Week in Review: IoT, Security, Auto


Internet of Things Combining artificial intelligence with unmanned aerial vehicles could provide a quicker and safer alternative to inspecting roadways for cracks, potholes, and other damage, according to a paper posted on arvix.org. “[M]anual visual inspection [is] not only tedious, time-consuming, and costly, but also dangerous for the personnel. Furthermore, the detection results are alwa... » read more

The Automation Of AI


Semiconductor Engineering sat down to discuss the role that EDA has in automating artificial intelligence and machine learning with Doug Letcher, president and CEO of Metrics; Daniel Hansson, CEO of Verifyter; Harry Foster, chief scientist verification for Mentor, a Siemens Business; Larry Melling, product management director for Cadence; Manish Pandey, Synopsys fellow; and Raik Brinkmann, CEO ... » read more

Pushing AI Into The Mainstream


Artificial intelligence is emerging as the driving force behind many advancements in technology, even though the industry has merely scratched the surface of what may be possible. But how deeply AI penetrates different market segments and technologies, and how quickly it pushes into the mainstream, depend on a variety of issues that still must be resolved. In addition to a plethora of techni... » read more

EDA Grabs Bigger Slice Of Chip Market


EDA revenues have been a fairly constant percentage of semiconductor revenues, but that may change in 2019. With new customers creating demand, and some traditional customers shifting focus from advanced nodes, the various branches of the EDA tool industry may be where sticky technical problems are solved. IC manufacturing, packaging and development tools all are finding new ways to handle t... » read more

The Data Deluge


Lip-Bu Tan, president and CEO of Cadence, sat down with Semiconductor Engineering to discuss the intersection of big data and technology, from the data center to the edge and vertical markets such as automotive. What follows are excerpts of that conversation. SE: What are the biggest changes you've seen over the past year? Tan: We are moving quickly toward data-driven economics. There... » read more

Taming Concurrency


Concurrency adds complexity for which the industry lacks appropriate tools, and the problem has grown to the point where errors can creep into designs with no easy or consistent way to detect them. In the past, when chips were essentially a single pipeline, this wasn't a problem. In fact, the early pioneers of EDA created a suitable language to describe and contain the necessary concurrency ... » read more

Trends In FPGA Effectiveness: The 2018 Wilson Research Group Functional Verification Study


We all know that knowledge is power. The adage holds true even in the prosaic case of making informed decisions backed by good data. Our hope and motivation in conducting the worldwide Wilson Research Group Functional Verification Study is to provide our community the information needed to make the best methodology and tool choices for their business and design goals. As well, we at Mentor, ... » read more

Top Tech Talks Of 2018


2018 shaped up to be a year of transition and inflection, sometimes in the same design. There were new opportunities in automotive, continued difficulties in scaling, and an explosion in AI and machine learning everywhere. Traffic numbers on stories give a snapshot of the most current trends, but with videos those trends are even more apparent because of the time invested in watching those v... » read more

Making IP Friendlier


Semiconductor Engineering sat down to discuss IP tracking and management with Ranjit Adhikary, vice president of marketing for ClioSoft; Jim Bruister, director digital systems (since retired) at Silvaco; Marc Greenberg, product marketing group director at Cadence; and Kelvin Low, vice president of marketing at Arm. What follows are excerpts from that conversation. Part one can be found here. ... » read more

Deep Learning Hardware: FPGA vs. GPU


FPGAs or GPUs, that is the question. Since the popularity of using machine learning algorithms to extract and process the information from raw data, it has been a race between FPGA and GPU vendors to offer a HW platform that runs computationally intensive machine learning algorithms fast and efficiently. As Deep Learning has driven most of the advanced machine learning applications, it is r... » read more

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