Related papers: Fast FPGA emulation of analog dynamics in digitall…
Multipliers are widely-used arithmetic operators in digital signal processing and machine learning circuits. Due to their relatively high complexity, they can have high latency and be a significant source of power consumption. One strategy…
Contemporary field-programmable gate arrays (FPGAs) are predestined for the application of finite impulse response (FIR) filters. Their embedded digital signal processing (DSP) blocks for multiply-accumulate operations enable efficient…
Deep neural network (DNN) inference relies increasingly on specialized hardware for high computational efficiency. This work introduces a field-programmable gate array (FPGA)-based dynamically configurable accelerator featuring systolic…
Analog/mixed-signal circuit design is one of the most complex and time-consuming stages in the whole chip design process. Due to various process, voltage, and temperature (PVT) variations from chip manufacturing, analog circuits inevitably…
The ever-increasing data rates of modern communication systems lead to severe distortions of the communication signal, imposing great challenges to state-of-the-art signal processing algorithms. In this context, neural network (NN)-based…
This paper presents a mixed-signal neuromorphic accelerator architecture designed for accelerating inference with event-based neural network models. This fully CMOS-compatible accelerator utilizes analog computing to emulate synapse and…
In this paper, the acceleration of algorithms using a design of a field programmable gate array (FPGA) as a prototype of a static dataflow architecture is discussed. The static dataflow architecture using operators interconnected by…
With present-day detectors in high energy physics one often faces fast analog pulses of a few nanoseconds length which cover large dynamic ranges. In many experiments both amplitude and timing information have to be measured with high…
Many aerospace and automotive applications use FPGAs in their designs due to their low power and reconfigurability requirements. Meanwhile, such applications also pose a high standard on system reliability, which makes the early-stage…
The rapid advancement of AI workloads and domain-specific architectures has led to increasingly diverse processor microarchitectures, whose design exploration requires fast and accurate performance validation. However, traditional workflows…
In this work, we propose an architecture and methodology to design hardware/software systems for high-performance embedded computing on FPGA. The hardware side is based on a many-core architecture whose design is generated automatically…
Neuromorphic Computing is a nascent research field in which models and devices are designed to process information by emulating biological neural systems. Thanks to their superior energy efficiency, analog neuromorphic systems are highly…
Sensory processing with neuromorphic systems is typically done by using either event-based sensors or translating input signals to spikes before presenting them to the neuromorphic processor. Here, we offer an alternative approach: direct…
Digital twinning enables real-time simulation and predictive modeling by maintaining a continuously updated virtual representation of a physical system. In mission-critical applications, such as mid-air collision avoidance, these models…
Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications. In-memory computing mixed-signal neuromorphic architectures provide promising ultra-low-power…
High parallel framework has been proved to be very suitable for graph processing. There are various work to optimize the implementation in FPGAs, a pipeline parallel device. The key to make use of the parallel performance of FPGAs is to…
We present a tool flow and results for a model-based hardware design for FPGAs from Simulink descriptions which nicely integrates into existing environments. While current commercial tools do not exploit some high-level optimizations, we…
An experimental digital correlated double sampler (DCDS) video processor has been implemented in a Xilinx Artix FPGA. It uses an Opal Kelly XEM7010-A50 module that comes with an integrated USB2 interface for easy interfac-ing to a data…
FPGA overlays are commonly implemented as coarse-grained reconfigurable architectures with a goal to improve designers' productivity through balancing flexibility and ease of configuration of the underlying fabric. To truly facilitate full…
Flexibility and customization are key strengths of Field-Programmable Gate Arrays (FPGAs) when compared to other computing devices. For instance, FPGAs can efficiently implement arbitrary-precision arithmetic operations, and can perform…