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

ACAP At The Edge With The Versal AI Edge Series

By Xilinx - 30 Jun, 2021 - Comments: 0

This white paper introduces the AI Edge series to the Versal ACAP portfolio, a domain-specific architecture (DSA) that meets the strenuous demands of systems implemented in the 7nm silicon process. This series is optimized to meet the performance-per-watt requirements of edge nodes at or near the analog-digital boundary. Here, immediate response to the physical world is highly valued, and in ma... » read more

Debug: The Schedule Killer

By Brian Bailey - 30 Jun, 2021 - Comments: 0

Debug often has been labeled the curse of management and schedules. It is considered unpredictable and often can happen close to the end of the development cycle, or even after – leading to frantic attempts at work-arounds. And the problem is growing. "Historically, about 40% of time is spent in debug, and that aspect is becoming more complex," says Vijay Chobisa, director of product manag... » read more

Manufacturing Bits: June 29

By Mark LaPedus - 29 Jun, 2021 - Comments: 0

Speeding up ALD with AI The U.S. Department of Energy’s (DOE) Argonne National Laboratory has developed various ways to make atomic layer deposition (ALD) more efficient by using artificial intelligence (AI). ALD is a deposition technique that deposits materials one layer at a time on chips. For years, ALD has been used for the production of DRAMs, logic devices and other products. In ... » read more

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Knowledge Centers
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