tag: machine learning

Next Challenge: Known Good Systems
By Ed Sperling - 07 Jul, 2020 - Comments: 0

The leading edge of design is heading toward multi-die/multi-chiplet architectures, and an increasing number of mainstream designs likely will follow as processing moves closer to the edge. This doesn't mean every chipmaker will be designing leading-edge chips, of course. But more devices will have at least some leading-edge logic or will be connected over some advanced interconnect scheme t... » read more

Data Becomes Key For Next-Gen Chips
By Susan Rambo And Ed Sperling - 07 Jul, 2020 - Comments: 1

Data has become vital to understanding the useful life of a semiconductor — and the knowledge gleaned is key to staying competitive beyond Moore’s Law. What's changed is a growing reliance earlier in the design cycle on multiple sources of data, including some from further right in the design-through-manufacturing flow. While this holistic approach may seem logical enough, the semiconduc... » read more

Are Better Machine Training Approaches Ahead?
By Bryon Moyer - 01 Jul, 2020 - Comments: 1

We live in a time of unparalleled use of machine learning (ML), but it relies on one approach to training the models that are implemented in artificial neural networks (ANNs) — so named because they’re not neuromorphic. But other training approaches, some of which are more biomimetic than others, are being developed. The big question remains whether any of them will become commercially viab... » read more

Winners And Losers At The Edge
By Ed Sperling - 01 Jul, 2020 - Comments: 0

The edge is a vast collection of niches tied to narrow vertical markets, and it is likely to stay that way for years to come. This is both good and bad for semiconductor companies, depending upon where they sit in the ecosystem and their ability to adapt to a constantly shifting landscape. Some segments will see continued or new growth, including EDA, manufacturing equipment, IP, security an... » read more

2020 CEO Outlook
By Ed Sperling - 25 Jun, 2020 - Comments: 0

Semiconductor Engineering sat down to discuss the semiconductor industry's outlook and what's changing with Simon Segars, CEO of Arm; Joseph Sawicki, executive vice president of IC EDA at Mentor, a Siemens Business; Raik Brinkmann, CEO of OneSpin Solutions; Babak Taheri, CEO of Silvaco; John Kibarian, CEO of PDF Solutions; and Prakash Narain, CEO of Real Intent. The conversation was part of the... » read more

ML Opening New Doors For FPGAs
By Bryon Moyer - 24 Jun, 2020 - Comments: 0

FPGAs have long been used in the early stages of any new digital technology, given their utility for prototyping and rapid evolution. But with machine learning, FPGAs are showing benefits beyond those of more conventional solutions. This opens up a hot new market for FPGAs, which traditionally have been hard to sustain in high-volume production due to pricing, and hard to use for battery-dri... » read more

Using ML In Manufacturing
By Ed Sperling - 23 Jun, 2020 - Comments: 0

How to prevent early life failures by applying machine learning to different use cases, and how to interpret models for different tradeoffs on reliability. Jeff David, vice president of AI solutions at PDF Solutions, digs down into how to utilize data to improve reliability. » read more

Simplifying And Speeding Up Verification
By Ed Sperling - 16 Jun, 2020 - Comments: 1

Semiconductor Engineering sat down to discuss what's ahead for verification with Daniel Schostak, Arm fellow and verification architect; Ty Garibay, vice president of hardware engineering at Mythic; Balachandran Rajendran, CTO at Dell EMC; Saad Godil, director of applied deep learning research at Nvidia; Nasr Ullah, senior director of performance architecture at SiFive. What follows are excerpt... » read more

New Approaches For Dealing With Thermal Problems
By Ann Mutschler - 11 Jun, 2020 - Comments: 0

New thermal monitoring, simulation and analysis techniques are beginning to coalesce in chips developed at leading-edge nodes and in advanced packages in order to keep those devices running at optimal temperatures. This is particularly important in applications such as AI, automotive, data centers and 5G. Heat can kill a chip, but it also can cause more subtle effects such as premature aging... » read more

Fundamental Changes In Economics Of Chip Security
By Ed Sperling - 10 Jun, 2020 - Comments: 0

Protecting chips from cyberattacks is becoming more difficult, more expensive and much more resource-intensive, but it also is becoming increasingly necessary as some of those chips end up in mission-critical servers and in safety-critical applications such as automotive. Security has been on the semiconductor industry's radar for at least the past several years, despite spotty progress and ... » read more

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