EDN

Viewpoint: The importance of FPGA-to-ASIC solutions to accelerate CPU-based protocols

For many years, there has been a running debate about how to best handle the processing of protocols mid-way up the protocol stack in a data networking or enterprise storage application. Oftentimes ...
AV Network

Justin Kennington on AV Supply Chain Using FPGA vs. ASIC Chips

SDVoE Alliance President, Justin Kennington shares his perspective on how FPGA versus ASIC chips impacts the product supply chain in the AV industry. When you purchase through links on our site, we ...
EDN

FPGA-to-ASIC integration provides flexibility in automotive microcontrollers

The widely applied microcontroller in automotive electronics is heading full-speed at a wall of time and cost. The primary benefit of using microcontrollers (MCUs) has been high level system ...
Semiconductor Engineering

FPGA Graduates To First-Tier Status

Robert Blake, president and CEO of Achronix, sat down with Semiconductor Engineering to talk about fundamental shifts in compute architectures and why AI, machine learning and various vertical ...
The Next Platform

Supercomputer Mixes Streams with CPU, GPU, and FPGA

If this is truly the age of heterogeneous supercomputers, then the system installed earlier this month at the University of Tsukuba is its poster child. The new NEC-built machine, which is now up and ...
Forbes

An Overview Of Mining: CPU, GPU And ASIC

A blockchain is a decentralized database of transactions that everyone on the network can see. The network consists of many computers that verify transactions and add them to the blockchain ledger; ...
TweakTown

Ubitium announces 'universal processor': combines CPU, GPU, DSP, FPGA in a single RISC-V chip

TL;DR: Ubitium is developing a Universal Processor that combines CPU, GPU, DSP, and FPGA into a single chip, aiming to revolutionize the market by reusing every transistor for multiple functions.
TechSpot

Startup's Universal Processor combines CPU, GPU, DSP, and FPGA into a single chip

Why it matters: Devices like smartphones rely on a fragmented array of CPUs, GPUs, NPUs, DSPs, and other accelerators to handle various tasks. However, these specialized cores often remain idle, ...
Semiconductor Engineering

Deep Learning Hardware: FPGA vs. GPU

FPGAs or GPUs, that is the question. Since the popularity of using machine learning algorithms to extract and process the information from raw data, it has been a race between FPGA and GPU vendors to ...
insideHPC

Unified Deep Learning with CPU, GPU and FPGA Technologies

Deep learning and complex machine learning has quickly become one of the most important computationally intensive applications for a wide variety of fields. The combination of large data sets, ...
Forbes

Why NVIDIA Is Building Its Own TPU

The blistering pace of innovation in artificial intelligence for image, voice, robotic and self-driving vehicle applications has been fueled, in large part, by NVIDIA ’s GPU chips that deliver the ...