DYCE: A Resilient Shared Memory Paradigm for Heterogenous Distributed Systems without Memory Coherence

Ulrich Finkler, H. Franke, David S. Kung
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引用次数: 1

Abstract

Parallel programming paradigms are commonly characterized by the core metrics of scalability, memory use, ease of use, hardware requirements and resiliency. Increasingly the support of heterogeneous environments, for example a mix of CPUs and accelerators, are of interest. Analysis of the semantics of different classes of parallel programming paradigms and their cost leads to DYCE (Distributed Yet Common Environment), a shared memory, rich but hardware friendly, race and deadlock free parallel programming paradigm that allows for resiliency without the need for explicit check-pointing code. Pointer based structures that span the memory of multiple heterogeneous compute devices are possible. Importantly, data exchange is independent of the specific data structures and does not require serialization and deserialization code, even for data structures such as a dynamic linked radix tree of strings. The analysis shows that DYCE does not require coherence from the system and thus can be executed with near minimal overhead and hardware requirements, including the page table cost for large unified address spaces that span many devices. We demonstrate efficacy with a prototype.
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无内存一致性的异构分布式系统的弹性共享内存范式
并行编程范例通常以可伸缩性、内存使用、易用性、硬件需求和弹性等核心指标为特征。对异构环境(例如cpu和加速器的混合)的支持越来越受到关注。对不同类型的并行编程范例的语义和它们的成本的分析导致了DYCE(分布式公共环境),一个共享内存,丰富但硬件友好,无竞争和死锁的并行编程范例,允许弹性而不需要显式的检查点代码。跨越多个异构计算设备的内存的基于指针的结构是可能的。重要的是,数据交换独立于特定的数据结构,并且不需要序列化和反序列化代码,即使对于字符串的动态链接基数树这样的数据结构也是如此。分析表明,DYCE不需要系统的一致性,因此可以在几乎最小的开销和硬件要求下执行,包括跨许多设备的大型统一地址空间的页表成本。我们用一个原型来证明有效性。
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