New USB Standards: Benefits And Incompatibilities


Just because it's a standard doesn't mean everything will work together, and this is especially evident with conflicting USB standards. David Shin, senior product marketing manager at Cadence Design Systems, explains where incompatibilities can crop up, why it's so difficult to control the different versions, and what's behind all this confusion. » read more

1 Megawatt Racks In Data Centers


The demand for performance in an AI data center is causing a huge spike in the amount of power being consumed. Within a rack are a half-dozen SoC components housed in different types of advanced packages and connected with an assortment of blazing-fast interface IP and optical signaling. Manmeet Walia, director of product management for mixed-signal PHY IP in the Synopsys Solutions Group, talks... » read more

New CPU Memory Module


Moving data has become the top challenge inside data centers. There is more data to process, more to move, and more to store and retrieve from memory. This is where small outline compression attached memory modules (SOCAMMs) fit in. Frank Ferro, group director for product management at Cadence, talks about the benefits of this next-gen modular low-power memory standard, how it compares with oth... » read more

Why More CPUs Are Needed For Agentic AI


The shift from generative AI to agentic AI will significantly increase the amount of compute power needed in data centers. Queries to search for and analyze data from multiple sources will be performed simultaneously by agents and without human intervention, rather than a single request from a live person. Jeff Defilippi, senior director of product management at Arm, talks about the impact of r... » read more

State Of The Market For Edge Silicon


The explosion of data and the rapid ramp of AI is causing significant changes in how chips are architected. At the edge, the key metrics are power, latency, and performance, but those can vary significantly by application and by workload. Steve Roddy, chief marketing officer at Quadric, talks about the need to balance performance and efficiency with flexibility for different applications, what ... » read more

Memory For AI At The Edge


Inferencing at the edge has very different needs than training large language models or large-scale inferencing in AI data centers. Many edge devices run on a battery. They're price-sensitive, and they are constrained by the physical area of the device. As a result, the amount of memory that can be packed into these devices is also limited. Steve Woo, Rambus fellow and distinguished inventor, t... » read more

New Performance Requirements For Audio


Demand for higher performance in audio is rising as human-machine interactions increase on the edge. That means more processing elements, and more challenges in keeping data consistent across those processors. Prakash Madhvapathy, director of product marketing and product management at Cadence, talks about the advantages of coherent designs, how that impacts security, and how DSPs are evolving ... » read more

Changes In Chip Architectures At The Edge


Edge computing is all about low latency, within a tight power budget, and with sufficient performance. This is very different from an AI data center, where the real focus is on data throughput between processor and memory. Achieving those goals requires a focus on what different processing elements bring to the table. Nigel Drego, co-founder and CTO of Quadric, talks about how these different c... » read more

LPDDR6: Not Just For Mobile Anymore


LPDDR memory has been almost synonymous with mobile devices, but starting with the new LPDDR6 specification released in July 2025 by JEDEC, it will begin showing up inside of data centers, as well, early next year. The key factors in various flavors of DRAM are bandwidth, capacity, and cost. HBM is the fastest, but it's also expensive, and it requires a 2.5D or 3.5D packaging approach. GDDR is ... » read more

Critical Factors For Storing Data In DRAM


DRAM is becoming more complicated to develop, and more difficult to manage inside AI data centers. In the past, latency, bandwidth, and capacity were the primary considerations. But as the amount of data that needs to be processed, moved, and stored continues to rise, a whole new set of factors is emerging. Steven Woo, fellow and distinguished inventor at Rambus, talks about latency under load,... » read more

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