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At least 37 records · Page 2

An analysis of computational workloads for the ORNL Jaguar system. In: ICS '12 Proceedings of the 26th ACM international conference on Supercomputing

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↗

Discrete Event Execution with One-Sided and Two-Sided GVT Algorithms on 216,000 Processor Cores

Global virtual time (GVT) computation is a key determinant of the efficiency and runtime dynamics of parallel discrete event simulations (PDES), especially on large-scale parallel platforms. Here, three execution modes of a generalized GVT computation algorithm are studied on high-performance parallel computing systems: (1) a synchronous GVT algorithm that affords ease of implementation, (2) an asynchronous GVT algorithm that is more complex to implement but can relieve blocking latencies, and (3) a variant of the asynchronous GVT algorithm to exploit one-sided communication in extant supercomputing platforms. Performance results are presented of implementations of these algorithms on up to 216,000 cores of a Cray XT5 system, exercised on a range of parameters: optimistic and conservative synchronization, fine- to medium-grained event computation, synthetic and non-synthetic applications, and different lookahead values. Performance of up to 54 billion events executed per second is registered. Detailed PDES-specific runtime metrics are presented to further the understanding of tightly-coupled discrete event dynamics on massively parallel platforms.

Perumalla, Kalyan S↗

Discrete event modeling and massively parallel execution of epidemic outbreak phenomena

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks cannot be supported by sequential or small-scale parallel execution, making it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction–diffusion simulation model of epidemic propagation is presented to facilitate a dramatic increase in the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallel execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene/P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes, with mobility and detailed state evolution modeled at the level of each individual, exceeding several hundreds of millions of individuals in the largest cases, are successfully exercised to verify model scalability.

Computer Science↗

Improving the Performance Scalability of the Community Atmosphere Model

The Community Atmosphere Model (CAM), which serves as the atmosphere component of the Community Climate System Model (CCSM), is the most computationally expensive CCSM component in typical configurations. On current and next-generation leadership class computing systems, the performance of CAM is tied to its parallel scalability. Improving performance scalability in CAM has been a challenge, due largely to algorithmic restrictions necessitated by the polar singularities in its latitude-longitude computational grid. Nevertheless, through a combination of exploiting additional parallelism, implementing improved communication protocols, and eliminating scalability bottlenecks, we have been able to more than double the maximum throughput rate of CAM on production platforms. We describe these improvements and present results on the Cray XT5 and IBM BG/P. The approaches taken are not specific to CAM and may inform similar scalability enhancement activities for other codes.

99 GENERAL AND MISCELLANEOUS↗

An application-level parallel I/O library for Earth system models

We describe the design and implementation of an application-level parallel I/O (PIO) library for the reading and writing of distributed arrays to several common scientific data formats. PIO provides the flexibility to control the number of I/O tasks through data rearrangement to an I/O friendly decomposition. This flexibility enables reductions in per task memory usage and improvements in disk I/O performance versus a serial I/O approach. We illustrate the impact various features within PIO have on memory usage and disk I/O bandwidth on a Cray XT5 system.

Computer Science↗

Linux Kernel Co-Scheduling and Bulk Synchronous Parallelism

This paper describes a kernel scheduling algorithm that is based on coscheduling principles and that is intended for parallel applications running on 1000 cores or more. Experimental results for a Linux implementation on a Cray XT5 machine are presented. The results indicate that Linux is a suitable operating system for this new scheduling scheme, and that this design provides a dramatic improvement in scaling performance for synchronizing collective operations at scale.

co-scheduling.↗

Computational Performance of Ultra-High-Resolution Capability in the Community Earth System Model

With the fourth release of the Community Climate System Model, the ability to perform ultra-high resolution climate simulations is now possible, enabling eddy-resolving ocean and sea ice models to be coupled to a finite-volume atmosphere model for a range of atmospheric resolutions. This capability was made possible by enabling the model to use large scale parallelism, which required a significant refactoring of the software infrastructure. We describe the scalability of two ultra-high-resolution coupled configurations on leadership class computing platforms. We demonstrate the ability to utilize over 30,000 processor cores on a Cray XT5 system and over 60,000 cores on an IBM Blue Gene/P system to obtain climatologically relevant simulation rates for these configurations.

99 GENERAL AND MISCELLANEOUS↗

Full Core Reactor Analysis: Running Denovo on Jaguar

Fully-consistent, full-core, 3D, deterministic neutron transport simulations using the orthogonal mesh code Denovo were run on the massively parallel computing architecture Jaguar XT5. Using energy and spatial parallelization schemes, Denovo was able to efficiently scale to more than 160k processors. Cell-homogenized cross sections were used with step-characteristics, linear-discontinuous finite element, and trilinear-discontinuous finite element spatial methods. It was determined that using the finite element methods gave considerably more accurate eigenvalue solutions for large-aspect ratio meshes than using step-characteristics.

Denovo↗

Using High Performance Computing to Understand Roles of Labile and Nonlabile U(VI) on Hanford 300 Area Plume Longevity

Evolution of a hexavalent uranium [U(VI)] plume at the Hanford 300 Area bordering the Columbia River is investigated to evaluate the roles of labile and nonlabile forms of U(VI) on the longevity of the plume. A high fidelity, three-dimensional, field-scale, reactive flow and transport model is used to represent the system. Richards equation coupled to multicomponent reactive transport equations are solved for times up to 100 years taking into account rapid fluctuations in the Columbia River stage resulting in pulse releases of U(VI) into the river. The peta-scale computer code PFLOTRAN developed under a DOE SciDAC-2 project is employed in the simulations and executed on ORNL's Cray XT5 supercomputer Jaguar. Labile U(VI) is represented in the model through surface complexation reactions and its nonlabile form through dissolution of metatorbernite used as a surrogate mineral. Initial conditions are constructed corresponding to the U(VI) plume already in place to avoid uncertainties associated with the lack of historical data for the waste stream. The cumulative U(VI) flux into the river is compared for cases of equilibrium and multirate sorption models and for no sorption. The sensitivity of the U(VI) flux into the river on the initial plume configuration is investigated. The presence of nonlabile U(VI) was found to be essential in explaining the longevity of the U(VI) plume and the prolonged high U(VI) concentrations at the site exceeding the EPA MCL for uranium.

99 GENERAL AND MISCELLANEOUS↗

Quantum Monte Carlo Endstation for Petascale Computing

The major achievements enabled by QMC Endstation grant include * Performance improvement on clusters of x86 multi-core systems, especially on Cray XT systems * New and improved methods for the wavefunction optimizations * New forms of trial wavefunctions * Implementation of the full application on NVIDIA GPUs using CUDA The scaling studies of QMCPACK on large-scale systems show excellent parallel efficiency up to 216K cores on Jaguarpf (Cray XT5). The GPU implementation shows speedups of 10-15x over the CPU implementation on older generation of x86. We have implemented hybrid OpenMP/MPI scheme in QMC to take advantage of multi-core shared memory processors of petascale systems. Our hybrid scheme has several advantages over the standard MPI-only scheme. * Memory optimized: large read-only data to store one-body orbitals and other shared properties to represent the trial wave function and many-body Hamiltonian can be shared among threads, which reduces the memory footprint of a large-scale problem. * Cache optimized: the data associated with an active Walker are in cache during the compute-intensive drift-diffusion process and the operations on an Walker are optimized for cache reuse. Thread-local objects are used to ensure the data affinity to a thread. * Load balanced: Walkers in an ensemble are evenly distributed among threads and MPI tasks. The two-level parallelism reduces the population imbalance among MPI tasks and reduces the number of point-to-point communications of large messages (serialized objects) for the Walker exchange. * Communication optimized: the communication overhead, especially for the collective operations necessary to determine ET and measure the properties of an ensemble, is significantly lowered by using less MPI tasks. The multiple forms of parallelism afforded by QMC algorithms make them ideal candidates for acceleration in the many-core paradigm. We presented the results of our effort to port the QMCPACK simulation code to the NVIDIA CUDA GPU platform. We restructured the CPU algorithms to express additional parallelism, minimize GPU-CPU communication, and efficiently utilize the GPU memory hierarchy. Using mixed precision on GT200 GPUs and MPI for intercommunication and load balancing, we observe typical full-application speedups of approximately 10x to 15x relative to quad-core Xeon CPUs alone, while reproducing the double-precision CPU results within statistical error. We developed an all-electron quantum Monte Carlo (QMC) method for solids that does not rely on pseudopotentials, and used it to construct a primary ultra-high-pressure calibration based on the equation of state of cubic boron nitride. We computed the static contribution to the free energy with the QMC method and obtained the phonon contribution from density functional theory, yielding a high-accuracy calibration up to 900 GPa usable directly in experiment. We computed the anharmonic Raman frequency shift with QMC simulations as a function of pressure and temperature, allowing optical pressure calibration. In contrast to present experimental approaches, small systematic errors in the theoretical EOS do not increase with pressure, and no extrapolation is needed. This all-electron method is applicable to first-row solids, providing a new reference for ab initio calculations of solids and benchmarks for pseudopotential accuracy. We compared experimental and theoretical results on the momentum distribution and the quasiparticle renormalization factor in sodium. From an x-ray Compton-profile measurement of the valence-electron momentum density, we derived its discontinuity at the Fermi wavevector finding an accurate measure of the renormalization factor that we compared with quantum-Monte-Carlo and G0W0 calculations performed both on crystalline sodium and on the homogeneous electron gas. Our calculated results are in good agreement with the experiment. We have been studying the heat of formation for various Kubas complexes of molecular hydrogen on Ti(1,2)ethylene-nH2 using Diffusion Monte Carlo. This work has been started and is ongoing. We are studying systems involving 1 and 2 Ti bonding sites with up to 10 hydrogen molecules in numerous configurations. This work will establish a benchmark that will test the accuracy of density functional calculations and establish the feasibility of our methods for similar systems.

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↗

Providing Runtime Clock Synchronization With Minimal Node-to-Node Time Deviation on XT4s and XT5s

We present a new high precision clock synchronization algorithm designed for large XT4 and XT5 leadership-class machines. The algorithm, which is designed to support OS noise reduction through co-scheduling, is suitable for usage cases requiring low overhead and minimal time deviation between nodes. Unlike most high-precision algorithms which reach their precision in a post-mortem analysis after the application has completed, the new ORNL developed algorithm rapidly provides precise results during runtime. Previous to our work, the leading high-precision clock synchronization algorithms that made results available during runtime relied on probabilistic schemes that are not guaranteed to result in an answer.

99 GENERAL AND MISCELLANEOUS↗

Linux Kernel Co-Scheduling For Bulk Synchronous Parallel Applications

This paper describes a kernel scheduling algorithm that is based on co-scheduling principles and that is intended for parallel applications running on 1000 cores or more where inter-node scalability is key. Experimental results for a Linux implementation on a Cray XT5 machine are presented.1 The results indicate that Linux is a suitable operating system for this new scheduling scheme, and that this design provides a dramatic improvement in scaling performance for synchronizing collective operations at scale.

99 GENERAL AND MISCELLANEOUS↗

Characterizing Application Runtime Behavior from System Logs and Metrics

Large-scale systems are heavily shared resource environments where a mix of applications are launched concurrently competing for network and storage resources. It is essential to characterize the runtime behavior of these applications for provisioning system resources and understanding the impact of application s performance when competing for resources. In this paper, we study the use of zero- and low-overhead system logs and other system metric data for characterizing the runtime behavior of several applications. We present our preliminary work on estimating individual application s I/O demands by observing file system usage pattern over multiple runs, and interpreting application s network utilization characteristics by observing link-layer error logs. We also present preliminary findings on using such information in making context-sensitive scheduling decisions that minimize potentially negative interactions between applications competing for shared resources. Our analysis is based on four months of system log data collected on one of the world s largest supercomputing facilities, the Jaguar XT5 petaflop system at Oak Ridge National Laboratory.

99 GENERAL AND MISCELLANEOUS↗

Improving Multi-Million Virtual Rank MPI Execution in

(MUPI) is a parallel discrete event simulator designed for enabling software-based experimentation via simulated execution across a range of synthetic to unmodified parallel programs using the Message Passing Interface (MPI) with millions of tasks. Here, we report work in progress in improving the efficiency of . Among the issues uncovered are the scaling problems with implementing barriers and intertask message ordering. Preliminary performance shows the possibility of supporting hundreds of virtual MPI ranks per real processor core. Performance improvements of at least 2 are observed, and enable execution of benchmark MPI runs with over 16 million virtual ranks synchronized in a discrete event fashion on as few as 16,128 real cores of a Cray XT5.

99 GENERAL AND MISCELLANEOUS↗

GVT Algorithms and Discrete Event Dynamics on 128K+ Processor Cores

Parallel discrete event simulation (PDES) represents a class of codes that are challenging to scale to large number of processors due to tight global timestamp-ordering and fine-grained event execution. One of the critical factors in scaling PDES is the efficiency of the underlying global virtual time (GVT) algorithm needed for correctness of parallel execution and speed of progress. Although many GVT algorithms have been proposed previously, few have been proposed for scalable asynchronous execution and none customized to exploit one-sided communication. Moreover, the detailed performance effects of actual GVT algorithm implementations on large platforms are unknown. Here, three major GVT algorithms intended for scalable execution on high-performance systems are studied: (1) a synchronous GVT algorithm that affords ease of implementation, (2) an asynchronous GVT algorithm that is more complex to implement but can relieve blocking latencies, and (3) a variant of the asynchronous GVT algorithm, proposed and studied for the first time here, to exploit one-sided communication in extant supercomputing platforms. Performance results are presented of implementations of these algorithms on over 64,000 cores of a Cray XT5 system, exercised on a range of parameters: optimistic and conservative synchronization, fine- to medium-grained event computation, synthetic and non-synthetic applications, and different lookahead values. Performance of tens of billions of events executed per second are registered, exceeding the speeds of any known PDES engine, and showing asynchronous GVT algorithms to outperform state-of-the-art synchronous GVT algorithms. Detailed PDES-specific runtime metrics are presented to further the understanding of tightly-coupled discrete event execution dynamics on massively parallel platforms.

99 GENERAL AND MISCELLANEOUS↗

Cheetah: A Framework for Scalable Hierarchical Collective Operations

Collective communication operations, used by many scientific applications, tend to limit overall parallel application performance and scalability. Computer systems are becoming more heterogeneous with increasing node and core-per-node counts. Also, a growing number of data-access mechanisms, of varying characteristics, are supported within a single computer system. We describe a new hierarchical collective communication framework that takes advantage of hardware-specific data-access mechanisms. It is flexible, with run-time hierarchy specification, and sharing of collective communication primitives between collective algorithms. Data buffers are shared between levels in the hierarchy reducing collective communication management overhead. We have implemented several versions of the Message Passing Interface (MPI) collective operations, MPI Barrier() and MPI Bcast(), and run experiments using up to 49, 152 processes on a Cray XT5, and a small InfiniBand based cluster. At 49, 152 processes our barrier implementation outperforms the optimized native implementation by 75%. 32 Byte and one Mega-Byte broadcasts outperform it by 62% and 11%, respectively, with better scalability characteristics. Improvements relative to the default Open MPI implementation are much larger.

99 GENERAL AND MISCELLANEOUS↗

Discrete Event Modeling and Massively Parallel Execution of Epidemic Outbreak Phenomena

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post-facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks make it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction-diffusion simulation model of epidemic propagation is presented to facilitate in dramatically increasing the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallel execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene / P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes exceeding several hundreds of millions of individuals in the largest cases are successfully exercised to verify model scalability.

99 GENERAL AND MISCELLANEOUS↗