scholarly journals Exploring the feasibility of lossy compression for PDE simulations

2018 ◽  
Vol 33 (2) ◽  
pp. 397-410 ◽  
Author(s):  
Jon Calhoun ◽  
Franck Cappello ◽  
Luke N Olson ◽  
Marc Snir ◽  
William D Gropp
Keyword(s):  
Energy Cost ◽  
High Performance ◽  
Truncation Error ◽  
Computational Cost ◽  
Lossy Compression ◽  
Data Movement ◽  
Hardware Failure ◽  
Traditional Approaches ◽  
Application Codes ◽  
Performance Computing

Checkpoint restart plays an important role in high-performance computing (HPC) applications, allowing simulation runtime to extend beyond a single job allocation and facilitating recovery from hardware failure. Yet, as machines grow in size and in complexity, traditional approaches to checkpoint restart are becoming prohibitive. Current methods store a subset of the application’s state and exploit the memory hierarchy in the machine. However, as the energy cost of data movement continues to dominate, further reductions in checkpoint size are needed. Lossy compression, which can significantly reduce checkpoint sizes, offers a potential to reduce computational cost in checkpoint restart. This article investigates the use of numerical properties of partial differential equation (PDE) simulations, such as bounds on the truncation error, to evaluate the feasibility of using lossy compression in checkpointing PDE simulations. Restart from a checkpoint with lossy compression is considered for a fail-stop error in two time-dependent HPC application codes: PlasComCM and Nek5000. Results show that error in application variables due to a restart from a lossy compressed checkpoint can be masked by the numerical error in the discretization, leading to increased efficiency in checkpoint restart without influencing overall accuracy in the simulation.

scholarly journals A Framework for HI Spectral Source Finding Using Distributed-Memory Supercomputing

2014 ◽  
Vol 31 ◽  
Author(s):  
Stefan Westerlund ◽  
Christopher Harris
Keyword(s):  
High Performance ◽  
Distributed Memory ◽  
Computing Systems ◽  
Sky Surveys ◽  
Local Statistics ◽  
Wide Range ◽  
Gaussian Source ◽  
High Bandwidth ◽  
Traditional Approaches ◽  
Performance Computing

AbstractThe latest generation of radio astronomy interferometers will conduct all sky surveys with data products consisting of petabytes of spectral line data. Traditional approaches to identifying and parameterising the astrophysical sources within this data will not scale to datasets of this magnitude, since the performance of workstations will not keep up with the real-time generation of data. For this reason, it is necessary to employ high performance computing systems consisting of a large number of processors connected by a high-bandwidth network. In order to make use of such supercomputers substantial modifications must be made to serial source finding code. To ease the transition, this work presents the Scalable Source Finder Framework, a framework providing storage access, networking communication and data composition functionality, which can support a wide range of source finding algorithms provided they can be applied to subsets of the entire image. Additionally, the Parallel Gaussian Source Finder was implemented using SSoFF, utilising Gaussian filters, thresholding, and local statistics. PGSF was able to search on a 256GB simulated dataset in under 24 minutes, significantly less than the 8 to 12 hour observation that would generate such a dataset.

scholarly journals Assessing the Effects of Data Compression in Simulations Using Physically Motivated Metrics

2014 ◽  
Vol 22 (2) ◽  
pp. 141-155 ◽  
Author(s):  
Daniel Laney ◽  
Steven Langer ◽  
Christopher Weber ◽  
Peter Lindstrom ◽  
Al Wegener
Keyword(s):  
High Performance ◽  
Turbulence Modeling ◽  
Time Step ◽  
Data Movement ◽  
Laser Plasma Interaction ◽  
Error Metrics ◽  
Tightly Coupled ◽  
Modeling Code ◽  
The Impact ◽  
Performance Computing

This paper examines whether lossy compression can be used effectively in physics simulations as a possible strategy to combat the expected data-movement bottleneck in future high performance computing architectures. We show that, for the codes and simulations we tested, compression levels of 3–5X can be applied without causing significant changes to important physical quantities. Rather than applying signal processing error metrics, we utilize physics-based metrics appropriate for each code to assess the impact of compression. We evaluate three different simulation codes: a Lagrangian shock-hydrodynamics code, an Eulerian higher-order hydrodynamics turbulence modeling code, and an Eulerian coupled laser-plasma interaction code. We compress relevant quantities after each time-step to approximate the effects of tightly coupled compression and study the compression rates to estimate memory and disk-bandwidth reduction. We find that the error characteristics of compression algorithms must be carefully considered in the context of the underlying physics being modeled.

The structure of self-sustained instability, transition and turbulence in the separating boundary layer under an internal solitary wave of depression

2021 ◽  
Author(s):  
Peter Diamessis ◽  
Takahiro Sakai ◽  
Gustaaf Jacobs
Keyword(s):  
Boundary Layer ◽  
Large Amplitude ◽  
High Performance ◽  
Separation Bubble ◽  
Computational Cost ◽  
Three Dimensional ◽  
Instability Mode ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Performance Computing

<p>The development of the separated bottom boundary layer (BBL) in the footprint of a large-amplitude ISW of depression is examined using high-accuracy/resolution implicit Large Eddy Simulation. The talk will focus on a single relatively idealized case of a large-amplitude ISW propagating against an oncoming barotropic current with its own, initially laminar, BBL under the inevitable restriction of laboratory-scale Reynolds number. Significant discussion will be dedicated to the non-trivial computational cost of setting up and conducting the above simulation, within long domains and over long-integration times, in a high-performance-computing environment. Results will focus on documenting the full downstream evolution of the structure of the separated BBL development. Particular emphasis will be placed on the existence of a three-dimensional global instability mode, at the core of the separation bubble where typically one might assume two-dimensional dynamics. The particular instability mode is spontaneously excited and is considered responsible for the self-sustained nature of the resulting near-bed turbulent wake in the lee of the ISW. Fundamental mean BBL flow metrics will then be presented along with a short discussion for potential for particulate resuspension. The talk will close with a discussion of the relevance of the existing flow configuration to both the laboratory and ocean, in light of recent measurements in the NW Australian Shelf.<br><br></p>

scholarly journals WearGP: A UQ/ML Wear Prediction Framework for Slurry Pump Impellers and Casings

2020 ◽  
Author(s):  
Anh Tran ◽  
Yan Wang ◽  
John Furlan ◽  
Krishnan V. Pagalthivarthi ◽  
Mohamed Garman ◽  
...  
Keyword(s):  
High Performance ◽  
Computational Cost ◽  
Operating Conditions ◽  
Wear Prediction ◽  
Wear Rates ◽  
Computing Platform ◽  
Multi Phase ◽  
Performance Computing ◽  
Low Computational Cost ◽  
High Computational Cost

Abstract Dedicated to the memory of John Furlan. Wear prediction is important in designing reliable machinery for slurry industry. It usually relies on multi-phase computational fluid dynamics, which is accurate but computationally expensive. Each run of the simulations can take hours or days even on a high-performance computing platform. The high computational cost prohibits a large number of simulations in the process of design optimization. In contrast to physics-based simulations, data-driven approaches such as machine learning are capable of providing accurate wear predictions at a small fraction of computational costs, if the models are trained properly. In this paper, a recently developed WearGP framework [1] is extended to predict the global wear quantities of interest by constructing Gaussian process surrogates. The effects of different operating conditions are investigated. The advantages of the WearGP framework are demonstrated by its high accuracy and low computational cost in predicting wear rates.

Data Movement in Data-Intensive High Performance Computing

2016 ◽  
pp. 31-59 ◽  
Author(s):  
Pietro Cicotti ◽  
Sarp Oral ◽  
Gokcen Kestor ◽  
Roberto Gioiosa ◽  
Shawn Strande ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Data Movement ◽  
Data Intensive ◽  
Performance Computing

scholarly journals Deriving Large-Scale Coastal Bathymetry from Sentinel-2 Images Using an HIGH-Performance Cluster: A Case Study Covering North Africa’s Coastal Zone

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7006
Author(s):  
Mohamed Wassim Baba ◽  
Gregoire Thoumyre ◽  
Erwin W. J. Bergsma ◽  
Christopher J. Daly ◽  
Rafael Almar
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Computational Cost ◽  
Remote Sensing Data ◽  
Coastal Areas ◽  
New Perspective ◽  
Sentinel 2A ◽  
Performance Computing ◽  
High Computational Cost

Coasts are areas of vitality because they host numerous activities worldwide. Despite their major importance, the knowledge of the main characteristics of the majority of coastal areas (e.g., coastal bathymetry) is still very limited. This is mainly due to the scarcity and lack of accurate measurements or observations, and the sparsity of coastal waters. Moreover, the high cost of performing observations with conventional methods does not allow expansion of the monitoring chain in different coastal areas. In this study, we suggest that the advent of remote sensing data (e.g., Sentinel 2A/B) and high performance computing could open a new perspective to overcome the lack of coastal observations. Indeed, previous research has shown that it is possible to derive large-scale coastal bathymetry from S-2 images. The large S-2 coverage, however, leads to a high computational cost when post-processing the images. Thus, we develop a methodology implemented on a High-Performance cluster (HPC) to derive the bathymetry from S-2 over the globe. In this paper, we describe the conceptualization and implementation of this methodology. Moreover, we will give a general overview of the generated bathymetry map for NA compared with the reference GEBCO global bathymetric product. Finally, we will highlight some hotspots by looking closely to their outputs.

Design of an intermediate high voltage EM for 3-D studies of biological material and its integration with a system for remote access

1995 ◽  
Vol 53 ◽  
pp. 66-67 ◽  
Author(s):  
Mark H. Ellisman
Keyword(s):  
High Voltage ◽  
High Performance ◽  
Remote Access ◽  
3 Dimensional ◽  
Voltage Electron ◽  
Remote Operation ◽  
High Voltage Electron Microscope ◽  
La Jolla ◽  
Performance Computing ◽  
Advanced Version

The increased availability of High Performance Computing and Communications (HPCC) offers scientists and students the potential for effective remote interactive use of centralized, specialized, and expensive instrumentation and computers. Examples of instruments capable of remote operation that may be usefully controlled from a distance are increasing. Some in current use include telescopes, networks of remote geophysical sensing devices and more recently, the intermediate high voltage electron microscope developed at the San Diego Microscopy and Imaging Resource (SDMIR) in La Jolla. In this presentation the imaging capabilities of a specially designed JEOL 4000EX IVEM will be described. This instrument was developed mainly to facilitate the extraction of 3-dimensional information from thick sections. In addition, progress will be described on a project now underway to develop a more advanced version of the Telemicroscopy software we previously demonstrated as a tool to for providing remote access to this IVEM (Mercurio et al., 1992; Fan et al., 1992).

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