加速联邦应用中的通信：透明对象代理
Accelerating Communications in Federated Applications with Transparent Object Proxies
AI总结：
本文提出一种将按引用传递扩展到分布式应用的编程范式，通过ProxyStore系统实现透明对象代理，解耦控制流与数据流，降低跨云、HPC和边缘系统数据传递成本，并经基准测试和实际应用验证其高效性。
摘要：
网络、加速器和云服务的进步鼓励程序员重新考虑在哪里进行计算——例如，当快速网络使得在远程加速器上计算尽管增加了延迟但仍具成本效益时。工作流和云托管的无服务器计算框架可以管理跨越云、高性能计算（HPC）和边缘系统联邦集合的多步计算，但通过云存储在计算步骤之间传递数据可能会产生高昂的成本。在这里，我们通过一种新的编程范式克服了这一障碍，该范式通过将按引用传递模型扩展到分布式应用，将控制流与数据流解耦。我们描述了ProxyStore，一个通过提供对象代理来实现这一范式的系统，这些代理充当具有即时解析的广域对象引用。这种代理模型使数据生产者能够单方面、透明且高效地将数据传递给本地和远程消费者。我们通过合成基准测试和真实世界的科学应用，在各种计算平台上展示了该模型的好处。
英文摘要：
Advances in networks, accelerators, and cloud services encourage programmers to reconsider where to compute -- such as when fast networks make it cost-effective to compute on remote accelerators despite added latency. Workflow and cloud-hosted serverless computing frameworks can manage multi-step computations spanning federated collections of cloud, high-performance computing (HPC), and edge systems, but passing data among computational steps via cloud storage can incur high costs. Here, we overcome this obstacle with a new programming paradigm that decouples control flow from data flow by extending the pass-by-reference model to distributed applications. We describe ProxyStore, a system that implements this paradigm by providing object proxies that act as wide-area object references with just-in-time resolution. This proxy model enables data producers to communicate data unilaterally, transparently, and efficiently to both local and remote consumers. We demonstrate the benefits of this model with synthetic benchmarks and real-world scientific applications, running across various computing platforms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
