RISC-V: What’s Missing And Who’s Competing


Part 2: Semiconductor Engineering sat down to discuss the business and technology landscape for RISC-V with Zdenek Prikryl, CTO of Codasip; Helena Handschuh, a Rambus Security Technologies fellow; Louie De Luna, director of marketing at Aldec; Shubhodeep Roy Choudhury, CEO of Valtrix Systems; and Bipul Talukdar, North America director of applications engineering at SmartDV. What follows are exc... » read more

Week In Review: Manufacturing, Test


Chipmakers and OEMs Apple has launched a new Apple Watch and iPad. Missing from the announcement was the iPhone 12, which may appear next month, according to Krish Sankar, an analyst at Cowen. What was interesting about this week’s announcement? Apple unveiled the iPad Air with the A14 Bionic, Apple’s most advanced chip. “Apple revealed the new 8th gen iPad (starting at $329) powered by ... » read more

Week In Review: Auto, Security, Pervasive Computing


Security Synopsys’ Software Integrity Group published the results of a security survey that looked at the ways organizations across industries are handling their software security initiatives and how to improve them. The Building Security In Maturity Model (BSIMM) version 11 (BSIMM11 Study) describes the work of 8,457 software security pros. FinTech — the technology that “follows the mon... » read more

Week In Review: Design, Low Power


Nvidia will acquire Arm from SoftBank in a $40 billion deal. Nvidia says that Arm will continue to operate its open-licensing model while maintaining global customer neutrality. SoftBank acquired Arm in 2016 for $32 billion; it also holds an ownership stake in Nvidia that is expected to remain under 10%. The deal does not include Arm's IoT Services Group. The acquisition will need to pass regul... » read more

Custom Designs, Custom Problems


Semiconductor Engineering sat down to discuss power optimization with Oliver King, CTO at Moortec; João Geada, chief technologist at Ansys; Dino Toffolon, senior vice president of engineering at Synopsys; Bryan Bowyer, director of engineering at Mentor, a Siemens Business; Kiran Burli, senior director of marketing for Arm's Physical Design Group; Kam Kittrell, senior product management group d... » read more

Blog Review: Sept. 16


Cadence's Paul McLellan checks out what's new for TSMC's advanced packaging solutions and the ultra-low power, RF, eNVM, and CMOS image sensor specialty processes. Mentor's Ron Press points to an automated solution to measuring pattern value that provides a consistent, “apples to apples” assessment of patterns detecting defects based on the likelihood the physical defects occurring. S... » read more

Nvidia To Buy Arm For $40B


Nvidia inked a deal with Softbank to buy Arm for $40 billion, combining the No. 1 AI/ML GPU maker with the No. 1 processor IP company. Assuming the deal wins regulatory approval, the combination of these two companies will create a powerhouse in the AI/ML world. Nvidia's GPUs are the go-to platform for training algorithms, while Arm has a broad portfolio of AI/ML processor cores. Arm also ha... » read more

Optimizing For Energy In Physical Design


Energy is a precious resource, which should not be wasted. Energy drives economies and sustains societies. Predictions show that the energy of electronics may soon consume 20% to 33% of the global energy supply, as it is highlighted in this blog post about "Design and Manufacturing in 2030" from Greg Yeric, fellow at Arm. Energy efficiency is such an important global issue that it is ... » read more

Is DVFS Worth The Effort?


Almost all designs have become power-aware and are being forced to consider every power saving technique, but not all of them are yielding the expected results. Moreover, they can add significant complexity into designs, increasing the time it takes to get to tapeout and boosting up the cost. Dynamic voltage and frequency scaling (DVFS) is one such power and energy saving technique now being... » read more

Compiling And Optimizing Neural Nets


Edge inference engines often run a slimmed-down real-time engine that interprets a neural-network model, invoking kernels as it goes. But higher performance can be achieved by pre-compiling the model and running it directly, with no interpretation — as long as the use case permits it. At compile time, optimizations are possible that wouldn’t be available if interpreting. By quantizing au... » read more

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