tag: AI

Sweeping Changes Ahead For Systems Design
By Ann Mutschler - 29 Jul, 2021 - Comments: 0

Data centers are undergoing a fundamental change, shifting from standard processing models to more data-centric approaches based upon customized hardware, less movement of data, and more pooling of resources. Driven by a flood of web searches, Bitcoin mining, video streaming, data centers are in a race to provide the most efficient and fastest processing possible. But because there are so ma... » read more

Sensor Fusion Everywhere
By Ed Sperling - 19 Jul, 2021 - Comments: 0

How do you distinguish between background noise and the sound of an intruder breaking glass? David Jones, head of marketing and business development for intuitive sensing solutions at Infineon, looks at what types of sensors are being developed, what happens when different sensors are combined, what those sensors are being used for today, and what they will be used for in the future. » read more

Safe And Robust Machine Learning
By Ed Sperling - 15 Jul, 2021 - Comments: 0

Deploying machine learning in the real world is a lot different than developing and testing it in a lab. Quenton Hall, AI systems architect at Xilinx, examines security implications on both the inferencing and training side, the potential for disruptions to accuracy, and how accessible these models and algorithms will be when they are used at the edge and in the cloud. This involves everything ... » read more

Dynamically Reconfiguring Logic
By Ed Sperling - 12 Jul, 2021 - Comments: 0

Dynamic reconfiguration of semiconductor logic has been possible for years, but it never caught on commercially. Cheng Wang, co-founder and senior vice president of software and engineering at Flex Logix, explains why this capability has been so difficult to utilize, what’s changed, how a soft logic layer can be used to control when to read, compute, steer, and write data back to memory, and ... » read more

Getting Realistic About AI
By Olaf Enge-Rosenblatt - 12 Jul, 2021 - Comments: 0

By Olaf Enge-Rosenblatt and Andy Heinig The topic of artificial intelligence (AI) is omnipresent today, both in the news and on popular science shows. The number of possibilities for AI methods to assist people in making decisions are expanding rapidly. There are three main reasons for this: The development of new AI methods (deep learning, reinforcement learning); The continuous ... » read more

Securing Server Systems And Data At The Hardware Level
By Gijs Willemse - 12 Jul, 2021 - Comments: 0

Across the global internet, there’s a growing need to secure data, not only coursing over the network, but within the servers in data centers and deployed at the edge. Interconnect technologies such as Compute Express Link (CXL) will enable future servers to be disaggregated into composable resources that can be finely matched to the requirements of varied workloads and support virtualized co... » read more

IC Data Hot Potato: Who Owns And Manages It?
By Susan Rambo And Ed Sperling - 06 Jul, 2021 - Comments: 1

Modern inspection, metrology, and test equipment produces a flood of data during the manufacturing and testing of semiconductors. Now the question is what to do with all of that data. Image resolutions in inspection and metrology have been improving for some time to deal with increased density and smaller features, creating a downstream effect that has largely gone unmanaged. Higher resoluti... » read more

RaPiD: AI Accelerator for Ultra-low Precision Training and Inference
By Technical Paper Link - 02 Jul, 2021 - Comments: 0

Abstract—"The growing prevalence and computational demands of Artificial Intelligence (AI) workloads has led to widespread use of hardware accelerators in their execution. Scaling the performance of AI accelerators across generations is pivotal to their success in commercial deployments. The intrinsic error-resilient nature of AI workloads present a unique opportunity for performance/energy i... » read more

Challenges Of Edge AI Inference
By Vinay Mehta - 01 Jul, 2021 - Comments: 0

Bringing convolutional neural networks (CNNs) to your industry—whether it be medical imaging, robotics, or some other vision application entirely—has the potential to enable new functionalities and reduce the compute requirements for existing workloads. This is because a single CNN can replace more computationally expensive image processing, denoising, and object detection algorithms. Howev... » read more

Challenges In Developing A New Inferencing Chip
By Ed Sperling - 01 Jul, 2021 - Comments: 0

Cheng Wang, co-founder and senior vice president of software and engineering at Flex Logix, sat down with Semiconductor Engineering to explain the process of bringing an inferencing accelerator chip to market, from bring-up, programming and partitioning to tradeoffs involving speed and customization.   SE: Edge inferencing chips are just starting to come to market. What challenges di... » read more

← Older posts Newer posts →

  • Sponsors

About

Navigation

Connect With Us

Copyright ©2013-2025 SMG   |  Terms of Service  |  Privacy Policy