Week in Review – IoT, Security, Autos


Products/Services Rambus entered an exclusive agreement to acquire the Silicon IP, Secure Protocols, and Provisioning business from Verimatrix, formerly known as Inside Secure. Financial terms were not revealed. The transaction is expected to close this year. Rambus will use the Verimatrix offerings in such demanding applications as artificial intelligence, automotive, the Internet of Things, ... » read more

Week In Review: Manufacturing, Test


Chipmakers GlobalFoundries has filed suits in the U.S. and Germany, alleging that semiconductor manufacturing technologies used by TSMC infringe upon 16 of GF's patents. The suits were filed in the U.S. International Trade Commission (ITC), the U.S. Federal District Courts in the Districts of Delaware and the Western District of Texas, and the Regional Courts of Dusseldorf and Mannheim in Germ... » read more

Week in Review: IoT, Security, Autos


Products/Services Rambus reports completing its acquisition of Northwest Logic, a supplier of memory, PCIe, and MIPI digital controllers. Meanwhile, the company named Sean Fan as chief operating officer. He previously served as vice president and general manager of the data center business unit at Renesas Electronics. Prior to its acquisition by Renesas earlier this year, Fan held senior execu... » read more

Surround And Conquer


The processor wars are back in full swing, this time with some new players in the field. But what defines winning this time around is far less obvious than it was in the past, and it will take years before we know the outcome. The strategy is the same, though, and it's one that has been in use for years in the tech world. It began in the 1990s, when IBM came to the realization that it could ... » read more

Chiplets, Faster Interconnects, More Efficiency


Big chipmakers are turning to architectural improvements such as chiplets, faster throughput both on-chip and off-chip, and concentrating more work per operation or cycle, in order to ramp up processing speeds and efficiency. Taken as a whole, this represents a significant shift in direction for the major chip companies. All of them are wrestling with massive increases in processing demands ... » read more

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

Week In Review: Manufacturing, Test


Deals Apple will pay $1 billion to buy Intel's smartphone modem unit. Under the terms of the agreement, Apple will hire 2,200 Intel employees and acquire Intel's IP and equipment. The deal, expected to close in Q4, puts an end to Intel's attempts to win a piece of the smartphone market. But the chipmaker retains the right to develop modems for non-smartphone applications, including PCs, IoT de... » read more

Semicon West Debrief


AI vs. energy. Quantum for everyone. Biofabrication of human organs on a mass scale. Slowing advancements from Moore’s law. In the midst of a market dip, optimism reigned as keynote and AI Design Forum speakers addressed both looming challenges and explosive market opportunities during July 9-10 presentations at SEMICON West 2019 in San Francisco. SEMICON West again proved to be a magnet f... » read more

Week in Review: IoT, Security, Autos


Products/Services Siemens announced that Mazda Motor adopted the Capital electrical design software suite from Mentor, a Siemens Business, for the design of next-generation automotive electrical systems. Mazda is said to use Capital for model-based generative design for the electrical and electronic systems of the entire vehicle platform. Synopsys will host the 11th annual Codenomi-con USA ... » read more

Power Is Limiting Machine Learning Deployments


The total amount of power consumed for machine learning tasks is staggering. Until a few years ago we did not have computers powerful enough to run many of the algorithms, but the repurposing of the GPU gave the industry the horsepower that it needed. The problem is that the GPU is not well suited to the task, and most of the power consumed is waste. While machine learning has provided many ... » read more

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