New Approaches To Power Decoupling

By Bryon Moyer - 24 Oct, 2024 - Comments: 0

Decoupling capacitors have long been an important aspect of maintaining a clean power source for integrated circuits, but with noise caused by rising clock frequencies, multiple power domains, and various types of advanced packaging, new approaches are needed. Power is a much more important factor than it used to be, especially in the era of AI. “Doing an AI search consumes 10X the power t... » read more

In Situ Backpropagation Strategy That Progressively Updates Neural Network Layers Directly in HW (TU Eindhoven)

By Technical Paper Link - 16 Jul, 2024 - Comments: 0

A new technical paper titled "Hardware implementation of backpropagation using progressive gradient descent for in situ training of multilayer neural networks" was published by researchers at Eindhoven University of Technology. Abstract "Neural network training can be slow and energy-expensive due to the frequent transfer of weight data between digital memory and processing units. Neuromorp... » read more

Making Tradeoffs With AI/ML/DL

By Ann Mutschler - 11 May, 2023 - Comments: 0

Machine learning, deep learning, and AI increasingly are being used in chip design, and they are being used to design chips that are optimized for ML/DL/AI. The challenge is understanding the tradeoffs on both sides, both of which are becoming increasingly complex and intertwined. On the design side, machine learning has been viewed as just another tool in the design team's toolbox. That's s... » read more

A crossbar array of magnetoresistive memory devices for in-memory computing

By Technical Paper Link - 14 Jan, 2022 - Comments: 0

Samsung has demonstrated the world’s first in-memory computing technology based on MRAM. Samsung has a paper on the subject in Nature. This paper showcases Samsung’s effort to merge memory and system semiconductors for next-generation artificial intelligence (AI) chips. Abstract "Implementations of artificial neural networks that borrow analogue techniques could potentially offer low-po... » read more

Architectural Considerations For AI

By Brian Bailey - 24 Jun, 2021 - Comments: 2

Custom chips, labeled as artificial intelligence (AI) or machine learning (ML), are appearing on a weekly basis, each claiming to be 10X faster than existing devices or consume 1/10 the power. Whether that is enough to dethrone existing architectures, such as GPUs and FPGAs, or whether they will survive alongside those architectures isn't clear yet. The problem, or the opportunity, is that t... » read more

The Benefits Of Using Embedded Sensing Fabrics In AI Devices

By Moortec - 11 Nov, 2020 - Comments: 0

AI chips, regardless of the application, are not regular ASICs and tend to be very large, this essentially means that AI chips are reaching the reticle limits in-terms of their size. They are also usually dominated by an array of regular structures and this helps to mitigate yield issues by building in tolerance to defect density due to the sheer number of processor blocks. The reason behind... » read more

Variables Complicate Safety-Critical Device Verification

By Ann Mutschler - 01 Jul, 2020 - Comments: 0

The inclusion of AI chips in automotive and increasingly in avionics has put a spotlight on advanced-node designs that can meet all of the ASIL-D requirements for temperature and stress. How should designers approach this task, particularly when these devices need to last longer than the applications? Semiconductor Engineering sat down to discuss these issues with Kurt Shuler, vice president of... » read more

Startup Funding: March 2020

By Jesse Allen - 08 Apr, 2020 - Comments: 0

Dedicated AI hardware, quantum computing, and avionics startups shined in March. Here's a look at seventeen startups, which raised a collective $525M. The avionics sector soared thanks to Lilium and its electric vertical takeoff jet. Quantum computing was another hot area, with three companies bringing in ~$88M together. Plus, chip design management, two companies developing AR glasses, and how... » read more

Defining And Improving AI Performance

By Brian Bailey - 12 Dec, 2019 - Comments: 2

Many companies are developing AI chips, both for training and for inference. Although getting the required functionality is important, many solutions will be judged by their performance characteristics. Performance can be measured in different ways, such as number of inferences per second or per watt. These figures are dependent on a lot of factors, not just the hardware architecture. The optim... » read more

Thermal Challenges In Advanced Packaging

By Ed Sperling - 02 Dec, 2019 - Comments: 2

CT Kao, product management director at Cadence, talks with Semiconductor Engineering about why packaging is so complicated, why power and heat vary with different use cases and over time, and why a realistic power map is essential particularly for AI chips, where some circuits are always on. Interested in more Semiconductor Engineering videos? Sign-up for our YouTube channel here » read more

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Knowledge Centers
Entities, people and technologies explored

Shift Left Is The Tip Of The Iceberg

A transformative change is underway for semiconductor design and EDA. New languages, models, and abstractions will need to be created.

by Brian Bailey

Partitioning In The Chiplet Era

Understanding how chiplets interact under different workloads is critical to ensuring signal integrity and optimal performance in heterogeneous designs.

by Ann Mutschler

3.5D: The Great Compromise

Pros and cons of a middle-ground chiplet assembly that combines 2.5D and 3D-IC.

by Ed Sperling

AI’s Role In Chip Design Widens, Drawing In New Startups

Focus is on letting engineers do much more with the same or fewer resources — and less drudgery.

by Karen Heyman

Key Technologies To Extend EUV To 14 Angstroms

Alongside high-NA EUV will be better-performing photoresists, reduced roughness using passivation and etch, and lateral etching to reduce tip-to-tip dimensions.

by Laura Peters

Memory Fundamentals For Engineers

eBook: Nearly everything you need to know about memory, including detailed explanations of the different types of memory; how and where these are used today; what's changing, which memories are successful and which ones might be in the future; and the limitations of each memory type.

by The SE Staff

What Comes After HBM For Chiplets

The standard for high-bandwidth memory limits design freedom at many levels, but that is required for interoperability. What freedoms can be taken from other functions to make chiplets possible?