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Transactional memory has been receiving much attention from both academia and industry. In transactional memory, program code is split into transactions, blocks of code that appear to execute atomically. Transactions are executed speculatively and the speculative execution is supported through data versioning and conflict detection and resolution mechanisms. Lazy versioning makes aborts fast but penalizes commits, whereas eager versioning makes commits fast but penalizes aborts. In this paper, we present an adaptive versioning approach that dynamically switches between eager and lazy versioning at runtime based on appropriate system parameters so that the performance of a transactional memory system is always better than that is obtained using either eager or lazy versioning individually. We implemented our adaptive versioning approach in the latest TinySTM distribution and extensively evaluated it through 5 micro-benchmarks and 8 complex benchmarks from STAMP and STAMPEDE suites. The results show significant benefits of our approach, giving performance improvements as much as 6.3x for execution time and as much as 170x for number of aborts.
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Jenga: Efficient Fault Tolerance for Stacked DRAM
In this paper, we introduce Jenga, a new scheme for protecting 3D DRAM, specifically high bandwidth memory (HBM), from failures in bits, rows, banks, channels, dies, and TSVs. By providing redundancy at the granularity of a cache block—rather than across blocks, as in the current state of the art—Jenga achieves greater error-free performance and lower error recovery latency. We show that Jenga’s runtime is on average only 1.03× the runtime of our Baseline across a range of benchmarks. Additionally, for memory intensive benchmarks, Jenga is on average 1.11× faster than prior work.
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- Award ID(s):
- 1717602
- PAR ID:
- 10063748
- Date Published:
- Journal Name:
- IEEE International Conference on Computer Design (ICCD 2017)
- Page Range / eLocation ID:
- 361 to 368
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICCD.2017.62
