Increasing AI Energy Efficiency With Compute In Memory

By Katherine Derbyshire - 16 Nov, 2023 - Comments: 0

Skyrocketing AI compute workloads and fixed power budgets are forcing chip and system architects to take a much harder look at compute in memory (CIM), which until recently was considered little more than a science project. CIM solves two problems. First, it takes more energy to move data back and forth between memory and processor than to actually process it. And second, there is so much da... » read more

Applications Of Large Language Models For Industrial Chip Design (NVIDIA)

By Technical Paper Link - 10 Nov, 2023 - Comments: 0

A technical paper titled “ChipNeMo: Domain-Adapted LLMs for Chip Design” was published by researchers at NVIDIA. Abstract: "ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we instead adopt the following domain adaptation techniques: custom tokenizers, domain-ad... » read more

Neural Network Model Quantization On Mobile

By Roberto Lopez Mendez - 09 Nov, 2023 - Comments: 0

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in the context of neural network (NN) models, as the process of reducing the precision of the weights, biases, and activations. Moving from floating-point representations to low-precision fixed intege... » read more

New Insights Into IC Process Defectivity

By Laura Peters - 07 Nov, 2023 - Comments: 1

Finding critical defects in manufacturing is becoming more difficult due to tighter design margins, new processes, and shorter process windows. Process marginality and parametric outliers used to be problematic at each new node, but now they are persistent problems at several nodes and in advanced packaging, where there may be a mix of different technologies. In addition, there are more proc... » read more

Optimization Of The Interface Between The PD And The AFE In High-Speed, High-Density Optical Receivers

By Technical Paper Link - 27 Oct, 2023 - Comments: 0

A technical paper titled “Optimizing the Photodetector/Analog Front-End Interface in Optical Communication Receivers” was published by researchers at University of Toronto. Abstract: "This article addresses the optimization of the interface between the photodetector (PD) and the analog front-end in high-speed, high-density optical communication receivers. Specifically, the article focuses... » read more

Energy Usage in Layers Of Computing (SLAC)

By Technical Paper Link - 19 Oct, 2023 - Comments: 0

A technical paper titled “Energy Estimates Across Layers of Computing: From Devices to Large-Scale Applications in Machine Learning for Natural Language Processing, Scientific Computing, and Cryptocurrency Mining” was published by researchers at SLAC National Laboratory and Stanford University. Abstract: "Estimates of energy usage in layers of computing from devices to algorithms have bee... » read more

Applying Machine Learning to EDA, FPGA Design Automation Tools

By Technical Paper Link - 11 Oct, 2023 - Comments: 0

A technical paper titled “Application of Machine Learning in FPGA EDA Tool Development” was published by researchers at the University of Texas Dallas. Abstract: "With the recent advances in hardware technologies like advanced CPUs and GPUs and the large availability of open-source libraries, machine learning has penetrated various domains, including Electronics Design Automation (EDA). E... » read more

Streamlining Failure Analysis Of Chips

By Anne Meixner - 10 Oct, 2023 - Comments: 1

Experts at the Table: Semiconductor Engineering sat down to discuss how increasing complexity in semiconductor and packaging technology is driving shifts in failure analysis methods, with Frank Chen, director of applications and product management at Bruker Nano Surfaces & Metrology; Mike McIntyre, director of product management in the Enterprise Business Unit at Onto Innovation; Kamran Hak... » read more

How Much AI Is Really Needed?

By John Koon - 05 Oct, 2023 - Comments: 0

Tensor Core GPUs have created a generative AI model gold rush. Whether it’s helping students with math homework, planning a vacation, or learning to prepare a six-course meal, generative AI is ready with answers. But that's only one aspect of AI, and not every application requires it. AI — now an all-inclusive term, referring to the process of using algorithms to learn, predict, and make... » read more

Data Collection For Edge AI / Tiny ML With Sensors

By Renesas - 04 Oct, 2023 - Comments: 0

Reality AI software from Renesas provides solution suites and tools for R&D engineers who build products and internal solutions using sensors. Working with accelerometers, vibration, sound, electrical (current/voltage/ capacitance), radar, RF, proprietary sensors, and other types of sensor data, Reality AI software identifies signatures of events and conditions, correlates changes in signat... » 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?