Related papers: Application of FPGA Acceleration in ADC Performanc…
Due to the emergence of embedded applications in image and video processing, communication and cryptography, improvement of pictorial information for better human perception like deblurring, denoising in several fields such as satellite…
Recent researches on neural network have shown significant advantage in machine learning over traditional algorithms based on handcrafted features and models. Neural network is now widely adopted in regions like image, speech and video…
In this work we evaluate the potential of FPGAs for accelerating HPC workloads as a more power-efficient alternative to GPUs. Using High-Level Synthesis and a large set of optimization techniques, we show that FPGAs can achieve better…
Pipelined analog-to-digital converters (ADCs) are fundamental components of various signal processing systems requiring high sampling rates and a high linearity. Over the past years, calibration techniques have been intensively investigated…
High Performance Computing (HPC) platforms allow scientists to model computationally intensive algorithms. HPC clusters increasingly use General-Purpose Graphics Processing Units (GPGPUs) as accelerators; FPGAs provide an attractive…
In this paper, we describe the algorithms we implemented in FDPS to make efficient use of accelerator hardware such as GPGPUs. We have developed FDPS to make it possible for many researchers to develop their own high-performance parallel…
Most modern computing tasks have digital electronic input and output data. Due to these constraints imposed by real-world use cases of computer systems, any analog computing accelerator, whether analog electronic or optical, must perform an…
With their widespread availability, FPGA-based accelerators cards have become an alternative to GPUs and CPUs to accelerate computing in applications with certain requirements (like energy efficiency) or properties (like fixed-point…
FPGAs are increasingly utilized in data centers due to their capacity to exploit data parallelism in computationally intensive workloads. Furthermore, the processing of modern data center workloads requires moving vast amounts of data,…
Inspired by Wilkinson ADC method, we implement a fast linear discharge method based on FPGA to digitize nuclear pulse signal. In this scheme, we use a constant current source to discharge the charge on capacitor which is integrated by the…
In this paper, a real-time 105-channel data acquisition platform based on FPGA for imaging will be implemented for mm-wave imaging systems. PC platform is also realized for imaging results monitoring purpose. Mm-wave imaging expands our…
The large growth of flash ADC techniques for processing signals, especially in applications of streaming data, raises issues such as data flow through an acquisition system, long-term storage, and greater complexity in data analysis. In…
High sampling speed can be achieved using multiple Analog-to-Digital Converters (ADCs) based on the Time-Interleaving A/D Conversion (TIADC) technique. Various types of methods were proposed to correct the mismatch errors among parallel ADC…
Recent trends in business and technology (e.g., machine learning, social network analysis) benefit from storing and processing growing amounts of graph-structured data in databases and data science platforms. FPGAs as accelerators for graph…
Cyclostationary analysis is widely used in signal processing, particularly in the analysis of human-made signals, and spectral correlation density (SCD) is often used to characterise cyclostationarity. Unfortunately, for real-time…
In this study, a novel type of Fourier transform radio spectrometer (termed as all-digital radio spectrometer; ADRS) has been developed in which all functionalities comprising a radio spectrometer including a sampler and Fourier computing…
With the advent of the 5G wireless networks, achieving tens of gigabits per second throughputs and low, milliseconds, latency has become a reality. This level of performance will fuel numerous real-time applications, such as autonomy and…
FPGA is appropriate for fix-point neural networks computing due to high power efficiency and configurability. However, its design must be intensively refined to achieve high performance using limited hardware resources. We present an…
As the development of electronic science and technology, electronic data acquisition (DAQ) system is more and more widely applied to nuclear physics experiments. Workstations are often utilized for data storage, data display, data…
Hardware acceleration has emerged as a key research topic for supporting computationally intensive signal processing and artificial intelligence applications in 6G research and development studies. This paper presents an RF Network on Chip…