Looking Beyond The CPU


CPUs no longer deliver the same kind of of performance improvements as in the past, raising questions across the industry about what comes next. The growth in processing power delivered by a single CPU core began stalling out at the beginning of the decade, when power-related issues such as heat and noise forced processor companies to add more cores rather than pushing up the clock frequency... » read more

AI Begins To Reshape Chip Design


Artificial intelligence is beginning to impact semiconductor design as architects begin leveraging its capabilities to improve performance and reduce power, setting the stage for a number of foundational shifts in how chips are developed, manufactured and updated in the future. AI—and machine learning and deep learning subsets—can be used to greatly improve the functional control and pow... » read more

From Physics To Applications


Jack Harding, president and CEO of eSilicon, sat down with Semiconductor Engineering to talk about the shift toward AI and advanced packaging, and the growing opportunities at 7nm at a time when Moore's Law has begun slowing down. What follows are excerpts of that conversation. SE: Over the past year, the industry has changed its focus from shrinking features and consolidation to all sorts o... » read more

Power Issues Grow For Cloud Chips


Performance levels in traditional or hyperscale data centers are being limited by power and heat caused by an increasing number of processors, memory, disk and operating systems within servers. The problem is so complex and intertwined, though, that solving it requires a series of steps that hopefully add up to a significant reduction across a system. But at 7nm and below, predicting exactly... » read more

Using ASICs For AI Inferencing


Flex Logix’s Cheng Wang looks at why ASICs are the best way to improve performance and optimize power and area for inferencing, and how to add flexibility into those designs to deal with constantly changing algorithms and data sets. https://youtu.be/XMHr7sz9JWQ » read more

Intel’s Next Move


Gadi Singer, vice president and general manager of Intel's Artificial Intelligence Products Group, sat down with Semiconductor Engineering to talk about Intel's vision for deep learning and why the company is looking well beyond the x86 architecture and one-chip solutions. SE: What's changing on the processor side? Singer: The biggest change is the addition of deep learning and neural ne... » read more

AI Architectures Must Change


Using existing architectures for solving machine learning and artificial intelligence problems is becoming impractical. The total energy consumed by AI is rising significantly, and CPUs and GPUs increasingly are looking like the wrong tools for the job. Several roundtables have concluded the best opportunity for significant change happens when there is no legacy IP. Most designs have evolved... » read more

Do Parallel Tools Make Sense?


Semiconductor Engineering sat down to talk about parallelization efforts within EDA with Andrea Casotto, chief scientist for Altair; Adam Sherer, product management group director in the System & Verification Group of Cadence; Harry Foster, chief scientist for Mentor, a Siemens Business; Vladislav Palfy, global manager for applications engineering at OneSpin; Vigyan Singhal, chief Oski for ... » read more

AI, ML Chip Choices


Flex Logix’s Cheng Wang talks about which types of chips work best for neural networks, AI and machine learning. https://youtu.be/k7OdP7B10o8 » read more

Pros, Cons Of ML-Specific Chips


Semiconductor Engineering sat down with Rob Aitken, an Arm fellow; Raik Brinkmann, CEO of OneSpin Solutions; Patrick Soheili, vice president of business and corporate development at eSilicon; and Chris Rowen, CEO of Babblelabs. What follows are excerpts of that conversation. To view part one, click here. Part two is here. SE: Is the industry's knowledge of machine learning keeping up with th... » read more

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