Verification of transactional memory in POWER8
Allon Adir, Dave Goodman, et al.
DAC 2014
Reaching hard-to-reach coverage events is a difficult task that requires both time and expertise. Data-driven coverage directed generation (CDG) can assist in the task when the coverage events are part of a structured coverage model, but is a priori less useful when the target events are singular and not part of a model. We present a data-driven CDG technique based on Bayesian networks that can improve the coverage of cross-product coverage models. To improve the capability of the system, we also present virtual coverage models as a means for enabling data-driven CDG to reach singular events. A virtual coverage model is a structured coverage model (e.g., cross-product coverage) defined around the target event, such that the target event is a point in the structured model. The CDG system can exploit this structure to learn how to reach the target event from covered points in the structured model. A case study using CDG and virtual coverage to reach a hard-to-reach event in a multi-processor system demonstrates the usefulness of the proposed method. © Springer-Verlag 2009.
Allon Adir, Dave Goodman, et al.
DAC 2014
Eyal Bin, Roy Emek, et al.
IBM Systems Journal
Shady Copty, Shai Fine, et al.
Theoretical Computer Science
Amir Nahir, Avi Ziv, et al.
DAC 2006