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首页> 外文会议>Parallel, Distributed and Network-Based Processing (PDP), 2012 20th Euromicro International Conference on >Dynamic Serialization: Improving Energy Consumption in Eager-Eager Hardware Transactional Memory Systems
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Dynamic Serialization: Improving Energy Consumption in Eager-Eager Hardware Transactional Memory Systems

机译：动态序列化：改善渴望的硬件事务存储系统中的能耗

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摘要

In the search for new paradigms to simplify multithreaded programming, Transactional Memory (TM) is currently being advocated as a promising alternative to deadlock-prone lock-based synchronization. In this way, future many-core CMP architectures may need to provide hardware support for TM. On the other hand, power dissipation constitutes a first class consideration in multicore processor designs. In this work, we propose Dynamic Serialization (DS) as a new technique to improve energy consumption without degrading performance in applications with conflicting transactions. Our proposal, which is implemented on top of a hardware transactional memory system with an eager conflict management policy, detects and serializes conflicting transactions dynamically. Particularly, in case of conflict one transaction is allowed to continue whilst the rest are completely stalled. Once the executing transaction has finished it wakes up several of the stalling transactions. This brings important benefits in terms of energy consumption due to the reduction in the amount of wasted work that DS implies. Results for a 16-core CMP show that Dynamic Serialization obtains reductions of 10% on average in energy consumption (more than 20% in high contention scenarios) without affecting, on average, execution time.
机译：在寻找简化多线程编程的新范例时，当前提倡使用事务性内存（Transactional Memory，TM）作为有死锁倾向的基于锁的同步的有希望的替代方法。这样，未来的多核CMP架构可能需要为TM提供硬件支持。另一方面，功耗是多核处理器设计中的首要考虑因素。在这项工作中，我们提出动态序列化（DS）作为一种新技术，以在不降低具有冲突事务的应用程序的性能的情况下提高能耗。我们的建议是在具有紧急冲突管理策略的硬件事务存储系统之上实施的，可以动态检测并序列化冲突事务。特别是在发生冲突的情况下，允许一笔交易继续进行，而其余交易则完全停止。一旦执行的事务完成，它将唤醒几个停滞的事务。由于减少了DS意味着浪费的工作量，因此在能耗方面带来了重要的好处。 16核CMP的结果表明，动态序列化平均降低了10％的能耗（在高竞争情况下，降低了20％以上），而平均而言没有影响执行时间。

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