Name
Abstract | ||
|---|---|---|
The growing complexity of modern chips has caused an increasing share of the verification effort to shift towards post-silicon validation. This phase is challenged by poor observability, limited off-chip bandwidth, and complex, concurrent communication interfaces. Furthermore, pre-silicon verification and post-silicon validation methodologies are very different and share little information between them. As as result, the diagnosis and debugging of post-silicon failures is very much an ad-hoc and time-consuming task that is largely unable to leverage the vast body of design knowledge available in pre-silicon. We propose BiPeD, a novel methodology to identify the exact time and location of post-silicon bugs. During pre-silicon verification, BiPeD learns the correct behavior of a design's communication patterns. In post-silicon, this knowledge is used to detect errors by means of a reconfigurable hardware unit. When an error is detected, bug reproduction is not necessary: a diagnosis software algorithm analyzes information stored in the hardware unit to provide a wide range of debugging information. We show that our system provides accurate bug localization for a range of failures on the industrial-size OpenSPARC T2 design. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2429384.2429403 | Computer-Aided Design |
Keywords | Field | DocType |
post-silicon validation methodology,debugging information,verification effort,pre-silicon verification,design knowledge,post-silicon validation,post-silicon debugging,accurate bug localization,t2 design,post-silicon failure,post-silicon bug,databases,hardware,silicon,computer bugs,debugging,failure analysis,protocols,detectors | Design knowledge,Observability,Computer science,Software bug,Real-time computing,Electronic engineering,Software,Bandwidth (signal processing),OpenSPARC,Embedded system,Reconfigurable computing,Debugging | Conference |
ISSN | Citations | PageRank |
1092-3152 | 4 | 0.41 |
References | Authors | |
14 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrew DeOrio | 1 | 315 | 14.34 |
| Jialin Li | 2 | 247 | 18.58 |
| Valeria Bertacco | 3 | 1365 | 86.93 |