Rochester Memory Hardware Error Research Project

Our research focuses on the characteristics of memory hardware errors and their implications on software systems. A plethora of research works can be found on memory fault tolerance. Often times researchers use accelerated tests in their controlled environments to collect data. We have taken a different approach to conduct field tests that monitor computers in real time and record the actual errors happening on them.

Memory errors can be categorized as soft errors and hard errors. Soft errors are also known as transient errors, which refer to those errors that are caused by environmental factors only and would not have lasting effects on memory hardware. Hard errors (or permanent errors) include those that are due to real hardware defects. We discovered that in each of our measured environments, the soft error rates are orders of magnitude lower than previously reported on a per Mbit basis. In the server farm at Ask.com, we found quite a few hard errors. We made some error rate/pattern analysis in our USENIX ATC'07 and HotDep'07 papers. Our USENIX ATC'10 paper uses the collected data to predict the whole memory system failure rate/pattern given different ECC schemes and maintenance strategies.

Publications:

Project Members:

Renzo Bustamante
Michael Huang
Xin Li (Now at Google)
Anarb Sarkar
Kai Shen
Ruohuang Zheng

Error Data Download:

We are publicly releasing the memory error data collected during our research. Our raw data file can be found in here. This file is of a csv format, which can be recognized by many software for data analysis purposes. We provide a brief description of the fields.

Some necessary detailed facts you should notice:

We are a participant of USENIX computer failure data repository. You can find more failure data in addition to ours following this link.

Support:

This project is supported in part by the National Science Foundation under Grant No. 1255729 (Link to the award abstract) and previously under Grant No. 0448413 (Link to the award abstract). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

This project is also supported in part by the Semiconductor Research Corporation (SRC) under Contract No. 2013-HJ-2405.