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

This paper aims to better understand the performance differences between FPGAs and
GPUs. We intentionally begin with a widely used GPU-friendly benchmark suite, Rodinia …

Stencil computation is one of the most important kernels in many application domains such
as image processing, solving partial differential equations, and cellular automata. Many of …

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

Embedded inference engines for convolutional networks must be parsimonious in memory
bandwidth and buffer sizing to meet power and cost constraints. We present an analytical …

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 demise of Moore's Law and Dennard Scaling has revived interest in specialized
computer architectures and accelerators. Verification and testing of this hardware depend …

After the introduction of the OpenCL-based FPGA accelerator design method, FPGAs are
getting very popular among high-performance computing. The key to achieving high …

Stencil-based algorithms are a relevant class of computational kernels in high-performance
systems, as they appear in a plethora of fields, from image processing to seismic …

In high-performance systems, stencil computations play a crucial role as they appear in a
variety of different fields of application, ranging from partial differential equation solving, to …