IC Integrity Of Edge-Computing Processors: Meeting The Demands Of AI

By Rob van Blommestein - 18 Nov, 2020 - Comments: 0

If you ask most people, they would say that we’re living in an age of artificial intelligence (AI). But the reality is that we’re just getting started. The age of artificial intelligence is still in its infancy. So many of aspects of our lives involve technology but we’re still having to feed that technology or manually operate that technology in order get the results we want. Autonomous ... » read more

The Expanding Universe Of MIPI Applications

By Joseph Rodriguez - 12 Nov, 2020 - Comments: 0

It’s hard to imagine today, but there was a time when mobile phones had no cameras and displays were tiny monochrome LCDs capable of displaying a phone number and not much more. The iconic Nokia 3310 announced Sept. 1, 2000, had an 84 x 48 pixel monochrome display and went on to sell 126 million units worldwide. You may still have one in your junk drawer. By the time of the original iPhone... » read more

Difficult Memory Choices In AI Systems

By Ann Mutschler - 12 Nov, 2020 - Comments: 0

The number of memory choices and architectures is exploding, driven by the rapid evolution in AI and machine learning chips being designed for a wide range of very different end markets and systems. Models for some of these systems can range in size from 10 billion to 100 billion parameters, and they can vary greatly from one chip or application to the next. Neural network training and infer... » read more

Artificial Intelligence For Sustainable And Energy Efficient Buildings

By Fraunhofer IIS/EAS - 11 Nov, 2020 - Comments: 0

According to the goals of Europe’s green deal missions, the continent strives for becoming carbon neutral by 2050. Since buildings are a major contributor to the overall consumption of energy, improving their energy efficiency can be a key to a more sustainable and greener Europe. On the way towards zero-emission buildings, several challenges have to be met: In modern energy systems, several ... » 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

Faster Inferencing At The Edge

By Ed Sperling - 09 Nov, 2020 - Comments: 0

Cheng Wang, senior vice president of engineering at Flex Logix, talks about inferencing at the edge, what are some of the main considerations in designing and choosing an inferencing chip, why programmability and modularity are important, and how hardware-software co-design with algorithms can improve performance and power. » read more

ResNet-50 Does Not Predict Inference Throughput For MegaPixel Neural Network Models

By Geoff Tate - 05 Nov, 2020 - Comments: 1

Customers are considering applications for AI inference and want to evaluate multiple inference accelerators. As we discussed last month, TOPS do NOT correlate with inference throughput and you should use real neural network models to benchmark accelerators. So is ResNet-50 a good benchmark for evaluating relative performance of inference accelerators? If your application is going to p... » read more

Blog Review: Nov. 4

By Jesse Allen - 04 Nov, 2020 - Comments: 0

Arm's Joshua Sowerby points to how to improve machine learning performance on mobile devices by using smart pruning to remove convolution filters from a network, reducing its size, complexity, and memory footprint. Mentor's Neil Johnson checks out how designers can write and verify RTL real-time using formal property checking in the style of test-driven development and why to give it a try. ... » read more

Speeding Up AI With Vector Instructions

By Ann Mutschler - 04 Nov, 2020 - Comments: 0

A search is underway across the industry to find the best way to speed up machine learning applications, and optimizing hardware for vector instructions is gaining traction as a key element in that effort. Vector instructions are a class of instructions that enable parallel processing of data sets. An entire array of integers or floating point numbers is processed in a single operation, elim... » read more

Security Tradeoffs In Chips And AI Systems

By Ed Sperling - 03 Nov, 2020 - Comments: 0

Semiconductor Engineering sat down to discuss the cost and effectiveness of security in chip architectures and AI systems with with Vic Kulkarni, vice president and chief strategist at Ansys; Jason Oberg, CTO and co-founder of Tortuga Logic; Pamela Norton, CEO and founder of Borsetta; Ron Perez, fellow and technical lead for security architecture at Intel; and Tim Whitfield, vice president of s... » 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

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.