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Hybrid Distributed Shared Memory Space in Multi-core Processors

机译：多核处理器中的混合分布式共享内存空间

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On multi-core processors, memories are preferably distributed and supporting Distributed Shared Memory (DSM) is essential for the sake of reusing huge amount of legacy code and easy programming. However, the DSM organization imports the inherent overhead of translating virtual memory addresses into physical memory addresses, resulting in negative performance. We observe that, in parallel applications, different data have different properties ( private or shared ). For the private data accesses, it’s unnecessary to perform Virtual-to-Physical address translations. Even for the same datum, its property may be changeable in different phases of the program execution. Therefore, this paper focuses on decreasing the overhead of Virtualto- Physical address translation and hence improving the system performance by introducing hybrid DSM organization and supporting run-time partitioning according to the data property. The hybrid DSM organization aims at supporting fast and physical memory accesses for private data and maintaining a global and single virtual memory space for shared data. Based on the data property of parallel applications, the run-time partitioning supports changing the hybrid DSM organization during the program execution. It ensures fast physical memory addressing on private data and conventional virtual memory addressing on shared data, improving the performance of the entire system by reducing virtual-to-physical address translation overhead as much as possible. We formulate the run-time partitioning of hybrid DSM organization in order to analyze its performance. A real DSM based multi-core platform is also constructed. The experimental results of real applications show that the hybrid DSM organization with run-time partitioning demonstrates performance advantage over the conventional DSM counterpart. The percentage of performance improvement depends on problem size, way of data partitioning and computation/communication ratio of parallel applications, network size of the system, etc. In our experiments, the maximal improvement is 34.42%, the minimal improvement 3.68%.
机译：在多核处理器上，内存最好是分布式的，支持分布式共享内存（DSM）对于重用大量遗留代码和易于编程至关重要。但是，DSM组织会导入将虚拟内存地址转换为物理内存地址的固有开销，从而导致性能下降。我们观察到，在并行应用程序中，不同的数据具有不同的属性（private或shared）。对于私有数据访问，无需执行虚拟到物理地址转换。即使对于相同的基准，其属性也可能在程序执行的不同阶段中发生变化。因此，本文着重于通过引入混合DSM组织并根据数据属性支持运行时分区来减少虚拟到物理地址转换的开销，从而提高系统性能。混合DSM组织旨在支持对私有数据的快速和物理内存访问，并为共享数据维护全局和单个虚拟内存空间。基于并行应用程序的数据属性，运行时分区支持在程序执行期间更改混合DSM组织。它确保了对私有数据的快速物理内存寻址和对共享数据的常规虚拟内存寻址，从而通过尽可能减少虚拟到物理地址转换的开销来提高整个系统的性能。我们制定混合DSM组织的运行时分区，以分析其性能。还构建了一个基于DSM的真实多核平台。实际应用程序的实验结果表明，具有运行时分区的混合DSM组织表现出优于常规DSM同类产品的性能优势。性能提高的百分比取决于问题的大小，数据划分的方式以及并行应用程序的计算/通信比率，系统的网络大小等。在我们的实验中，最大改进为34.42％，最小改进为3.68％。

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