Week in Review – IoT, Security, Autos

By Jeff Dorsch - 06 Sep, 2019 - Comments: 0

Products/Services Rambus entered an exclusive agreement to acquire the Silicon IP, Secure Protocols, and Provisioning business from Verimatrix, formerly known as Inside Secure. Financial terms were not revealed. The transaction is expected to close this year. Rambus will use the Verimatrix offerings in such demanding applications as artificial intelligence, automotive, the Internet of Things, ... » read more

The Race For Better Computational Software

By Ed Sperling - 05 Sep, 2019 - Comments: 0

Anirudh Devgan, president of Cadence, sat down with Semiconductor Engineering to talk about computational software, why it's so critical at the edge and in AI systems, and where the big changes are across the semiconductor industry. What follows are excerpts of that conversation. SE: There is no consistent approach to how data will be processed at the edge, in part because there is no consis... » 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

Chiplets, Faster Interconnects, More Efficiency

By Ed Sperling - 22 Aug, 2019 - Comments: 1

Big chipmakers are turning to architectural improvements such as chiplets, faster throughput both on-chip and off-chip, and concentrating more work per operation or cycle, in order to ramp up processing speeds and efficiency. Taken as a whole, this represents a significant shift in direction for the major chip companies. All of them are wrestling with massive increases in processing demands ... » read more

Why Scaling Must Continue

By Ed Sperling - 15 Aug, 2019 - Comments: 3

The entire semiconductor industry has come to the realization that the economics of scaling logic are gone. By any metric—price per transistor, price per watt, price per unit area of silicon—the economics are no longer in the plus column. So why continue? The answer is more complicated than it first appears. This isn't just about inertia and continuing to miniaturize what was proven in t... » read more

Powering The Edge: Driving Optimal Performance With the Arm ML Processor

By Arm - 07 Aug, 2019 - Comments: 0

On-device machine learning (ML) processing is already happening in more than 4 billion smart phones. As the adoption of connected devices continues to grow exponentially, the resulting data explosion means cloud processing could soon become an expensive and high-latency luxury. The Arm ML processor is defining the future of ML inference at the edge, allowing smart devices to make independent... » read more

Where Should Auto Sensor Data Be Processed?

By Ann Mutschler - 01 Aug, 2019 - Comments: 0

Fully autonomous vehicles are coming, but not as quickly as the initial hype would suggest because there is a long list of technological issues that still need to be resolved. One of the basic problems that still needs to be solved is how to process the tremendous amount of data coming from the variety of sensors in the vehicle, including cameras, radar, LiDAR and sonar. That data is the dig... » read more

Power Is Limiting Machine Learning Deployments

By Brian Bailey - 25 Jul, 2019 - Comments: 3

The total amount of power consumed for machine learning tasks is staggering. Until a few years ago we did not have computers powerful enough to run many of the algorithms, but the repurposing of the GPU gave the industry the horsepower that it needed. The problem is that the GPU is not well suited to the task, and most of the power consumed is waste. While machine learning has provided many ... » read more

Will In-Memory Processing Work?

By Brian Bailey - 16 Jul, 2019 - Comments: 1

The cost associated with moving data in and out of memory is becoming prohibitive, both in terms of performance and power, and it is being made worse by the data locality in algorithms, which limits the effectiveness of cache. The result is the first serious assault on the von Neumann architecture, which for a computer was simple, scalable and modular. It separated the notion of a computatio... » read more

Differential Energy Analysis To Optimize Mobile GPU Power

By Ansys - 15 Jul, 2019 - Comments: 0

Operating power has become one of the most important metrics for modern electronic devices. Qualcomm Technologies, a world-class mobile solution provider, significantly reduced power consumption in an already challenging market by performing power analysis at RTL using ANSYS PowerArtist. Qualcomm Technologies was able to reduce dynamic power by 10 percent through this approach. To read more,... » 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

tag: GPU