WP_Term Object
(
    [term_id] => 24
    [name] => TSMC
    [slug] => tsmc
    [term_group] => 0
    [term_taxonomy_id] => 24
    [taxonomy] => category
    [description] => 
    [parent] => 158
    [count] => 414
    [filter] => raw
    [cat_ID] => 24
    [category_count] => 414
    [category_description] => 
    [cat_name] => TSMC
    [category_nicename] => tsmc
    [category_parent] => 158
    [is_post] => 1
)

When Talking About IoT, Don’t Forget Memory

When Talking About IoT, Don’t Forget Memory
by Tom Simon on 11-13-2015 at 7:00 am

Memory is a big enough topic that it has its own conference, Memcon, which recently took place in October. While I was there covering the event for SemiWiki.com I went to the TSMC talk on memory technologies for the IoT market. Tom Quan, Director of the Open Innovation Platform (OIP) at TSMC was giving the talk. IoT definitely has special needs for memory because of the need for low power, data persistence and security.

Tom Quan started the talk with an informative view of the IoT market. I have heard a lot of IoT overviews, but I listed with a keen ear to learn how TSMC views this market. Since 1991 there have been three big growth drivers for the semiconductor industry. IoT promises to be the fourth.

The first was personal computing which saw 7X growth from 1991 to 2000. Next came mobile handsets demonstrating 9X growth from 1997 to 2007. Last we have smart mobile computing, which lumps together mobile computing, internet, mobile communications, and sensing. This segment grew by 12X from 2007 to 2014. Clearly the IoT is the next big thing and will likely continue this accelerating this trend. The conclusion is that IoT will be the next big growth driver for the semiconductor industry. The sum of PC’s smartphones, tablets and IoT is expected to approach 20 billion units by 2018, compared to roughly 8 billion total today. The last year there is hard data was 2013 with ~5 billion units.


IoT is really an extension of mobile computing. Tom’s talk broke it down into the four umbrella categories of smart wearables, smart cars, smart home and smart city. It will consist of smart devices on smart things. Think of health sensors, gesture and proximity, chemical sensors, positional sensors and more. So where do today’s technologies stand as far as meeting the requirements of the IoT?

Probably every metric for design will be stressed by IoT. Unit volumes will go from the single-digit billions of the PC era to hundreds of billions in the IoT era ahead. Operating times for devices will need to go from hours to years. This in turn demands that the hundreds of watts that PC’s used transform into nano watts for edge sensors and the like. Additionally, new technologies, materials and architectures will need to be developed.

To make these transitions everything will need to be moved forward technologically. The slide below shows how this might work for the wearables segment


A huge part of this will involve embedded memory. Right now SRAM is used primarily for volatile memory. There are a number of solutions for non-volatile memory (NVM), including several future technologies that are very promising. The two major axes for NVM are density (size) and endurance (re-writability). Small sizes that do not need high endurance are things like configuration bits, analog trim info, and calibration data. The work well with one time programmable (OTP) approaches.

Even some boot code can be stored in OTP when it is configured to simulate re-writable memory. However, the number of re-writes will be limited as the non-reusable bit cells are utilized.

Flash and eeprom are good for applications that require larger sizes and more re-write endurance. But they come with the penalty of requiring additional layers or special processes.

Tom suggested that magneto-resistive RAM (MRAM) is one technology that shows some promise. It harkens back to the old core memories, but is scaled to nanometer size. Of the two original approaches for MRAM only the spin-transfer torque (STT) technology has been proven to scale well. There are two competing approaches for this: In-Plane and Perpendicular. MRAM using STT is very fast and uses low power. So it looks very promising as a NVM replacement that can also be used for SRAM replacement.

Another area of promise for future NVM solutions is resistive RAM or RRAM which uses the memristor effect in solid state dielectrics. There are several flavors of this technology being researched. But RRAM is not as far along commercially as MRAM is. However, this is an active area of research and the frequently use high-k dielectric HfO2 material has been discovered to work as RRAM.

Advances in NVM will have a huge impact on IoT. Power savings from having readily available persistent storage will open up new application areas. Think of not having to save system RAM when entering sleep. To further save power TSMC continues to add ultra low power processes to its existing process nodes. IoT will be driven in large part by technologies that allow edge node devices to be power sipping.

For more info on TSMC’s Open Innovation Platform look here.