Hot Chips 2018: Nanotubes as DRAM from Nantero, a Live Website

Tuesday, August 21st, 2018 - DRAM, Teknologi

Hot Chips 2018: Nanotubes as DRAM from Nantero, a Live Website


01:44PM EDT – Lots of different types of ‘RAM’ have been in the news, most noticably Intel’s Optane memory and a couple of weeks ago at Flash Memory Summit we had the ‘MRAM’ Developer Day. At Hot Chips, Nantero is presentation about its new ‘NRAM’ technology, which uses carbon nanotubes. The talk is set to start at 10:45am PT.

01:47PM EDT – Carbon Nanotube Memory sounds sexy

01:47PM EDT – Go through Nanotubes to Memory in the talk

01:48PM EDT – A solution to replace DRAM

01:48PM EDT – ‘Memory-class storage’

01:48PM EDT – Nantero is like Arm but for memory technology

01:49PM EDT – Specific details about marketing will depend on Nantero’s customers

01:49PM EDT – Based on van-der-Walls effects

01:49PM EDT – Once connected, always connected

01:49PM EDT – Switched via electrostatic charges

01:50PM EDT – Use stochasic arrays of many nanotubes

01:50PM EDT – network of resistive elements

01:50PM EDT – an electrostatic force combines 1000 of cells together to lower resistance

01:50PM EDT – All the fun stuff happens at the bottom of the cell

01:51PM EDT – Part of the magic is how the nanotube is selected: length and diameter

01:51PM EDT – too long will short out the switch. too short will stand up

01:51PM EDT – Don’t let the carbon nanotubes at the top to move

01:51PM EDT – manufacturing process is simple

01:52PM EDT – Build the logic you need, on any process or geometry

01:52PM EDT – expose contacts, spin nanotube slurry, and bake it. Metal, etch, and seal

01:52PM EDT – 10-to-1 set to reset states in resistance

01:53PM EDT – Begun analysis of Multi-Level Cells

01:53PM EDT – Look at MLC after SLC in production

01:53PM EDT – Scales down to 15nm

01:54PM EDT – consistent performance over billions of cycles

01:54PM EDT – Only temperature sensitivity above 300C, drops to 300 years. Otherwise 10000 years

01:54PM EDT – Believe it will scale to 5nm at a minimum

01:55PM EDT – Even at 1nm, have enough nanotubes to still change

01:55PM EDT – It’s all about the length and diameter of nanotubes scaling

01:55PM EDT – Process agnostic

01:55PM EDT – on 28nm layer, 4Gb per layer in roughly 100mm2 die

01:55PM EDT – Also scale by adding layers

01:56PM EDT – Repeat nanotube deposit, metal, etch, deposit, metal, etch for layers

01:56PM EDT – Add layers of CNTs, or adding layers via TSVs

01:57PM EDT – Design for for DDR4 DRAM replacement device

01:57PM EDT – drop in replacement

01:57PM EDT – same timing, same perf, unlimited write endurance

01:57PM EDT – on 28nm, get 16Gb chip with 4 layers

01:57PM EDT – in a few years, easily 14nm or 7nm for 64 Gb / 256 Gb per die

01:57PM EDT – or add layers

01:58PM EDT – DDR4 to DDR5, whcih allows for additional die stacks

01:58PM EDT – Lots of capacity in every part

01:58PM EDT – NRAM is a storage class memroy

01:59PM EDT – NRAM is the only memory targeting a direct DRAM replacement

01:59PM EDT – unlimited endurance, same perf, better capacity, cheaper than DRAM

01:59PM EDT – Internal tiled architecture for memory

02:00PM EDT – Built in self-test and remapping logic for post-packaging repair

02:00PM EDT – SECDED engine in device

02:00PM EDT – in case problems with mass production – should increase yield and improve UX

02:01PM EDT – Aiming for DDR4 with ECC and to hit JEDEC standard on timings

02:01PM EDT – Decode logic in each tile with latching sense amplifiers

02:01PM EDT – Can do non-destructive read

02:01PM EDT – No things like pre-charge

02:01PM EDT – so faster 🙂

02:02PM EDT – Can now fit ECC into DDR4 timing easily due to no refresh

02:02PM EDT – 350ns to 0 ns

02:02PM EDT – DRAMs should be deterministic, but they’re not due to refresh

02:02PM EDT – The DRAM should be ready when you need it

02:03PM EDT – Every 2 microseconds, need to refresh for 15% of the time

02:03PM EDT – This cuts into bandwidth

02:03PM EDT – So this is three grades of speed in DRAM terms

02:03PM EDT – Can build standard memory modules. They just work


02:04PM EDT – For comparison, persistence memory through NVDIMM-N. Enables flash and power supply

02:04PM EDT – Requires buffers

02:04PM EDT – Half-DRAM and Half-Flash

02:05PM EDT – shutdown and startup time could be two minutes on NVDIMM-N

02:05PM EDT – NVDIMM-P is similar, but still non-deterministic

02:05PM EDT – Still need power, buffers

02:06PM EDT – Persistent memory such as NRAM means no reloading on power fail

02:06PM EDT – or limited

02:06PM EDT – helps with uptime

02:06PM EDT – Today, power fail means checkpointing reload. NRAM doesn’t need that

02:07PM EDT – Persistent memory is becoming more aware in software

02:07PM EDT – Persistent memory aware file systems and such

02:08PM EDT – All blocks and procedures are available for licencing

02:08PM EDT – Can be incorporated directly into silicon

02:08PM EDT – DRAM compatible front end possible

02:08PM EDT – On-the-fly ECC

02:09PM EDT – unlimited write endurance

02:09PM EDT – Memory-Class Storage

02:09PM EDT – Industry is ready

02:09PM EDT – Additional performance in DRAM mode

02:09PM EDT – Scaling in both stacks and process nodes

02:09PM EDT – Q&A Time

02:11PM EDT – Q: What you talk about is almost too good to be true. What am I missing? A: It does not go well with Peanut Butter or salsa. But seriously, we’ve built 1000s of test chips and we have profiled them. We haven’t built 16 Gb device yet, it’s up to the customer. Maybe it’s that 300C limit that’s the downside.

02:12PM EDT – Q: Do you have a metric for approximate energy per bit? A: I should have included it. Power conusmption has a major ripple effect. It runs off of the same power supplies, with the same or less energy as DRAM. 5 femto-joule per bit activation

02:13PM EDT – Q: A lot of data from individual die. Data over a large sample? A: We chose to pull single cell because it’s more readable. The accumulated data on the 5ns access time, that was over billions of cycles on billions of devices.

02:16PM EDT – Q: NVM device, but haven’t said about security? Encryption? Otherwise it’s not a drop-in. A: We have these conversations with customers, We’re an IP house – we do chip design. We had those discussions about each chip has encyption, but for the mainstream device, much like the NVDIMM-N, it’s up to the system guys. The strong message we have from customers is to not screw with it – they’ll deal with it. THey want dumb simple memory chips and their own security.

02:16PM EDT – Q: Alpha particle rate? A: These devices have been sent into space. We know about extremes, radiation. Nothing can you do to a nanotube to do something weird. We have electrostatic protection, nothing else seems to affect it.

02:18PM EDT – Q: You said nothing about the hammer to write the system. Said about alignment, but A: It’s a complex formulation, some under NDA. We can discuss about the nanotube selection – part of our secret source is about the CNT slurry. We build that and licence that – they use our proprietary technology to do nanotube selection. Tuned to the cell, the length and diameter has be tuned.

02:19PM EDT – Q: How do you flip it? A: Electrostatics. Voltage across a word line, a bit line, we have some proprietary technology to prevent sneak. Writes are faster than reads because you just throw it down the line.

02:19PM EDT – Q: When do you thin we can install these devices in these systems? 2018? 2019? 2020? A: 2-3 weeks ago Fujitsu announced they were taking CNT to mass market. So you can buy those next year or the year after. It’s all about fabrication and testing.

02:20PM EDT – That’s a wrap. A super interesting talk for sure. The next live Website is at 2pm PT about Arm’s Machine Learning Core.

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