FPGA-based accelerators are increasingly popular across a broad range of applications,
because they offer massive parallelism, high energy efficiency, and great flexibility for …

Cloud vendors are actively adopting FPGAs into their infrastructures for enhancing
performance and efficiency. As cloud services continue to evolve, FPGA (field …

Three-dimensional convolutional neural networks (3D CNNs) are used efficiently in many
computer vision applications. Most previous work in this area has concentrated only on …

FPGAs are more and more widely used as reconfigurable hardware accelerators for
applications leveraging convolutional neural networks (CNNs) in recent years. Previous …

CPU-FPGA heterogeneous architectures feature flexible acceleration of many workloads to
advance computational capabilities and energy efficiency in today's datacenters. This …

Large-scale sorting is always an important yet demanding task for data center applications.
In addition to powerful processing capability, high-performance sorting system requires …

Hardware accelerators are key to the efficiency and performance of system-on-chip (SoC)
architectures. With high-level synthesis (HLS), designers can easily obtain several …

The k-nearest neighbors (KNN) algorithm is an essential algorithm in many applications,
such as similarity search, image classification, and database query. With the rapid growth in …

In order to further increase the productivity of field-programmable gate array (FPGA)
programmers, several design space exploration (DSE) frameworks for high-level synthesis …

With the public availability of FPGAs from major cloud service providers like AWS, Alibaba,
and Nimbix, hardware and software developers can now easily access FPGA platforms …