The NSF has funded projects that will investigate how deep learning algorithms run on FPGAs and across systems using the high-performance RDMA interconnect. Another project, led by Andrew Ng and ...

Microchip has released a C++ algorithm high-level synthesis design workflow for its PolarFire FPGAs. “A large majority of edge compute, computer vision and industrial control algorithms are developed ...

Yao says “The FPGA based DPU platform achieves an order of magnitude higher energy efficiency over GPU on image recognition and speech detection.” Deephi believes a joint optimization between ...

In this special guest feature from Scientific Computing World, Robert Roe writes that FPGAs provide an early insight into possibile architectural specialization options for HPC and machine learning.

To dramatically simplify the path from image and signal processing algorithms to FPGA implementation, designers should choose an abstract language-based synthesis technology to use the executable ...

CoDeveloper for Virtex-4 allows software programmers and FPGA designers to describe parallel algorithms for image processing, DSP, encryption and other processing-intensive applications using standard ...

Today Intel announced record results on a new benchmark in deep learning and convolutional neural networks (CNN). ZTE’s engineers used Intel’s midrange Arria 10 FPGA for a cloud inferencing ...

Using a design flow put together by Mentor Graphics and Altera, designers can implement complex DSP algorithms in high-performance FPGAs directly from ANSI C++ code. The flow, which is based on ...

Field-programmable gate arrays (FPGAs) offer a unique platform for the implementation of high-performance sorting algorithms by combining inherent parallelism with customisable hardware architectures.

The PROC reconfigurable systems are used to accelerate complex algorithms that include DSP, image processing, national security and other performance critical domains.