The proceedings contain 10 papers. The special focus in this conference is on Software Challenges to Exascale Computing. The topics include: High level file system and parallel I/O optimization of DNS code;Hybrid para...
ISBN:
(纸本)9789811377280
The proceedings contain 10 papers. The special focus in this conference is on Software Challenges to Exascale Computing. The topics include: High level file system and parallel I/O optimization of DNS code;Hybrid parallelization of particle in cell monte carlo collision (PIC-MCC) algorithm for simulation of low temperature plasmas;a review of dimensionality reduction in high-dimensional data using multi-core and many-core architecture;Performance analysis of computational neuroscience software NEURON on knights corner many core processors;Overcoming MPI communication overhead for distributed community detection;Analyzing IO usage patterns of user jobs to improve overall HPC system efficiency;scalable software infrastructure for integrating supercomputing with volunteer computing and cloud computing;high-level approaches for leveraging deep-memory hierarchies on modern supercomputers.
The proceedings contain 9 papers. The topics discussed include: teaching HPC systems and parallel programming with small-scale clusters;Jupyter notebooks and user-friendly HPC access;SMPI courseware: teaching distribu...
ISBN:
(纸本)9781728101903
The proceedings contain 9 papers. The topics discussed include: teaching HPC systems and parallel programming with small-scale clusters;Jupyter notebooks and user-friendly HPC access;SMPI courseware: teaching distributed-memory computing with MPI in simulation;employing student retention strategies for an introductory GPU programming course;filling the gap between education and industry: evidence-based methods for introducing undergraduate students to HPC;evaluating the wide area classroom after 10,500 HPC students;a one year retrospective on a MOOC in parallel, concurrent, and distributed programming in Java;towards developing a repository of logical errors observed in parallel code for teaching ode correctness;and peachy parallel assignments (EduHPC 2018).
Peachy parallel Assignments are a resource for instructors teaching parallel and distributed programming. These are high-quality assignments, previously tested in class, that are readily adoptable. This collection of ...
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ISBN:
(纸本)9781728101903
Peachy parallel Assignments are a resource for instructors teaching parallel and distributed programming. These are high-quality assignments, previously tested in class, that are readily adoptable. This collection of assignments includes implementing a subset of OpenMP using pthreads, creating an animated fractal, image processing using histogram equalization, simulating a storm of high-energy particles, and solving the wave equation in a variety of settings. All of these come with sample assignment sheets and the necessary starter code.
The proceedings contain 122 papers. The topics discussed include: the CMS TIER1 at JINR: five years of operations;CRIC: the information system for LHC distributed computing;the atlas event index and its evolution base...
The proceedings contain 122 papers. The topics discussed include: the CMS TIER1 at JINR: five years of operations;CRIC: the information system for LHC distributed computing;the atlas event index and its evolution based on apache kudu storage;big data as the future of information technology;the designing of cloud infrastructure consisting of geographically distributed data centers;multicomponent cluster management system for the computing center at IHEP;RUNNET: infrastructural and service basis of the national research and education network of the Russian Federation;virtual testbed as a case for big data;and properties of the parallel discrete event simulation algorithms on small-world communication networks.
It is typical in High Performance Computing (HPC) courses to give students access to HPC platforms so that they can benefit from hands-on learning opportunities. Using such platforms, however, comes with logistical an...
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ISBN:
(纸本)9781728101903
It is typical in High Performance Computing (HPC) courses to give students access to HPC platforms so that they can benefit from hands-on learning opportunities. Using such platforms, however, comes with logistical and pedagogical challenges. For instance, a logistical challenge is that access to representative platforms must be granted to students, which can be difficult for some institutions or course modalities;and a pedagogical challenge is that hands-on learning opportunities are constrained by the configurations of these platforms. A way to address these challenges is to instead simulate program executions on arbitrary HPC platform configurations. In this work we focus on simulation in the specific context of distributed-memory computing and MPI programming education. While using simulation in this context has been explored in previous works, our approach offers two crucial advantages. First, students write standard MPI programs and can both debug and analyze the performance of their programs in simulation mode. Second, large-scale executions can be simulated in short amounts of time on a single standard laptop computer. This is possible thanks to SMPI, an MPI simulator provided as part of SimGrid. After detailing the challenges involved when using HPC platforms for HPC education and providing background information about SMPI, we present SMPI Courseware. SMPI Courseware is a set of in-simulation assignments that can be incorporated into HPC courses to provide students with hands-on experience for distributed-memory computing and MPI programming learning objectives. We describe some these assignments, highlighting how simulation with SMPI enhances the student learning experience.
To efficiently perform collective communications in current high-performance computing systems is a time-consuming task. With future exascale systems, this communication time will be increased further. However, global...
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ISBN:
(纸本)9781728101767
To efficiently perform collective communications in current high-performance computing systems is a time-consuming task. With future exascale systems, this communication time will be increased further. However, global information is frequently required in various physical models. By exploiting domain knowledge of the model behaviors globally needed information can be distributed more efficiently, using only peer-to-peer communication which spread the information to all processes asynchronous during multiple communication steps. In this article, we introduce a multi-hop based Manhattan Street Network (MSN) for global information exchange and show the conditions under which a local neighbor exchange is sufficient for exchanging distributed information. Besides the MSN, in various models, global information is only needed in a spatially limited region inside the simulation domain. Therefore, a second network is introduced, the local exchange network, to exploit this spatial assumption. Both non-collective global exchange networks are implemented in the massively parallel NAStJA framework. Based on two models, a phase-field model for droplet simulations and the cellular Potts model for biological tissue simulations, we exemplary demonstrate the wide applicability of these networks. Scaling tests of the networks demonstrate a nearly ideal scaling behavior with an efficiency of over 90%. Theoretical prediction of the communication time on future exascale systems shows an enormous advantage of the presented exchange methods of O(1) by exploiting the domain knowledge.
The proceedings contain 10 papers. The special focus in this conference is on. The topics include: Analysis of Mixed Workloads from Shared Cloud Infrastructure;Tuning EASY-Backfilling Queues;don’t Hurry Be Happy: A D...
ISBN:
(纸本)9783319773971
The proceedings contain 10 papers. The special focus in this conference is on. The topics include: Analysis of Mixed Workloads from Shared Cloud Infrastructure;Tuning EASY-Backfilling Queues;don’t Hurry Be Happy: A Deadline-Based Backfilling Approach;Supporting Real-Time Jobs on the IBM Blue Gene/Q: simulation-Based Study;towards Efficient Resource Allocation for distributed Workflows Under Demand Uncertainties;programmable In Situ System for Iterative Workflows;A Data Structure for Planning Based Workload Management of Heterogeneous HPC Systems;ScSF: A Scheduling simulation Framework.
The optimization of performance of complex simulation codes with high computational demands, such as Octo-Tiger, is an ongoing challenge. Octo-Tiger is an astrophysics code simulating the evolution of star systems bas...
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ISBN:
(纸本)9781450364393
The optimization of performance of complex simulation codes with high computational demands, such as Octo-Tiger, is an ongoing challenge. Octo-Tiger is an astrophysics code simulating the evolution of star systems based on the fast multipole method using adaptive octrees as the central data structure. Octo-Tiger was implemented using high-level C++ libraries, specifically HPX and Vc, which allows its use on different hardware platforms. Recently, we have demonstrated excellent scalability in a distributed setting. In this paper, we study the node-level performance of Octo-Tiger on an Intel Knights Landing platform. We focus on Octo-Tiger's fast multipole method, as it is the computationally most demanding component. By using HPX and a futurization approach, we can efficiently traverse the adaptive octrees in parallel. On the core-level, threads process sub-grids using multiple 1074-element stencils. In numerical experiments, simulating the time evolution of a rotating star on an Intel Xeon Phi 7250 Knights Landing processor, Octo-Tiger shows good parallel efficiency. For the fast multipole algorithm, we achieved up to 408 GFLOPS, resulting in a speedup of 2x compared to a 24-core Skylake-SP platform, using the same high-level abstractions.
The earthquake process leads to the destruction of building and has a significant influence on human life. Nowadays there is no methods to forecast it with the 100 % precision. Scientists around the world make efforts...
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Synchronization aspects in the method of large-scale simulation, knovvn as parallel discrete event simulation (PDES), analyzed using the models of the time profile evolutions. Time profile is formed vvith the local vi...
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