Featured Research

from universities, journals, and other organizations

Design-for-Manufacturing Tool For Embedded SRAMs Transferred To Samsung Electronics

Date:
April 21, 2009
Source:
Interuniversity Microelectronics Centre (IMEC)
Summary:
IMEC successfully transferred MemoryVAM (Memory Variability Aware Modeling), the first EDA tool for statistical memory analysis, to Samsung Electronics. The tool predicts yield loss of SRAMs caused by the process variations of deep-submicron IC technologies.

The figure depicts a typical outcome of MemoryVAM for a memory of a partner company of IMEC. Correlations are preserved for both global and local variations of cycle time and read margin for both the CP netlist and the memory. In addition one can see a comparison to a corner-based simulation (crosses). Interestingly, the chip-chip fluctuations have large effect on the cycle time but a small effect on the read margin when compared to local variations. This is logical as the read margin is a voltage difference across a differential signal pair where device matching matters a lot.
Credit: IMEC

IMEC successfully transferred MemoryVAM (Memory Variability Aware Modeling), the first EDA tool for statistical memory analysis, to Samsung Electronics. The tool predicts yield loss of SRAMs caused by the process variations of deep-submicron IC technologies.

IMEC’s MemoryVAM is an essential tool to avoid already at design time the most likely reasons for failure, anticipating and correcting weak design spots before tape-out, and hence avoiding redesign spins after processing. The tool also provides key help to memory and system designers to estimate yield loss due to changes of for example cycle time, access time and power consumption (static/dynamic) caused by process variations.

“With MemoryVAM IMEC completes a missing steppingstone in industrial and academic state-of-the-art Design-For-Manufacturing flows which lacked such modeling capabilities for memories;” said Rudy Lauwereins, Vice President Smart Systems Technology Office at IMEC. “This is especially interesting for embedded SRAMs, which are considered to be the most sensitive component to process variations of today’s systems-on-chip. We are excited that the tool is now being successfully used by the product engineering design teams at Samsung Electronics.”

“With collaboration with IMEC, a new novel statistical analysis tool MemoryVAM has become available in our embedded SRAM design.” said Kyu-Myung Choi, Vice President of Design Technology Team at Samsung Electronics. “We expect that MemoryVAM will be helpful for parametric yield modeling of embedded SRAM design and for understanding the unknown gap between design and silicon results due to process variability in deep sub-micron technology below 45nm.”

MemoryVAM is part of IMEC’s Variability Aware Modeling (VAM) flow which is the first holistic flow capable of percolating process variations all the way from the process technology up to the System on a Chip (SoC) level. VAM enables to track the reasons for yield loss and the relative likelihood of such failure. Unlike most of the statistical analysis techniques, VAM is unique in its kind by accurately keeping track of all statistical process, design and environmental correlations tightly linked together and across abstraction levels.

MemoryVAM builds on IMEC’s revolutionary method to analyze performance metrics of semiconductor memories under process variations. The method requires mainly three input items. The first is a transistor level netlist description of a segment of the memory describing all circuitry involved from input to output. The second one is a set of parameters describing the internal architecture of the memory, thus how the memory is built from the segment information, including redundancy and error correction code infrastructure. The third one is information about the variability of the devices and interconnects used in the underlying technology. This information can be provided in either the form of statistical distributions of certain transistor parameters, scattered data obtained via statistical simulation of the device or just plain data set obtained via silicon measurements.

The power of MemoryVAM lies in the analysis of parameters of the memory that can be directly embedded in the input netlist by the designer. These are then used to carry out the implementation of the method, without requiring additional custom modeling steps from the user. The key to this strategy is the ability to complement the analysis of a nominal memory model under test with statistically sampled variants of the devices. This is done by using an in-house developed statistically enhanced Monte Carlo technique, although it also allows the usage of any other available enhanced sampling technique. With this novel and fast analytical technique, statistical information on the critical path percolates to the complete SRAM organization level, resulting in a realistic prediction of the yield as perceived by the memory tester and/or equivalent BIST (built-in-self-testing) technique.


Story Source:

The above story is based on materials provided by Interuniversity Microelectronics Centre (IMEC). Note: Materials may be edited for content and length.


Cite This Page:

Interuniversity Microelectronics Centre (IMEC). "Design-for-Manufacturing Tool For Embedded SRAMs Transferred To Samsung Electronics." ScienceDaily. ScienceDaily, 21 April 2009. <www.sciencedaily.com/releases/2009/04/090421080401.htm>.
Interuniversity Microelectronics Centre (IMEC). (2009, April 21). Design-for-Manufacturing Tool For Embedded SRAMs Transferred To Samsung Electronics. ScienceDaily. Retrieved August 23, 2014 from www.sciencedaily.com/releases/2009/04/090421080401.htm
Interuniversity Microelectronics Centre (IMEC). "Design-for-Manufacturing Tool For Embedded SRAMs Transferred To Samsung Electronics." ScienceDaily. www.sciencedaily.com/releases/2009/04/090421080401.htm (accessed August 23, 2014).

Share This




More Computers & Math News

Saturday, August 23, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Apple iPhone 6 Screen Hits Snag Ahead of Launch

Apple iPhone 6 Screen Hits Snag Ahead of Launch

Reuters - Business Video Online (Aug. 22, 2014) Reuters has learned Apple is scrambling to get enough screens ready for the iPhone 6. Sources say it's unclear whether this could delay the launch. Fred Katayama reports. Video provided by Reuters
Powered by NewsLook.com
Is Apple's iMessage Really Being Overrun By Spammers?

Is Apple's iMessage Really Being Overrun By Spammers?

Newsy (Aug. 21, 2014) A report says more than one third of all SMS spam over the past year came from a "single campaign" using iMessage and targeting iPhone users. Video provided by Newsy
Powered by NewsLook.com
Families Can Now Ask Twitter To Remove Photos Of Deceased

Families Can Now Ask Twitter To Remove Photos Of Deceased

Newsy (Aug. 20, 2014) In the wake of a high-profile harassment case, Twitter says family members can ask for photos of dying or dead relatives to be taken down. Video provided by Newsy
Powered by NewsLook.com
Ballmer Leaves Microsoft's Board, Has Advice For Nadella

Ballmer Leaves Microsoft's Board, Has Advice For Nadella

Newsy (Aug. 19, 2014) In a letter to Microsoft CEO Satya Nadella, Ballmer said he's leaving the board of directors and offered tips on how the company can be successful. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:
from the past week

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins