Machine Learning and the Store of the Future

CATEGORIES : deep learning/AUTHOR : Ron Wilson

What is the future of bricks-and-mortar retail? Imagine, if you will, two scenarios. In one scenario, shopping malls, main-street stores, and even big-box stores slip into a downward spiral. Customers shop online, starving brick-and-mortar stores of revenue. The stores cut staff, inventories, and maintenance to preserve profits, alienating even loyal customers. In the end, whole […]

Updating Legacy Systems the FPGA Way

CATEGORIES : Embedded system, FPGA, legacy, SoC/AUTHOR : Ron Wilson

It is a scenario many embedded-systems designers recognize. An existing design needs an update. That could include Internet connectivity to bring the system into the Internet of Things (IoT). Along with that might come requirements for deeper security. And given the current enthusiasm for all things artificially intelligent, there may be new needs for deep-learning […]

Getting an Edge on Machine Learning

CATEGORIES : Computing, Embedded system, Network/AUTHOR : Ron Wilson

Taking Machine Learning to the Edge Like it or not, machine learning networks are set to be the solution du jour in embedded systems for the foreseeable future. Their remarkable ability to find and classify patterns in noisy data offers designers the option of circumventing difficult algorithm development along with the opportunity to endow their […]

Blockchain’s Burden

Blockchains are spreading. Originally proposed in 2008, by the still-unidentified Satoshi Nakamoto, as a secure public ledger for recording Bitcoin transactions, blockchains have moved beyond Bitcoin to a profusion of other cryptocurrencies, and beyond cryptocurrencies into a plethora of other applications (Figure 1). Figure 1. Blockchains are evolving to implement a wide range of services that […]

FPGAs and Data Centers: It Takes a Stack

CATEGORIES : All, Data Center, Design Challenges/AUTHOR : Ron Wilson

Design experience across a wide range of applications—from signal processing to network packet processing to cryptography to deep learning inference—has shown that, properly used, FPGAs can provide very substantial performance and power  improvements in algorithm execution. Generally, these improvements come from implementing computational kernels—the inner loops of the algorithm—in the FPGA hardware, offloading these kernels […]