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

Incremental System Verification


Semiconductor Engineering sat down to discuss the implications of having an executable specification that drives verification with Hagai Arbel, chief executive officer for VTool; Adnan Hamid, chief executive office for Breker Verification; Mark Olen, product marketing manager for Mentor, a Siemens Business; Jim Hogan, managing partner of Vista Ventures; Sharon Rosenberg, senior solutions archit... » read more

Complexity’s Impact On Security


Ben Levine, senior director of product management for Rambus’ Security Division, explains why security now depends on the growing number of components and the impact of interactions between those components. This is particularly problematic with AI chips, both on the training and inferencing side, where security problems on the training side can alter models for AI inferencing. » read more

The Case For Embedded FPGAs Strengthens And Widens


The embedded FPGA, an IP core integrated into an ASIC or SoC, is winning converts. System architects are starting to see the benefits of eFPGAs, which offer the flexibility of programmable logic without the cost of FPGAs. Programmable logic is especially appealing for accelerating machine learning applications that need frequent updates. An eFPGA can provide some architects the cover they ne... » read more

Multi-Physics At 5/3nm


Joao Geada, chief technologist at ANSYS, talks about why timing, process, voltage, and temperature no longer can be considered independently of each other at the most advanced nodes, and why it becomes more critical as designs shrink from 7nm to 5nm and eventually to 3nm. In addition, more chips are being customized, and more of those chips are part of broader systems that may involve an AI com... » read more

Accelerating Adoption of SiC Power


The market has heard for many years about wide bandgap product roadmaps and concepts, touting that many possibilities could be available. However, you can’t design in a PowerPoint presentation or a preliminary datasheet, so this article will reinforce that Wolfspeed SiC power has moved way beyond any hype, talk, and fake news and has pioneered the widespread adoption of silicon carbide power ... » read more

Power Budgets At 3nm And Beyond


There is high confidence that digital logic will continue to shrink at least to 3nm, and possibly down to 1.5nm. Each of those will require significant changes in how design teams approach power. This is somewhat evolutionary for most chipmakers. Five years ago there were fewer than a handful of power experts in most large organizations. Today, everyone deals with power in one way or another... » read more

Using Less Power At The Same Node


Going to the next node has been the most effective way to reduce power, but that is no longer true or desirable for a growing percentage of the semiconductor industry. So the big question now is how to reduce power while maintaining the same node size. After understanding how the power is used, both chip designers and fabs have techniques available to reduce power consumption. Fabs are makin... » read more

Gearing Up For 5G


5G has been touted as the new enabler for many market segments, including mobile phones, automotive, virtual reality, and IoT. But there are many questions and much speculation about when and how this new wireless standard will impact different market segments and what effect it will have on semiconductor design. With a promise of orders of magnitude improvement in communication speed an... » 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

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