QED: Scalable Verification of Hardware Memory Consistency Article Swipe
Gokulan Ravi
,
Xiaokang Qiu
,
Mithuna Thottethodi
,
T. N. Vijaykumar
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2404.03113
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2404.03113
Memory consistency model (MCM) issues in out-of-order-issue microprocessor-based shared-memory systems are notoriously non-intuitive and a source of hardware design bugs. Prior hardware verification work is limited to in-order-issue processors, to proving the correctness only of some test cases, or to bounded verification that does not scale in practice beyond 7 instructions across all threads. Because cache coherence (i.e., write serialization and atomicity) and pipeline front-end verification and testing are well-studied, we focus on the memory ordering in an out-of-order-issue processor's load-store queue and the coherence interface between the core and global coherence. We propose QED based on the key notion of observability that any hardware reordering matters only if a forbidden value is produced. We argue that one needs to consider (1) only directly-ordered instruction pairs -- transitively non-redundant pairs connected by an edge in the MCM-imposed partial order -- and not all in-flight instructions, and (2) only the ordering of external events from other cores (e.g.,invalidations) but not the events' originating cores, achieving verification scalability in both the numbers of in-flight memory instructions and of cores. Exhaustively considering all pairs of instruction types and all types of external events intervening between each pair, QED attempts to restore any reordered instructions to an MCM-complaint order without changing the execution values, where failure indicates an MCM violation. Each instruction pair's exploration results in a decision tree of simple, narrowly-defined predicates to be evaluated against the RTL. In our experiments, we automatically generate the decision trees for SC, TSO, and RISC-V WMO, and illustrate automatable verification by evaluating a substantial predicate against BOOMv3 implementation of RISC-V WMO, leaving full automation to future work.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2404.03113
- https://arxiv.org/pdf/2404.03113
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394007163
All OpenAlex metadata
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https://openalex.org/W4394007163Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2404.03113Digital Object Identifier
- Title
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QED: Scalable Verification of Hardware Memory ConsistencyWork title
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preprintOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-04-03Full publication date if available
- Authors
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Gokulan Ravi, Xiaokang Qiu, Mithuna Thottethodi, T. N. VijaykumarList of authors in order
- Landing page
-
https://arxiv.org/abs/2404.03113Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2404.03113Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2404.03113Direct OA link when available
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Scalability, Computer science, Consistency (knowledge bases), Computer hardware, Computer architecture, Embedded system, Parallel computing, Operating system, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| abstract_inverted_index.processor's | 79 |
| abstract_inverted_index.processors, | 28 |
| abstract_inverted_index.scalability | 165 |
| abstract_inverted_index.substantial | 257 |
| abstract_inverted_index.Exhaustively | 177 |
| abstract_inverted_index.experiments, | 237 |
| abstract_inverted_index.instructions | 50, 173, 200 |
| abstract_inverted_index.transitively | 127 |
| abstract_inverted_index.verification | 22, 41, 65, 164, 253 |
| abstract_inverted_index.MCM-complaint | 203 |
| abstract_inverted_index.automatically | 239 |
| abstract_inverted_index.instructions, | 144 |
| abstract_inverted_index.non-intuitive | 12 |
| abstract_inverted_index.non-redundant | 128 |
| abstract_inverted_index.observability | 101 |
| abstract_inverted_index.serialization | 59 |
| abstract_inverted_index.shared-memory | 8 |
| abstract_inverted_index.well-studied, | 69 |
| abstract_inverted_index.implementation | 261 |
| abstract_inverted_index.in-order-issue | 27 |
| abstract_inverted_index.directly-ordered | 123 |
| abstract_inverted_index.narrowly-defined | 227 |
| abstract_inverted_index.out-of-order-issue | 6, 78 |
| abstract_inverted_index.(e.g.,invalidations) | 156 |
| abstract_inverted_index.microprocessor-based | 7 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |