More Semiconductor Data Moving To Cloud


The cloud is booming. After years of steady growth it has begun to spike, creating new options for design, test, analytics and AI, all of which have an impact on every segment of the semiconductor industry. The initial idea behind the cloud is that it would supplement processing done on premises, adding extra processing power wherever necessary, such as in the verification and debug stages o... » read more

Big Shifts In Big Data


The big data market is in a state of upheaval as companies begin shifting their data strategies from "nothing" or "everything" in the cloud to a strategic mix, squeezing out middle-market players and changing what gets shared, how that data is used, and how best to secure it. This has broad implications for the whole semiconductor supply chain, because in many cases it paves the way for ... » read more

Edge Complexity To Grow For 5G


Edge computing is becoming as critical to the success of 5G as millimeter-wave technology will be to the success of the edge. In fact, it increasingly looks as if neither will succeed without the other. 5G networks won’t be able to meet 3GPP’s 4-millisecond-latency rule without some layer to deliver the data, run the applications and broker the complexities of multi-tier Internet apps ac... » read more

Power, Reliability And Security In Packaging


Semiconductor Engineering sat down to discuss advanced packaging with Ajay Lalwani, vice president of global manufacturing operations at eSilicon; Vic Kulkarni, vice president and chief strategist in the office of the CTO at ANSYS; Calvin Cheung, vice president of engineering at ASE; Walter Ng, vice president of business management at UMC; and Tien Shiah, senior manager for memory at Samsun... » read more

Memory Options And Tradeoffs


Steven Woo, Rambus fellow and distinguished inventor, talks with Semiconductor Engineering about different memory options, why some are better than others for certain tasks, and what the tradeoffs are between the different memory types and architectures.     Related Articles/Videos Memory Tradeoffs Intensify In AI, Automotive Applications Why choosing memories and archi... » read more

5G Design Changes


Mike Fitton, senior director of strategic planning at Achronix, talks with Semiconductor Engineering about the two distinct parts of 5G deployment, how to get a huge amount of data from the core to the edge of a device where it is usable, and how a network on chip can improve the flow of data. » read more

Accelerating Endpoint Inferencing


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

Machine Learning Drives High-Level Synthesis Boom


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

Holes In AI Security


Mike Borza, principal security technologist in Synopsys’ Solutions Group, explains why security is lacking in AI, why AI is especially susceptible to Trojans, and why small changes in training data can have big impacts on many devices. » read more

Inferencing At The Edge


Geoff Tate, CEO of Flex Logix, talks about the challenges of power and performance at the edge, why this market is so important from a business and technology standpoint, and what factors need to be balanced. » read more

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