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Reversi: Post-silicon validation system for modern microprocessors
Verification remains an integral and crucial phase of todaypsilas microprocessor design and manufacturing process. Unfortunately, with soaring design complexities and decreasing time-to-market windows, todaypsilas verification approaches are incapable of fully validating a microprocessor before its...
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Main Authors: | , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | Verification remains an integral and crucial phase of todaypsilas microprocessor design and manufacturing process. Unfortunately, with soaring design complexities and decreasing time-to-market windows, todaypsilas verification approaches are incapable of fully validating a microprocessor before its release to the public. Increasingly, post-silicon validation is deployed to detect complex functional bugs in addition to exposing electrical and manufacturing defects. This is due to the significantly higher execution performance offered by post-silicon methods, compared to pre-silicon approaches. Validation in the post-silicon domain is predominantly carried out by executing constrained-random test instruction sequences directly on a hardware prototype. However, to identify errors, the state obtained from executing tests directly in hardware must be compared to the one produced by an architectural simulation of the designpsilas golden model. Therefore, the speed of validation is severely limited by the necessity of a costly simulation step. In this work we address this bottleneck in the traditional flow and present a novel solution for post-silicon validation that exposes its native high performance. Our framework, called Reversi, generates random programs in such a way that their correct final state is known at generation time, eliminating the need for architectural simulations. Our experiments show that Reversi generates tests exposing more bugs faster, and can speed up post-silicon validation by 20x compared to traditional flows. |
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ISSN: | 1063-6404 2576-6996 |
DOI: | 10.1109/ICCD.2008.4751878 |