Week In Review: Design, Low Power


M&A eSilicon will be acquired by Inphi Corporation and Synopsys. Inphi is acquiring the majority of the company, including the ASIC business and 56/112G SerDes design and related IP, for $216 million in both cash and the assumption of debt. Inphi expects to combine its DSP, TiA, Driver and SiPho products with eSilicon’s 2.5D packaging and custom silicon design capabilities for electro-optics... » read more

Speeding Up 3D Design


2.5D and 3D designs have garnered a lot of attention recently, but when should these solutions be considered and what are the dangers associated with them? Each new packaging option trades off one set of constraints and problems for a different set, and in some cases the gains may not be worth it. For other applications, they have no choice. The tooling in place today makes it possible to de... » read more

ML, Edge Drive IP To Outperform Broader Chip Market


The market for third-party semiconductor IP is surging, spurred by the need for more specific capabilities across a wide variety of markets. While the IP industry is not immune to steep market declines in semiconductor industry, it does have more built-in resilience than other parts of the industry. Case in point: The top 15 semiconductor suppliers were hit with an 18% decline in 2019 first-... » read more

Week In Review: Design, Low Power


eSilicon debuted its 7nm high-bandwidth interconnect (HBI)+ PHY IP, a special-purpose hard IP block that offers a high-bandwidth, low-power and low-latency wide-parallel, clock-forwarded PHY interface for 2.5D applications such as chiplets. HBI+ PHY delivers a data rate of up to 4.0Gbps per pin. Flexible configurations include up to 80 receive and 80 transmit connections per channel and up to 2... » read more

Long And Longer Reach SerDes – On The Road Again


We’ve had the pleasure of participating in two events over the past two weeks. I wouldn’t recommend doing two major shows back-to-back, but it has been exhilarating and quite interesting. Our “road trip” began last week in Mountain View for the second annual AI Hardware Summit. You’ve probably noticed you can go to an AI-related show every week (or more) if you like. The trick is to f... » read more

Opposites Attract: IP Standardization vs. Customization


Have you had a look lately at an autonomous driving SoC? Have you noticed, besides the cool machine learning stuff, the grocery list of third-party IP that goes into it? It is a long, long list, composed of pieces both big and small and quite diverse. For example, interface and peripheral PHYs and controllers, memories, on-chip interconnects, PVT monitors and PLLs. In some highly-publicized exa... » read more

3D Power Delivery


Getting power into and around a chip is becoming a lot more difficult due to increasing power density, but 2.5D and 3D integration are pushing those problems to whole new levels. The problems may even be worse with new packaging approaches, such as chiplets, because they constrain how problems can be analyzed and solved. Add to that list issues around new fabrication technologies and an emph... » 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

Chiplets: Open Market or Joint Venture?


By Dr. Carlos Macián, senior director AI Strategy & Products, eSilicon Corporation “It may prove to be more economical to build large systems out of smaller functions, which are separately packaged and interconnected.” — Gordon Moore, 1965 “Chiplet” has become a buzzword and like most of its kind, the success of the buzzword predates the widespread availability of the produ... » read more

Optimizing Power For Learning At The Edge


Learning on the edge is seen as one of the Holy Grails of machine learning, but today even the cloud is struggling to get computation done using reasonable amounts of power. Power is the great enabler—or limiter—of the technology, and the industry is beginning to respond. "Power is like an inverse pyramid problem," says Johannes Stahl, senior director of product marketing at Synopsys. "T... » read more

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