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Science applications preparing for the exascale era are increasingly exploring in situ computations comprising of simulation‐analysis‐reduction pipelines coupled in‐memory. Efficient composition and execution of such complex pipelines for a target platform is a codesign process that evaluates the impact and tradeoffs of various application‐ and system‐specific parameters. In this article, we describe...
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...
To meet the rising demands on high-performance computing, the number of computing nodes composing a high- performance computing system has been continuously growing. Simultaneously, the complexity of networks linking such computing nodes, or the interconnect, has also been increasing. Taking the scale-out of computing nodes in future high-performance computing systems into consideration, it is unrealistic...
Recently, researchers' and scientists' interest and concern to Internet of Things (IoT) have been remarkably increasing. A diversity of IoT devices such as mobile phones, sensors and even scientific measurement facilities have been connected to the Internet and then generating an enormous amount of data. From the demands on computational resources enough to analyze such data, the utilization of the...
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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