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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Performance of the fusion code GYRO on four generations of Cray computers

GYRO is a code used for the direct numerical simulation of plasma microturbulence. It has been ported to a variety of modern MPP platforms including several modern commodity clusters, IBM SPs, and Cray XC, XT, and XE series machines. We briefly describe the mathematical structure of the equations, the data layout, and the redistribution scheme. Also, while the performance and scaling of GYRO on many of these systems has been shown before, here we show the comparative performance and scaling on four generations of Cray supercomputers including the newest addition - the Cray XC30. The more recently added hybrid OpenMP/MPI imple- mentation also shows a great deal of promise on custom HPC systems that utilize fast CPUs and proprietary interconnects. Four machines of varying sizes were used in the experiment, all of which are located at the National Institute for Computational Sciences at the University of Tennessee at Knoxville and Oak Ridge National Laboratory. The advantages, limitations, and performance of using each system are discussed.

Fahey, Mark R↗

Monitoring Cray Cooling Systems

While sites generally have systems in place to monitor the health of Cray computers themselves, often the cooling systems are ignored until a computer failure requires investigation into the source of the failure. The Liebert XDP units used to cool the Cray XE/XK models as well as the Cray proprietary cooling system used for the Cray XC30 models provide data useful for health monitoring. Unfortunately, this valuable information is often available only to custom solutions not accessible by a center-wide monitoring system or is simply ignored entirely. In this paper, methods and tools used to harvest the monitoring data available are discussed, and the implementation needed to integrate the data into a center-wide monitoring system at the Oak Ridge National Laboratory is provided.

Maxwell, Don E↗

Small scale to extreme: Methods for characterizing energy efficiency in supercomputing applications

Here, power measurement capabilities are becoming commonplace on large scale HPC system deployments. There exist several different approaches to providing power measurements that are used today, primarily in-band and out-of-band measurements. Both of these fundamental techniques can be augmented with application-level profiling and the combination of different techniques is also possible. However, it can be difficult to assess the type and detail of measurement needed to obtain insights and knowledge of the power profile of an application. In addition, the heterogeneity of modern hybrid supercomputing platforms requires that different CPU architectures must be examined as well.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Searching for Physics Beyond the Standard Model: Strongly-Coupled Field Theories at the Intensity and Energy Frontiers

This proposal is to develop the software and algorithmic infrastructure needed for the numerical study of quantum chromodynamics (QCD), and of theories that have been proposed to describe physics beyond the Standard Model (BSM) of high energy physics, on current and future computers. This infrastructure will enable users (1) to improve the accuracy of QCD calculations to the point where they no longer limit what can be learned from high-precision experiments that seek to test the Standard Model, and (2) to determine the predictions of BSM theories in order to understand which of them are consistent with the data that will soon be available from the LHC. Work will include the extension and optimizations of community codes for the next generation of leadership class computers, the IBM Blue Gene/Q and the Cray XE/XK, and for the dedicated hardware funded for our field by the Department of Energy. Members of our collaboration at Brookhaven National Laboratory and Columbia University worked on the design of the Blue Gene/Q, and have begun to develop software for it. Under this grant we will build upon their experience to produce high-efficiency production codes for this machine. Cray XE/XK computers with many thousands of GPU accelerators will soon be available, and the dedicated commodity clusters we obtain with DOE funding include growing numbers of GPUs. We will work with our partners in NVIDIA's Emerging Technology group to scale our existing software to thousands of GPUs, and to produce highly efficient production codes for these machines. Work under this grant will also include the development of new algorithms for the effective use of heterogeneous computers, and their integration into our codes. It will include improvements of Krylov solvers and the development of new multigrid methods in collaboration with members of the FASTMath SciDAC Institute, using their HYPRE framework, as well as work on improved symplectic integrators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Frontier (HPE Cray EX) Exascale Supercomputer at the Oak Ridge Leadership Computing Facility

Frontier is the HPE Cray EX exascale supercomputer deployed and operated by the Oak Ridge Leadership Computing Facility (OLCF) at Oak Ridge National Laboratory (ORNL). Frontier is designed for large-scale modeling, simulation, and AI workloads and is built from HPE Cray EX system architecture with AMD CPUs and AMD Instinct GPU accelerators connected by the HPE Slingshot interconnect. System composition (representative production configuration): Frontier is composed of approximately 74 cabinets with 128 compute nodes per cabinet (~9,400 compute nodes total). Each compute node contains one 64-core AMD EPYC CPU and four AMD Instinct MI250X GPUs. Nodes are connected using HPE Slingshot (Slingshot-200 class) networking with multiple NIC ports per node providing high injection bandwidth. Frontier is connected to the Orion parallel file system (multi-tier Lustre) providing a large, center-wide high-performance storage namespace. Operational context: Frontier entered public prominence as the first system to reach No. 1 on the TOP500 list in May 2022 (HPL benchmark), establishing the first widely recognized exascale-era performance milestone. The system supports DOE Office of Science mission workloads and enables leadership-class computational science and AI for open science users.

AMD EPYC↗

Aurora: Argonne’s Next-Generation Exascale Supercomputer

Argonne National Laboratory’s next-generation supercomputer, Aurora, will be one of the world’s first exascale systems when it arrives in 2021. The exascale supercomputer, developed in partnership with Intel and Cray, will dramatically accelerate scientific discovery and usher in new technological capabilities, furthering the United States’ scientific leadership position globally. Aurora will be housed at the Argonne Leadership Computing Facility, a U.S. Department of Energy Office of Science User Facility and a premier source of world-class computing resources for open science research since 2006.

97 MATHEMATICS AND COMPUTING↗

The fusion code XGC: Enabling kinetic study of multi-scale edge turbulent transport in ITER [Book Chapter]

The XGC fusion gyrokinetic code combines state-of-the-art, portable computational and algorithmic technologies to enable complicated multiscale simulations of turbulence and transport dynamics in ITER edge plasma on the largest US open-science computer, the CRAY XK7 Titan, at its maximal heterogeneous capability, which have not been possible before due to a factor of over 10 shortage in the time-to-solution for less than 5 days of wall-clock time for one physics case. Frontier techniques such as nested OpenMP parallelism, adaptive parallel I/O, staging I/O and data reduction using dynamic and asynchronous applications interactions, dynamic repartitioning for balancing computational work in pushing particles and in grid related work, scalable and accurate discretization algorithms for non-linear Coulomb collisions, and communication-avoiding subcycling technology for pushing particles on both CPUs and GPUs are also utilized to dramatically improve the scalability and time-to-solution, hence enabling the difficult kinetic ITER edge simulation on a present-day leadership class computer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In this paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.

97 MATHEMATICS AND COMPUTING↗

The HARNESS Workbench: Unified and Adaptive Access to Diverse HPC Platforms

The primary goal of the Harness WorkBench (HWB) project is to investigate innovative software environments that will help enhance the overall productivity of applications science on diverse HPC platforms. Two complementary frameworks were designed: one, a virtualized command toolkit for application building, deployment, and execution, that provides a common view across diverse HPC systems, in particular the DOE leadership computing platforms (Cray, IBM, SGI, and clusters); and two, a unified runtime environment that consolidates access to runtime services via an adaptive framework for execution-time and post processing activities. A prototype of the first was developed based on the concept of a 'system-call virtual machine' (SCVM), to enhance portability of the HPC application deployment process across heterogeneous high-end machines. The SCVM approach to portable builds is based on the insertion of toolkit-interpretable directives into original application build scripts. Modifications resulting from these directives preserve the semantics of the original build instruction flow. The execution of the build script is controlled by our toolkit that intercepts build script commands in a manner transparent to the end-user. We have applied this approach to a scientific production code (Gamess-US) on the Cray-XT5 machine. The second facet, termed Unibus, aims to facilitate provisioning and aggregation of multifaceted resources from resource providers and end-users perspectives. To achieve that, Unibus proposes a Capability Model and mediators (resource drivers) to virtualize access to diverse resources, and soft and successive conditioning to enable automatic and user-transparent resource provisioning. A proof of concept implementation has demonstrated the viability of this approach on high end machines, grid systems and computing clouds.

97 MATHEMATICS AND COMPUTING↗

The fusion code XGC: Enabling kinetic study of multi-scale edge turbulent transport in ITER

The XGC fusion gyrokinetic code combines state-of-the-art, portable computational and algorithmic technologies to enable complicated multiscale simulations of turbulence and transport dynamics in ITER edge plasma on the largest US open-science computer, the CRAY XK7 Titan, at its maximal heterogeneous capability, which have not been possible before due to a factor of over 10 shortage in the time-to-solution for less than 5 days of wall-clock time for one physics case. Frontier techniques such as nested OpenMP parallelism, adaptive parallel I/O, staging I/O and data reduction using dynamic and asynchronous applications interactions, dynamic repartitioning.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Study of interconnect errors, network congestion, and applications characteristics for throttle prediction on a large scale HPC system

Today’s High Performance Computing (HPC) systems contain thousand of nodes which work together to provide performance in the order of petaflops. The performance of these systems depends on various components like processors, memory, and interconnect. Among all, interconnect plays a major role as it glues together all the hardware components in an HPC system. A slow interconnect can impact a scientific application running on multiple processes severely as they rely on fast network messages to communicate and synchronize frequently. Unfortunately, the HPC community lacks a study that explores different interconnect errors, congestion events and applications characteristics on a large-scale HPC system. In our previous work, we process and analyze interconnect data of the Titan supercomputer to develop a thorough understanding of interconnects faults, errors, and congestion events. In this work, we first show how congestion events can impact application performance. We then investigate application characteristics interaction with interconnect errors and network congestion to predict applications encountering congestion with more than 90% accuracy.

97 MATHEMATICS AND COMPUTING↗

An Analysis of Computational Workloads on the Jaguar Cray XT System

This study presents an analysis of science application workloads for the Jaguar Cray XT5 system during its tenure as a 2.3 petaflop supercomputer at Oak Ridge National Laboratory. Jaguar was the first petascale system to be deployed for open science and has been one of the world's top three supercomputers for six releases of the TOP500 list. Its workload is investigated here as a representative of the growing worldwide install base of petascale systems and also as a foreshadowing of science workloads to be expected for future systems. The study considers characteristics of the Jaguar workload such as resource utilization, typical job characteristics, most heavily used applications, application scaling and application usage patterns. Implications of these findings are considered for current petascale workflows and for exascale systems to be deployed later this decade.

Joubert, Wayne↗

Comparing the Performance of Blue Gene/Q with Leading Cray XE6 and InfiniBand Systems

Abstract—Three types of systems dominate the current High Performance Computing landscape: the Cray XE6, the IBM Blue Gene, and commodity clusters using InfiniBand. These systems have quite different characteristics making the choice for a particular deployment difficult. The XE6 uses Cray’s proprietary Gemini 3-D torus interconnect with two nodes at each network endpoint. The latest IBM Blue Gene/Q uses a single socket integrating processor and communication in a 5-D torus network. InfiniBand provides the flexibility of using nodes from many vendors connected in many possible topologies. The performance characteristics of each vary vastly along with their utilization model. In this work we compare the performance of these three systems using a combination of micro-benchmarks and a set of production applications. In particular we discuss the causes of variability in performance across the systems and also quantify where performance is lost using a combination of measurements and models. Our results show that significant performance can be lost in normal production operation of the Cray XT6 and InfiniBand Clusters in comparison to Blue Gene/Q.

-High Performance Computing, Performance Evaluatio↗

Online Diagnostics at Scale

The Oak Ridge Leadership Computing Facility (OLCF) housed at the Oak Ridge National Laboratory recently acquired a 200-cabinet Cray XK6. The computer will primarily provide capability computing cycles to the U.S. Department of Energy (DOE) Office of Science INCITE program. The OLCF has a tradition of installing very large computer systems requiring unique methods in order to achieve production status in the most expeditious and efficient manner. This paper will explore some of the methods that have been used over the years at OLCF to eliminate both early-life hardware failures and ongoing failures giving users a more stable machine for production.

99 GENERAL AND MISCELLANEOUS↗

Open MPI for Cray XE/XK Systems

Open MPI provides an implementation of the MPI standard supporting communications over a range of high-performance network interfaces. Recently, ORNL and LANL have collaborated on creating a port of Open MPI for Gemini, the network interface for Cray XE and XK systems. In this paper, we present our design and implementation of Open MPI's point-to-point and collective operations for Gemini, and techniques we employ to provide good scaling, and performance characteristics.

97 MATHEMATICS AND COMPUTING↗

Improving MPI Collective I/O for High Volume Non-Contiguous Requests With Intra-Node Aggregation

Two-phase I/O is a well-known strategy for implementing collective MPI-IO functions. It redistributes I/O requests among the calling processes into a form that minimizes the file access costs. As modern parallel computers continue to grow into the exascale era, the communication cost of such request redistribution can quickly overwhelm collective I/O performance. In this study, this effect has been observed from parallel jobs that run on multiple compute nodes with a high count of MPI processes on each node. Furthermore, to reduce the communication cost, we present a new design for collective I/O by adding an extra communication layer that performs request aggregation among processes within the same compute nodes. This approach can significantly reduce inter-node communication contention when redistributing the I/O requests. We evaluate the performance and compare it with the original two-phase I/O on Cray XC40 parallel computers (Theta and Cori) with Intel KNL and Haswell processors. Using I/O patterns from two large-scale production applications and an I/O benchmark, we show our proposed method effectively reduces the communication cost and hence maintains the scalability for a large number of processes.

97 MATHEMATICS AND COMPUTING↗

Production Experiences with the Cray-Enabled TORQUE Resource Manager

High performance computing resources utilize batch systems to manage the user workload. Cray systems are uniquely different from typical clusters due to Cray s Application Level Placement Scheduler (ALPS). ALPS manages binary transfer, job launch and monitoring, and error handling. Batch systems require special support to integrate with ALPS using an XML protocol called BASIL. Previous versions of Adaptive Computing s TORQUE and Moab batch suite integrated with ALPS from within Moab, using PERL scripts to interface with BASIL. This would occasionally lead to problems when all the components would become unsynchronized. Version 4.1 of the TORQUE Resource Manager introduced new features that allow it to directly integrate with ALPS using BASIL. This paper describes production experiences at Oak Ridge National Laboratory using the new TORQUE software versions, as well as ongoing and future work to improve TORQUE.

Adaptive Comput- ing↗