Firmware Skills Shortage

By Brian Bailey - 25 Feb, 2021 - Comments: 0

Good hardware without good software is a waste of silicon, but with so many new processors and accelerator architectures being created, and so many new skills required, companies are finding it hard to hire enough engineers with low-level software expertise to satisfy the demand. Writing compilers, mappers and optimization software does not have the same level of pizazz as developing new AI ... » read more

Powering The Edge: Driving Optimal Performance With Ethos-N77 Processor

By Arm - 10 Feb, 2021 - Comments: 0

Repurposing a CPU, GPU, or DSP is an easy way to add ML capabilities to an edge device. However, where responsiveness or power efficiency is critical, a dedicated Neural Processing Unit (NPU) may be the best solution. In this paper, we describe how the Arm Ethos-N77 NPU delivers optimal performance. Click here to read more. » read more

What Do Feedback Loops For AI/ML Devices Really Show?

By Ed Sperling - 09 Feb, 2021 - Comments: 0

AI/ML is being designed into an increasing number of chips and systems these days, but predicting how they will behave once they're in the field is, at best, a good guess. Typically, verification, validation, and testing of systems is done before devices reach the market, with an increasing amount of in-field data analysis for systems where reliability is potentially mission- or safety-criti... » read more

Edge-Inference Architectures Proliferate

By Bryon Moyer - 04 Feb, 2021 - Comments: 0

First part of two parts. The second part will dive into basic architectural characteristics. The last year has seen a vast array of announcements of new machine-learning (ML) architectures for edge inference. Unburdened by the need to support training, but tasked with low latency, the devices exhibit extremely varied approaches to ML inference. “Architecture is changing both in the comp... » read more

AI And ML Applications Require Advanced Datapath Verification

By Kiran Vittal - 28 Jan, 2021 - Comments: 0

In popular usage, the term “artificial intelligence” (AI) once conjured up images of robot armies subjugating humans or evil computers outsmarting their users, as in '2001: A Space Odyssey.' In recent years, AI has become a part of daily life for much of the planet’s population. People use voice commands to interact with their smartphones, smart speakers and even TV remote controls. Sophi... » read more

Taming Non-Predictable Systems

By Brian Bailey - 28 Jan, 2021 - Comments: 0

How predictable are semiconductor systems? The industry aims to create predictable systems and yet when a carrot is dangled, offering the possibility of faster, cheaper, or some other gain, decision makers invariably decide that some degree of uncertainty is warranted. Understanding uncertainty is at least the first step to making informed decisions, but new tooling is required to assess the im... » read more

Learning properties of ordered and disordered materials from multi-fidelity data

By Technical Paper Link - 14 Jan, 2021 - Comments: 0

Source: Chen, C., Zuo, Y., Ye, W. et al. Learning properties of ordered and disordered materials from multi-fidelity data. Nat Comput Sci 1, 46–53 (2021). https://doi.org/10.1038/s43588-020-00002-x Abstract: "Predicting the properties of a material from the arrangement of its atoms is a fundamental goal in materials science. While machine learning has emerged in recent years as a n... » read more

Why AI Systems Are So Hard To Predict

By Ed Sperling - 12 Jan, 2021 - Comments: 0

AI can do many things, but how to ensure that it does the right things is anything but clear. Much of this stems from the fact that AI/ML/DL systems are built to adapt and self-optimize. With properly adjusted weights, training algorithms can be used to make sure these systems don't stray too far from the starting point. But how to test for that, in the lab, the fab and in the field is far f... » read more

5 Predictions For AI Innovation In 2021

By Arun Venkatachar - 22 Dec, 2020 - Comments: 0

By Arun Venkatachar and Stelios Diamantidis Artificial intelligence (AI) has emerged as one of the most important watchwords in all of technology. The once-utopian vision of developing machines that can think and behave like humans is becoming more of a reality as engineering innovations enable the performance required to process and interpret previously unimaginable amounts of data efficien... » read more

A Collaborative Data Model For AI/ML In EDA

By Si2 - 21 Dec, 2020 - Comments: 0

This work explores industry perspectives on: Machine Learning and IC Design Demand for Data Structure of a Data Model A Unified Data Model: Digital and Analog examples Definition and Characteristics of Derived Data for ML Applications Need for IP Protection Unique Requirements for Inferencing Models Key Analysis Domains Conclusions and Proposed Future Work Abstra... » 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

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?

by Brian Bailey

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

Why Small Fab And Assembly Houses Are Thriving

Megafabs churning out the most advanced processors are not the only game in town.

by Bryon Moyer

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