Software Is At Least As Important As Hardware For Inference Accelerators


In articles and conference presentations on Inference Accelerators, the focus is primarily on TOPS (frequency times number of MACs), a little bit on memory (DRAM interfaces and on chip SRAM), very little on interconnect (also very important, but that’s another story) and almost nothing on the software! Without software, the inference accelerator is a rock that does nothing. Software is wha... » read more

Ensuring Coverage In Large SoCs


Sven Beyer, product manager for design verification at OneSpin Solutions, talks about why formal technology is required to ensure coverage in some of the newest chips, how it deals with potential interactions and different use cases, and why it is gaining traction in automotive applications. » read more

Design For Airborne Electronics


The Next Generation Air Transportation System (NextGen), an FAA-led modernization of America's air transportation system meant to make flying more efficient, predictable and safer, is currently underway as one of the most ambitious infrastructure projects in U.S. history. This is not just a minor upgrade to an aging infrastructure. The FAA and partners are in the process of implementing new ... » read more

Divided On System Partitioning


Building an optimal implementation of a system using a functional description has been an industry goal for a long time, but it has proven to be much more difficult than it sounds. The general idea is to take software designed to run on a processor and to improve performance using various types of alternative hardware. That performance can be specified in various ways and for specific applic... » read more

Big Design, IP and End Market Shifts In 2020


EDA is on a roll. Design starts are up significantly thanks to increased investment in areas such as AI, a plethora of new communications standards, buildout of the Cloud, the race toward autonomous driving and continued advancements in mobile phones. Many designs demand the latest technologies and push the limits of complexity. Low power is becoming more than just reducing wasted power at t... » read more

More Knobs, Fewer Markers


The next big thing in chip design may be really big — the price tag. In the past, when things got smaller, so did the cost per transistor. Now they are getting more expensive to design and manufacture, and the cost per transistor is going up along with the number of transistors per area of die, and in many cases even the size of the die. That's not exactly a winning economic formula, which... » read more

Uses And Limitations Of AI In Chip Design


Raik Brinkmann, president and CEO of OneSpin Solutions, sat down with Semiconductor Engineering to talk about AI changes and challenges, new opportunities for using existing technology to improve AI, and vice versa. What follows are excerpts of that conversation. SE: What's changing in AI? Brinkmann: There are a couple of big changes underway. One involves AI in functional safety, where y... » read more

Using Hypervisor For IVI And AUTOSAR Consolidation On An ECU


Current approaches used to tackle the complexities described earlier in this paper (cockpit domain units) are both cost-prohibitive and lacking in performance. Utilizing virtualization in automotive software architecture provides a better approach when taking on these complexities. This can be achieved by encapsulating different heterogeneous automotive platforms inside virtual machines running... » read more

Scaling, Packaging, And Partitioning


Prior to the finFET era, most chipmakers either focused on shrinking or packaging, but they rarely did both. Going forward, the two will be inseparable, and that will lead to big challenges with partitioning of data and processing. The key driver here, of course, is that device scaling no longer provides appreciable benefits in power, performance and cost. Nevertheless, scaling does provide ... » read more

Making Sense Of Inferencing Options


Ian Bratt, fellow in Arm’s machine learning group, sheds light on all the different processing elements in machine learning, how different end user requirements affect those choices, why CPUs are a critical element in orchestrating what happens in these systems, and how power and software play into these choices. » read more

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