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Recent rapid scale out of high performance computing systems has rapidly and continuously increased the scale and complexity of the interconnects. As a result, current static and over-provisioned interconnects are becoming cost-ineffective. Against this background, we have been working on the integration of network programmability into the interconnect control, based on the idea that dynamically controlling...
The MPI reduction operation such as MPI_Reduce and MPI_Allreduce are frequently used and time-consuming operations. The performance enhancement of these operations can substantially speed up large-scale parallel applications. In this paper, a greedy based MPI_Reduce algorithm called Greedy Shortest Binomial Tree (GSBT) is proposed. This proposed algorithm leverages SDN technology and OpenFlow network...
High performance computing is required for Big Science application because the proliferation and huge amount of scientific data that needs to be analyzed is a serious problem. Traditionally, network resources were generally assumed as a static resource users cannot control on demand. By integrating network programmability to every stage of a scientific workflow, this study explores a next-generation...
In general, modern high-performance computing systems are built as cluster systems. We have been investigating the feasibility of optimizing MPI communications by integrating the dynamic network control realized by SDN. In this paper, we present a concept of a generic SDN enhanced MPI framework, an application-aware network control mechanism specifically for MPI applications.
Nowadays, supercomputers play an essential role in high-performance computing. In general, modern supercomuputers are built as a cluster system, which is a system of multiple computers interconnected on a network. In coding a parallel program on such a cluster system, MPI (Message Passing Interface) is utilized. In this paper, we aim to reduce the execution time of MPI Allreduce, a frequently used...
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