Revving Up For Edge Computing

By Ed Sperling - 07 Nov, 2019 - Comments: 1

The edge is beginning to take shape as a way of limiting the amount of data that needs to be pushed up to the cloud for processing, setting the stage for a massive shift in compute architectures and a race among chipmakers for a stake in a new and highly lucrative market. So far, it's not clear which architectures will win, or how and where data will be partitioned between what needs to be p... » read more

Using Multiple Inferencing Chips In Neural Networks

By Ed Sperling - 04 Oct, 2019 - Comments: 0

Geoff Tate, CEO of Flex Logix, talks about what happens when you add multiple chips in a neural network, what a neural network model looks like, and what happens when it’s designed correctly vs. incorrectly. » read more

ML, Edge Drive IP To Outperform Broader Chip Market

By Kevin Fogarty - 03 Oct, 2019 - Comments: 0

The market for third-party semiconductor IP is surging, spurred by the need for more specific capabilities across a wide variety of markets. While the IP industry is not immune to steep market declines in semiconductor industry, it does have more built-in resilience than other parts of the industry. Case in point: The top 15 semiconductor suppliers were hit with an 18% decline in 2019 first-... » read more

Why Data Is So Difficult To Protect In AI Chips

By Ed Sperling - 25 Sep, 2019 - Comments: 0

Experts at the Table: Semiconductor Engineering sat down to discuss a wide range of hardware security issues and possible solutions with Norman Chang, chief technologist for the Semiconductor Business Unit at ANSYS; Helena Handschuh, fellow at Rambus, and Mike Borza, principal security technologist at Synopsys. What follows are excerpts of that conversation. The first part of this discussion ca... » read more

What’s Powering Artificial Intelligence?

By Arm - 11 Sep, 2019 - Comments: 0

While artificial intelligence (AI) and machine learning (ML) applications soar in popularity, many organizations are questioning where ML workloads should be performed. Should they be done on a central processor (CPU), a graphics processor (GPU), or a neural processor (NPU)? The choice most teams are making today will surprise you. To scale artificial intelligence (AI) and machine learning (... » read more

Synthesizing Hardware From Software

By Brian Bailey - 22 Aug, 2019 - Comments: 1

The ability to automatically generate optimized hardware from software was one of the primary tenets of system-level design automation that was never fully achieved. The question now is whether that will ever happen, and whether it is just a matter of having the right technology or motivation to make it possible. While high-level synthesis (HLS) did come out of this work and has proven to be... » read more

Machine Learning Inferencing Moves To Mobile Devices

By Kevin Fogarty - 02 Jul, 2019 - Comments: 0

It may sound retro for a developer with access to hyperscale data centers to discuss apps that can be measured in kilobytes, but the emphasis increasingly is on small, highly capable devices. In fact, Google staff research engineer Pete Warden points to a new app that uses less than 100 kilobytes for RAM and storage, creates an inference model smaller than 20KB, and which is capable of proce... » read more

Machine Learning Drives High-Level Synthesis Boom

By Kevin Fogarty - 06 Jun, 2019 - Comments: 0

High-level synthesis (HLS) is experiencing a new wave of popularity, driven by its ability to handle machine-learning matrices and iterative design efforts. The obvious advantage of HLS is the boost in productivity designers get from working in C, C++ and other high-level languages rather than RTL. The ability to design a layout that should work, and then easily modify it to test other confi... » read more

Accelerating Endpoint Inferencing

By Kevin Fogarty - 06 Jun, 2019 - Comments: 0

Chipmakers are getting ready to debut inference chips for endpoint devices, even though the rest of the machine-learning ecosystem has yet to be established. Whatever infrastructure does exist today is mostly in the cloud, on edge-computing gateways, or in company-specific data centers, which most companies continue to use. For example, Tesla has its own data center. So do most major carmake... » read more

Driving AI, ML To New Levels On MCUs

By Rhonda Dirvin - 09 May, 2019 - Comments: 0

One of the most dramatic impacts of technology of late has been the implementation of artificial intelligence and machine learning on small edge devices, the likes of which are forming the backbone of the Internet of Things. At first, this happened through sheer engineering willpower and innovation. But as the drive towards a world of a trillion connected devices accelerates, we must find wa... » 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

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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

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

New AI Processors Architectures Balance Speed With Efficiency

Hot Chips 24: Large language models ratchet up pressure for sustainable computing and heterogeneous integration; data management becomes key differentiator.