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TSHMEM: Shared-Memory Parallel Computing on Tilera Many-Core Processors

机译:TSHMEM:Tilera多核处理器上的共享内存并行计算

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With many-core processor architectures emerging, concerns arise regarding the productivity of numerous parallel programming tools, models, and languages as developers from a broad spectrum of science domains struggle to maximize performance and maintain correctness of their applications. Fortunately, a partitioned global address space (PGAS) programming model has demonstrated realizable performance and productivity potential for large parallel computing systems with distributed-memory architectures. One such PGAS approach is SHMEM, a lightweight, shared-memory programming library. Renewed interest for SHMEM has developed around Oppenheim, a recent community-led effort to produce a standardized specification for the SHMEM library amidst incompatible commercial implementations. This paper presents and evaluates the design of TSHMEM (short for TileSHMEM), a new OpenSHMEM library for the Tilera TILE-Gx8036 and TILEPro64 many-core processors. TSHMEM is built atop Tilera-provided libraries with key emphasis upon realizable performance with those libraries, demonstrated through micro benchmarking. Furthermore, SHMEM application portability is illustrated with two case studies. TSHMEM successfully delivers high performance with ease of programmability and portability for SHMEM applications on TILE-Gx and TILEPro architectures.
机译:随着许多核心处理器体系结构的出现,随着来自广泛科学领域的开发人员努力使性能最大化并保持其应用的正确性,人们对众多并行编程工具,模型和语言的生产率产生了担忧。幸运的是,分区全局地址空间(PGAS)编程模型已经证明了具有分布式内存体系结构的大型并行计算系统可实现的性能和生产力潜力。一种这样的PGAS方法是SHMEM,这是一种轻量级的共享内存编程库。围绕Oppenheim的SHMEM重新引起了人们的兴趣,这是最近由社区主导的努力,目的是在不兼容的商业实现中为SHMEM库生成标准化的规范。本文介绍并评估了TSHMEM(TileSHMEM的缩写)的设计,TSHMEM是Tilera TILE-Gx8036和TILEPro64多核处理器的新OpenSHMEM库。 TSHMEM建立在Tilera提供的库之上,重点放在这些库的可实现性能上,通过微基准测试证明了这一点。此外,通过两个案例研究说明了SHMEM应用程序的可移植性。 TSHMEM为TILE-Gx和TILEPro架构上的SHMEM应用程序成功地提供了易于编程和可移植的高性能。

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