Lots of great information came out of the two days of workshops in Japan recently organized by the SOI Consortium. Some of the presentations are now posted on the consortium website (get them here).
The first day (held in Yokohama and sponsored by Silvaco) focused on FD-SOI and RF-SOI design. The second day (held at U. Tokyo) focused on More than Moore (especially silicon photonics, MEMS & sensors), and the SOI manufacturing ecosystem.
The 1st day panel discussion was so interesting we’ll give it a post of its own, then follow up with round-ups of the presentations from both days.
The morning panel discussion on end-user deployment for FD and RF-SOI was moderated by SOI Consortium Executive Director Giorgio Cesana. GF’s CTO Subi Kengeri led off saying that that 2017 had been the year of FD-SOI adoption. Samsung Director Adam Lee noted that in the beginning nobody believed it would get traction, but now everybody does, and Samsung is commercializing it: chips coming out this year will ramp in volume in 2019.
VeriSilicon CEO Wayne Dai said he sees great potential in IoT, where the volumes are high but fragmented. In IoT, he said, you need RF, but you really only need very high performance about 20% of the time, which is a perfect fit for FD-SOI.
ST Director John Carey noted that ST’s been using FD-SOI since 2014. They’ve fabbed products for cryptocurrency and infrastructure. Now in their second and third generations of designing with it, they’ve got some big FD-SOI chips coming out next year with embedded memory and RF. He sees it being particularly successful in mmWave, automotive and IoT.
The conversation then shifted to RF-SOI. Mostofa Emam, CEO of Incize, explained that since RF-SOI is already in every smart phone, it’s in a different situation from FD-SOI. The emphasis here is now on adding more blocks. “RF is an art,” he said. “It takes an artist. You need talented artists and tools.” One of the biggest challenges for fabs that are newcomers is models – not just at the transistor level, but also at the substrate level. The big players have addressed this, but Incize is working to support more foundries with new, innovative approaches, and helping them develop robust PDKs. The industry needs more good RF designers as well as better RF design flow, he concluded.
Coming back to FD-SOI, Cesana asked about non-volatile memory (NVM). Samsung’s Lee said they’ve already got NVM options including eMRAM for 28nm, and customers are now requesting eMRAM PDKs for the next node (18FDS). ST’s Kengeri added eNVM is important for FD-SOI, especially since flash is not scaling. While there are lots of options, MRAM gives you all the value, and in FD-SOI it only adds three more mask steps, so cost savings are maintained.
With respect to local computing for AI with FD-SOI, everyone agreed on the importance of the edge. In addition to RF, FD-SOI gives you density even at 28nm, explained Carey. You can manually control power with back biasing, so you get something very flexible, especially for NB-IoT applications where the battery will have to last for 10 years. In fact Kengeri sees FD-SOI as enabling fog/edge computing.
The next question was about 5G: which applications would we be seeing first, and how does FD-SOI help? Lee said Samsung’s seeing it for apps up to 10GHz as well as mmWave. Customers are telling them they want FD-SOI for technical reasons.
Kengeri expanded on that point, saying it comes down to fundamental physics: gate resistance, capacitance, mismatch. FD-SOI has lower Vmin and better Fmax compared to FinFETs, and that’s what tier-one players want.
Carey brought it back to RF-SOI (noting that ST’s introducing a 45nm version), which supports a large number of elements and increased complexity with smaller power budgets. Emam then asked the foundry guys about mmWave. Substrates won’t be the bottleneck he said, so what’s the FD-SOI/mmWave roadmap? Kengeri responded that GF’s ready. Lee said Samsung is also ready, and you’d see it next year on handsets. Samsung has engaged with customers on 30GHz for the middle of next year, he added: it’s qualified. Carey said ST sees it first in consumer premises equipment that’s connected by satellite.
Cesana then asked about image sensor processors (ISPs), noting that analyst Handel Jones has said this is a big opportunity for FD-SOI. You can do 3D integration with sensors, but heat makes noise, so you need technology that decreases heat production and doesn’t give you hotspots (which would be visible in the image). Kengeri pointed to challenges in power density, thermal envelopes and the RTS (random telegraph noise signal). Although there are a lot of options, FD-SOI plays well for thermals and noise, so GF sees a good opportunity here. Dai added that the industry needs volume applications for FD-SOI, and ISPs need to bring more logic closer to the camera. And he concurred that you need FD-SOI for the thermals: it’s very important.
In closing, Dai noted that as a design house, “We walk on two legs: FinFETs and FD-SOI.” 28, 22, 18 and 12nm FD-SOI all enable differentiation. In particular, you need something between 20nm and 7nm: FD-SOI is here. Asked about Japan in particular, Dai said beyond automotive he saw lots of potential in ULP for AVR. Kengeri added that for any applications besides performance-at-any-cost, FD-SOI is the right enabler.