BBN Times

FPGA vs. GPU for Deep Learning: Which Hardware Accelerates AI Better?

Deep learning has advanced rapidly, driving breakthroughs in image recognition, natural language processing, and autonomous ...
Tweakers

Microsoft wil deep learning versnellen met fpga's in Brainwave-project

Microsoft heeft in het kader van de Hot Chips-conferentie een project onder de naam Brainwave aangekondigd. Het bedrijf claimt hiermee deep learning met zeer lage latency te kunnen uitvoeren op fpga's ...
Design-Reuse

Floating- to fixed-point MATLAB algorithm conversion for FPGAs

In a recent survey conducted by AccelChip Inc. (recently acquired by Xilinx), 53% of the respondents identified floating- to fixed-point conversion as the most difficult aspect of implementing an ...
Nature

High-Performance Sorting Algorithms and Architectures Using FPGA

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.
Nature

Hardware Architecture for Cryptographic Algorithms on FPGA

Field Programmable Gate Arrays (FPGAs) have emerged as a versatile platform for implementing cryptographic algorithms, offering a balance between flexibility, performance and energy efficiency. Recent ...
Design-Reuse

How to use the CORDIC algorithm in your FPGA design

Most engineers tasked with implementing a mathematical function such as sine, cosine or square root within an FPGA may initially think of doing so by means of a lookup table, possibly combined with ...