlator for Applications in Embedded Smart Devices.

Correlation has a variety of applications that require signal processing. However, it is computationally intensive, and software correlators require high-performance processors for real-time data analysis. This is a challenge for embedded devices because of the limitation of computing resources. Hardware correlators that use Field Programmable Gate Array (FPGA) technology can significantly boost computational power and bridge the gap between the need for high-performance computing and the limited processing power available in embedded devices. This paper presents a detailed FPGA-based correlator design at the register level along with the open-source Very High-Speed Integrated Circuit Hardware Description Language (VHDL) code. It includes base modules for linear and multi-tau correlators of varying sizes. Every module implements a simple and unified data interface for easy integration with standard and publicly available FPGA modules. Eighty-lag linear and multi-tau correlators were built for validation of the design. Three input data sets—constant signal, pulse signal, and sine signal—were used to test the accuracy of the correlators. The results from the FPGA correlators were compared against the outputs of equivalent software correlators and validated with the corresponding theoretical values. The FPGA correlators returned results identical to those from the software references for all tested data sets and were proven to be equivalent to their software counterparts. Their computation speed is at least 85,000 times faster than the software correlators running on a Xilinx MicroBlaze processor. The FPGA correlator can be easily implemented, especially on System on a Chip (SoC) integrated circuits that have processor cores and FPGA fabric. It is the ideal component for device-on-chip solutions in biosensing.

The Wave-Union Method on DSP Blocks: Improving FPGA-Based TDC Resolutions by 3x With a 1.5x Area Increase

Achieving high-resolution time-to-digital conversion is challenging at high count rates. In past work, the highest resolutions with low dead times (≤2 cycles) on field-programmable gate arrays (FPGAs) have been achieved using digital signal processing (DSP) blocks or using the wave-union method. In this article, we investigate the possibility of combining the wave-union method with DSP blocks. With the given configuration on a Xilinx Artix-7 200T FPGA, we achieve 13.60-ps single-shot precision (SSP) using only 3.78% of the FPGA fabric per channel (1.22% of the fabric in the finite step response (FSR) injector and 2.56% of the fabric in the delay line) for three edges, compared to 52.65 ps using 2.97% of the FPGA fabric per channel without the wave-union method. The scaling of edge numbers (for higher resolutions) is shown to be significantly better than the previously suggested parallel implementation, at just 0.407% of the FPGA fabric per edge compared to ~2.5% per edge in the parallel implementation. Temperature characterization showed an SSP penalty of just 4 ps over a 60 °C temperature difference.

MC-DeF

Executing complex scientific applications on Coarse-Grain Reconfigurable Arrays ( CGRAs ) promises improvements in execution time and/or energy consumption compared to optimized software implementations or even fully customized hardware solutions. Typical CGRA architectures contain of multiple instances of the same compute module that consist of simple and general hardware units such as ALUs, simple processors. However, generality in the cell contents, while convenient for serving a wide variety of applications, penalizes performance and energy efficiency. To that end, a few proposed CGRAs use custom logic tailored to a particular application’s specific characteristics in the compute module. This approach, while much more efficient, restricts the versatility of the array. To date, versatility at hardware speeds is only supported with Field programmable gate arrays (FPGAs), that are reconfigurable at a very fine grain. This work proposes MC-DeF, a novel Mixed-CGRA Definition Framework targeting a Mixed-CGRA architecture that leverages the advantages of CGRAs by utilizing a customized cell array, and those of FPGAs by incorporating a separate LUT array used for adaptability. The framework presented aims to develop a complete CGRA architecture. First, a cell structure and functionality definition phase creates highly customized application/domain specific CGRA cells. Then, mapping and routing phases define the CGRA connectivity and cell-LUT array transactions. Finally, an energy and area estimation phase presents the user with area occupancy and energy consumption estimations of the final design. MC-DeF uses novel algorithms and cost functions driven by user defined metrics, threshold values, and area/energy restrictions. The benefits of our framework, besides creating fast and efficient CGRA designs, include design space exploration capabilities offered to the user. The validity of the presented framework is demonstrated by evaluating and creating CGRA designs of nine applications. Additionally, we provide comparisons of MC-DeF with state-of-the-art related works, and show that MC-DeF offers competitive performance (in terms of internal bandwidth and processing throughput) even compared against much larger designs, and requires fewer physical resources to achieve this level of performance. Finally, MC-DeF is able to better utilize the underlying FPGA fabric and achieves the best efficiency (measured in LUT/GOPs).

System-on-Chip FPGA Devices for Complex Electrical Energy Systems Control

Digital electronics has become a standard for controlling electrical systems. This is due to the constant improvement of the digital devices, whether in terms of density, performance, flexibility of use, or cost reduction <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> . This article looks into system-on-chip (SoC) field-programmable gate array (FPGA) for controlling complex electrical energy systems. These devices encompass multicore floating-point microprocessors embedded with standard peripherals and an FPGA fabric that allows the design of custom peripherals and specific hardware (HW) accelerators. Thus, SoC FPGA devices can be regarded as a good compromise between “super” microcontrollers (very fast in terms of computation but with a fixed microarchitecture) and pure FPGAs (ideal for specific concurrent microarchitectures but limited in terms of density).

Fine resolution delay tuning method to improve the linearity of an unbalanced time‐to‐digital converter on a Xilinx FPGA

In this study, a method for fine adjustment of Xilinx field programmable gate array (FPGA) routing delays is proposed and applied to improve the linearity of an unbalanced multi-measurement time-to-digital converter (TDC). The delay control method increases load capacitances of interconnect points of switch matrices by small amounts using additional connections to unused interconnects in the FPGA fabric. The novel delay control method uses the tool command language (TCL) scripting feature available in the Xilinx Vivado tool to automatically add wires into a fully placed and routed design. A total of 61 additional wires were successfully and automatically added to reduce the differential and integral non-linearities of the target TDC from 0.51 and −0.54 LSB to 0.05 and 0.06 LSB, respectively (reduction factors of 10.2 and 9) for an LSB equal to 333 ps.

High-Performance COTS FPGA SoC for Parallel Hyperspectral Image Compression With CCSDS-123.0-B-1

Nowadays, hyperspectral imaging is recognized as a cornerstone remote sensing technology. Next generation, high-speed airborne, and space-borne imagers have increased resolution, resulting in an explosive growth in data volume and instrument data rate in the range of gigapixel per second. This competes with limited on-board resources and bandwidth, making hyperspectral image compression a mission critical on-board processing task. At the same time, the “new space” trend is emerging, where launch costs decrease, and agile approaches are exploited building smallsats using commercial-off-the-shelf (COTS) parts. In this contribution, we introduce a high-performance parallel implementation of the CCSDS-123.0-B-1 hyperspectral compression algorithm targeting SRAM field-programmable gate array (FPGA) technology. The architecture exploits image segmentation to provide the robustness to data corruption and enables scalable throughput performance by leveraging segment-level parallelism. Furthermore, we exploit the capabilities of a COTS FPGA system-on-chip (SoC) device to optimize size, weight, power, and cost (SWaP-C). The architecture partitions a hyperspectral cube stored in a DRAM framebuffer into segments, compressing them in parallel using a flexible software scheduler hosted in the SoC CPU and several compressor accelerator cores in the FPGA fabric. A 5-core implementation demonstrated on a Zynq-7045 FPGA achieves a throughput performance of 1387 Msamples/s [22.2 Gb/s at 16 bits per pixel per band (bpppb)] and outperforms previous implementations in equivalent FPGA technology, allowing seamless integration with next-generation hyperspectral sensors.

CPAmap: On the Complexity of Secure FPGA Virtualization, Multi-Tenancy, and Physical Design

With virtualized Field Programmable Gate Arrays (FPGAs) on the verge of being deployed to the cloud computing domain, there is a rising interest in resolving recently identified security issues. Those issues result from different trusted and untrusted entities sharing the FPGA fabric and the Power Distribution Network. Researchers were able to perform both side-channel and fault attacks between logically isolated designs on the same FPGA fabric, compromising security of cryptographic modules and other critical implementations. Side-channel attacks specifically are enabled by the vast degree of freedom given to developers when making use of the basic FPGA resources. Both ring oscillators as well as long delay lines, implemented using low-level FPGA primitives, have been shown to provide sufficient data for simple or correlation-based power analysis attacks. In order to develop new or apply known countermeasures onto designs and implementations in a virtualized multi-tenant FPGA, we seek to fully understand the underlying mechanisms and dependencies of chip-internal side-channel attacks. Although the impact of process variation and other physical design parameters on side-channel vulnerability has been investigated in previous works, remote attacks between logically isolated partitions in multi-tenant FPGAs introduce new and unique challenges. Thus, we systematically analyze the impact of physical mapping of both attacker and victim design on the success of correlation power analysis attacks on the Advanced Encryption Standard (AES). We report our findings on a Xilinx Zynq 7000-based platform, which show that the effect of global and local placement as well as routing and process variation on the success of side-channel attacks almost exceeds the impact of hiding countermeasures. This result reveals fundamental challenges in secure virtualization of FPGAs, which have been mostly ignored so far. Eventually, our results may also help vendors and hypervisors in developing zero overhead side-channel countermeasures based on adequate global and local placement of isolated designs on a multi-tenant FPGA.

Dynamic power-aware scheduling of real-time tasks for FPGA-based cyber physical systems against power draining hardware trojan attacks

The present era has witnessed deployment of reconfigurable hardware or field-programmable gate arrays (FPGAs) in diverse domains like automation and avionics, which are cyber physical in nature. Such cyber physical systems are associated with strict power budgets. Efficient real-time task-scheduling strategies exist that ensure execution of maximum number of tasks within the power budget. However, these do not consider hardware threats into account. Recent literature has exposed the existence of hardware trojan horses (HTHs). HTHs are malicious circuitry that remain dormant during testing and evade detection, but get activated at runtime to jeopardize operations. HTHs can be etched into the FPGA fabric by adversaries in the untrustworthy foundries, during fabrication of the FPGAs. Even vendors selling reconfigurable intellectual properties or bitstreams that configure the FPGA fabric for task operation may insert HTHs during writing the bitstream codes. HTHs may cause a variety of attacks which may affect the basic security primitives of the system like its integrity, confidentiality or availability. In this work, we explore how power draining ability of HTHs may reduce lifetime of the system. A self-aware approach is also proposed which detects the affected resources of the system and eradicates their use in future to facilitate system reliability. An offline–online scheduling strategy is proposed for periodic tasks which can ensure reliability of their operations till the expected lifetime of the system. Accommodating non-periodic tasks in the periodic task schedule based on available power is also focused. For experimentation, we consider tasks associated with EPFL benchmarks and demonstrate results based on the metric task success rate for periodic tasks and metric task rejection rate for non-periodic tasks.

Real-time audio signal processing using system-on-chip field programmable gate arrays

System-on-Chip (SoC) Field Programmable Gate Arrays (FPGAs) are ideal for real-time signal processing due to their low, deterministic latency and high performance. To showcase the utility of our open FPGA computational platform for real-time audio signal processing and computational modeling, several applications have been implemented. We have ported the openMHA hearing aid software [1] to our platform to show that pre-existing audio processing software can be implemented in SoC FPGAs by making external audio interfaces show up as a sound card. To highlight the ability to perform real-time computational modeling on our performance platform, we are implementing a real-time version of Laurel Carney’s auditory-nerve model [2] running in its own custom accelerator in the FPGA fabric. To illustrate the ability to develop DSP algorithms in MathWork’s Simulink and then implement them in the FPGA fabric we have taken several algorithms from Issa Panahi’s group [3] to show both frame-based processing (noise reduction) and sample-based processing (dynamic range compression). Finally, we show that the platform can be used to visualize audio signals using a real-time spectrogram where FFTs are computed in the FPGA fabric. [1] www.openmha.org. [2] JASA 126, 2390–2412. [3] www.utdallas.edu/ssprl/hearing-aid-project/.

Scaling Up Modulo Scheduling for High-Level Synthesis

High-level synthesis (HLS) tools have been increasingly used within the hardware design community to bridge the gap between productivity and the need to design large and complex systems. When targeting heterogeneous systems, where the CPU and the field-programmable gate array (FPGA) fabric are both available to perform computations, a design space exploration (DSE) is usually carried out for deciding which parts of the initial code should be mapped to the FPGA fabric such as the overall system’s performance is enhanced by accelerating its computation via dedicated processors. As the targeted systems become more complex and larger, leading to a large DSE, the fast estimative of the possible acceleration that can be obtained by mapping certain functionality into the FPGA fabric is of paramount importance. Loop pipelining, which is responsible for the majority of HLS compilation time, is a key optimization toward achieving high-performance acceleration kernels. A new modulo scheduling algorithm is proposed, which reformulates the classical modulo scheduling problem and leads to a reduced number of integer linear problems solved, resulting in large computational savings. Moreover, the proposed approach has a controlled tradeoff between solution quality and computation time. Results show the scalability is improved efficiently from quadratic, for the state-of-the-art method, to linear, for the proposed approach, while the optimized loop suffers a 1% (geomean) increment in the total number of cycles.

Oscillator without a combinatorial loop and its threat to FPGA in data centre

Virtual field-programmable gate array (FPGA) is an emerging technology to put multiple users in the same FPGA fabric with logical isolation. Security researchers have studied new threats in virtual FPGA and proposed attacks on the logical isolation by exploiting analogue natures of FPGA. These attacks use an oscillator comprising a combinatorial loop to have access to the analogue domain using digital components only. Interestingly, the system in the field prohibits a combinatorial loop by a design rule check. In this Letter, the authors study if prohibiting a combinatorial loop is sufficient to thwart the conventional attacks. They negatively answer the question by showing oscillators without a combinatorial loop. They also show how to detect and reject the proposed oscillators by a design rule check.

SoC implementation of a photovoltaic reconfiguration algorithm by exploiting a HLS-based architecture

The dynamic reconfiguration of photovoltaic arrays is a promising technique for reducing the power drops due to partial shadowing. Some approaches for determining the optimal electrical configuration of the photovoltaic array have been presented in literature. The most encouraging solution is based on the use of stochastic algorithms that can be fruitfully implemented in a system on chip. The computation time takes profit from the available field programmable gate array fabric, where multiple instances of the fitness function can be run in parallel. The use of Vivado High Level Synthesis, to create a Register Transfer Level implementation from C/C++ sources, allows achieving satisfactory results. Coding the algorithm by taking into account the synthesis process, thus resource allocation, scheduling and binding, helps in obtaining a further performance improvement. In this paper a High Level Synthesis approach is used for the systematic exploration of the possible architectures that can be used for implementing the reconfiguration algorithm. Some solutions that differ in terms of computation time and hardware resources used are compared. The target system on chip is a low cost one from Xilinx.

An autonomous, highly portable NMR spectrometer based on a low-cost System-on-Chip (SoC).

This paper describes the development of a portable and self-optimizing NMR spectrometer based on a miniaturized custom analog front-end and a System-on-Chip (SoC)-based digital back-end. The SoC integrates a field-programmable gate array (FPGA) fabric with a hard processor running a Linux operating system, thus enabling fully-autonomous operation without the need for an external computer. In the proposed approach, data captured by the FPGA fabric during regular operation is transported to the hard processor using an integrated on-chip bus for further processing. The processed results are then used to automatically estimate parameter values that optimize a suitable cost function, such as signal-to-noise ratio (SNR) per unit time. Finally, the optimized values of both electrical and NMR-related tuning parameters (e.g., preamplifier gain and frequency response, pulse length and amplitude, operating frequency, etc.) are programmed back into the front-end and back-end hardware. Experimental NMR results from various samples in a ∼0.1 T permanent magnet are presented to verify the operation of the proposed spectrometer. These demonstrate on-board Laplace inversion and automated frequency tuning to compensate for temperature changes. Preliminary 14N NQR results are also presented.

Development of A Low-Cost FPGA-Based Measurement System for Real-Time Processing of Acoustic Emission Data: Proof of Concept Using Control of Pulsed Laser Ablation in Liquids.

Today, the demand for continuous monitoring of valuable or safety critical equipment is increasing in many industrial applications due to safety and economical requirements. Therefore, reliable in-situ measurement techniques are required for instance in Structural Health Monitoring (SHM) as well as process monitoring and control. Here, current challenges are related to the processing of sensor data with a high data rate and low latency. In particular, measurement and analyses of Acoustic Emission (AE) are widely used for passive, in-situ inspection. Advantages of AE are related to its sensitivity to different micro-mechanical mechanisms on the material level. However, online processing of AE waveforms is computationally demanding. The related equipment is typically bulky, expensive, and not well suited for permanent installation. The contribution of this paper is the development of a Field Programmable Gate Array (FPGA)-based measurement system using ZedBoard devlopment kit with Zynq-7000 system on chip for embedded implementation of suitable online processing algorithms. This platform comprises a dual-core Advanced Reduced Instruction Set Computer Machine (ARM) architecture running a Linux operating system and FPGA fabric. A FPGA-based hardware implementation of the discrete wavelet transform is realized to accelerate processing the AE measurements. Key features of the system are low cost, small form factor, and low energy consumption, which makes it suitable to serve as field-deployed measurement and control device. For verification of the functionality, a novel automatically realized adjustment of the working distance during pulsed laser ablation in liquids is established as an example. A sample rate of 5 MHz is achieved at 16 bit resolution.

NoC-DPR: A new simulation tool exploiting the Dynamic Partial Reconfiguration (DPR) on Network-on-Chip (NoC) based FPGA

Due to the ability of Dynamic Partial Reconfiguration (DPR) of SRAM-based Field Programmable Gate Arrays (FPGAs) to add more flexibility over runtime phase, DPR is attracting more interest. Recently, FPGA manufacturers are facilitating the design of applications that utilize DPR. One of the main issues in our knowledge of DPR's current techniques (i.e., ICAP and JTAG) is a performance bottleneck; only one DPR is allowed at a time. In this paper, a state-of-art NoC-based FPGA simulator which supports DPR simulation is proposed. The proposed NoC-DPR simulator is used to investigate design limitations and performance degradation of using DPR on NoC-based FPGA. To estimate the reconfiguration time overhead, which results from increasing the number of simultaneous DPRs on FPGA fabric, some experimental investigations are carried out using NoC-DPR simulator. These investigations revealed that the overhead of reconfiguration time increases exponentially with increasing the number of simultaneous DPRs. However, further investigations show that the network of wormhole routers with virtual channels optimizes the reconfiguration time with a factor up to 4x than that of the network of wormhole routers without virtual channels.

Superconducting Magnetic Field Programmable Gate Array

Field-programmable gate arrays (FPGAs) provide a significantly cheaper solution for various applications in traditional semiconductor electronics. Single flux quantum (SFQ) technologies are developing rapidly and the availability of SFQ-specific FPGA will be very useful. Towards developing such an SFQ-specific FPGA, new designs of FPGA subcircuits for both synchronous and asynchronous operation of SFQ circuits are presented in this paper. Magnetic Josephson junctions (MJJs) are used as bias limiting junctions in energy-efficient rapid SFQ (ERSFQ) biasing to implement programmable switches in various subcircuits of the proposed FPGA fabric. Designs of all FPGA subcircuits are developed and are verified through circuit simulation. Verilog hardware description language (HDL) models are also developed for all FPGA circuit blocks to facilitate large-scale FPGA simulations for the implementation of the desired circuit on the proposed FPGA fabric. Designs of a few subcircuits with switches based on nondestructive readout cell are also given in the current paper for better comparison with MJJ switch based counterparts. Programming of MJJ-based switches is based on the ability to control the critical current of MJJs externally. Recent implementations of SFQ decoder is proposed for accessing individual MJJs through the current lines in a crossbar structure. Estimations for the area and power consumption are much better in comparison to previous attempts at designing an SFQ specific FPGA.

An FPGA-Based Phase Measurement System

Phase measurement is required in electronic applications where a synchronous relationship between the signals needs to be preserved. Traditional electronic systems used for time measurement are designed using a classical mixed-signal approach. With the advent of reconfigurable hardware such as field-programmable gate arrays (FPGAs), it is more advantageous for designers to opt for all-digital architecture. Most high-speed serial transceivers of the FPGA circuitry do not ensure the same chip latency after each power cycle, reset cycle, or firmware upgrade. These cause uncertainty of phase relationship between the recovered signals. To address the need to register minute phase shift changes inside an FPGA, we propose a design for phase measurement logic core having resolution and precision in the range of a few picoseconds. The working principle is based on subsample accumulation using systematic sampling over the phase detector signal. The phase measurement logic can operate over a wide range of digital clock frequencies, ranging from a few kilohertz to the maximum frequency that is supported within the FPGA fabric. A mathematical model is developed to illustrate the operating principle of the design. The VLSI architecture is designed for the logic core. We also discussed the procedure of the phase measurement system, the calibration sequence involved, followed by the performance of the design in terms of accuracy, precision, and resolution.

Design techniques for a stable operation of cryogenic field-programmable gate arrays.

In this paper, we show how a deep-submicron field-programmable gate array (FPGA) can be operated more stably at extremely low temperatures through special firmware design techniques. Stability at low temperatures is limited through long power supply wires and reduced performance of various printed circuit board components commonly employed at room temperature. Extensive characterization of these components shows that the majority of decoupling capacitor types and voltage regulators are not well behaved at cryogenic temperatures, asking for an ad hoc solution to stabilize the FPGA supply voltage, especially for sensitive applications. Therefore, we have designed a firmware that enforces a constant power consumption, so as to stabilize the supply voltage in the interior of the FPGA. The FPGA is powered with a supply at several meters distance, causing significant resistive voltage drop and thus fluctuations on the local supply voltage. To achieve the stabilization, the variation in digital logic speed, which directly corresponds to changes in supply voltage, is constantly measured and corrected for through a tunable oscillator farm, implemented on the FPGA. The impact of the stabilization technique is demonstrated together with a reconfigurable analog-to-digital converter (ADC), completely implemented in the FPGA fabric and operating at 15 K. The ADC performance can be improved by at most 1.5 bits (effective number of bits) thanks to the more stable supply voltage. The method is versatile and robust, enabling seamless porting to other FPGA families and configurations.

FPGAs: Fundamentals, Advanced Features, and Applications in Industrial Electronics [Book News

This book presents all the facets of today’s field-programmable gate array (FPGA) technology. The aim of the authors is to offer engineers and, more generally, readers who have experience in industrial electronics a good understanding of both the basics and the latest trends related to FPGAs. This task is not easy because, since their creation 30 years ago, FPGAs have always been at the edge of innovation in the field of digital electronics, and, as a consequence, they are constantly evolving. This is all the more true because, over the last five years, a deep technological mutation has affected the world of FPGAs, shifting them from the well-known regular FPGA fabric to field-programmable systems on chips that, apart from the standard FPGA fabric, also include multiprocessor cores with their ecosystem. Thus, with the great diversity of possibilities offered by this new generation of devices, the risk to both the software engineer and the hardware designer is high if they are not able to find good documents that will help them demystify the part of the component with which they are not familiar. Having clearly identified this risk, the great merit of this book is to expose, in a simple way but with rigor, all the complexity and diversity of the latest generation of FPGAs. Readers will be able to better understand why such devices can fulfill the forthcoming challenges in terms of complexity for the next generation of industrial control systems. In today’s FPGAs, one can program at the same time powerful processor cores and design application-specific hardware accelerators in the FPGA fabric.

Design and Applications for Embedded Networks-on-Chip on FPGAs

Field-programmable gate-arrays (FPGAs) have evolved to include embedded memory, high-speed I/O interfaces and processors, making them both more efficient and easier-to-use for compute acceleration and networking applications. However, implementing on-chip communication is still a designer’s burden wherein custom system-level buses are implemented using the fine-grained FPGA logic and interconnect fabric. Instead, we propose augmenting FPGAs with an embedded network-on-chip (NoC) to implement system-level communication. We design custom interfaces to connect a packet-switched NoC to the FPGA fabric and I/Os in a configurable and efficient way and then define the necessary conditions to implement common FPGA design styles with an embedded NoC. Four application case studies highlight the advantages of using an embedded NoC. We show that access latency to external memory can be $\sim$ 1.5 $\times$ lower. Our application case study with image compression shows that an embedded NoC improves frequency by 10-80%, reduces utilization of scarce long wires by 40% and makes design easier and more predictable. Additionally, we leverage the embedded NoC in creating a programmable Ethernet switch that can support up to 819 Gb/s-5 $\times$ more switching bandwidth and 3 $\times$ lower area compared to previous work. Finally, we design a 400 Gb/s NoC-based packet processor that is very flexible and more efficient than other FPGA-based packet processors.