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Carnegie Mellon University, Pittsburgh, PA, USA, Google Research, New York City, New York, USA
CMU Machine Learning2
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渭STM achieves high performance without sacrificing safety or usability, allowing for general data types and deferred aborts in transactions.
Even with adaptive adversaries and write contention, practical concurrent primitives can achieve logarithmic latency using only constant hardware resources.
