<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">GEP</journal-id><journal-title-group><journal-title>Journal of Geoscience and Environment Protection</journal-title></journal-title-group><issn pub-type="epub">2327-4336</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/gep.2017.57012</article-id><article-id pub-id-type="publisher-id">GEP-77806</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Evaluation of the Application Benefit of Meteorological High Performance Computing Resources
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Min</surname><given-names>Wei</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Bin</surname><given-names>Wang</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>National Meteorological Information Center, Beijing, China</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>zxk668@126.com(BW)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>06</day><month>07</month><year>2017</year></pub-date><volume>05</volume><issue>07</issue><fpage>153</fpage><lpage>160</lpage><history><date date-type="received"><day>April</day>	<month>12,</month>	<year>2017</year></date><date date-type="rev-recd"><day>Accepted:</day>	<month>July</month>	<year>18,</year>	</date><date date-type="accepted"><day>July</day>	<month>21,</month>	<year>2017</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  The meteorological high-performance computing resource is the support platform for the weather forecast and climate prediction numerical model operation. The scientific and objective method to evaluate the application of meteorological high-performance computing resources can not only provide reference for the optimization of active resources, but also provide a quantitative basis for future resource construction and planning. In this paper, the concept of the utility value B and index compliance rate E of the meteorological high performance computing system are presented. The evaluation process, evaluation index and calculation method of the high performance computing resource application benefits are introduced.
 
</p></abstract><kwd-group><kwd>High-Performance Computing Resources</kwd><kwd> Resource Application</kwd><kwd> Benefit Evaluation</kwd><kwd> Benefit Value</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The application benefit evaluation of meteorological high-performance computing resource is an important basis for the decision-making of high-performance computing capability of meteorological department. It is also the basis for improving the service of computing resource and the rational use of computing resource. However, because the computing resources involve many levels, the diversification of the benefit manifestation makes the assessment work difficult to measure and uncertainty. The related research of the domain evaluates and analyzes the resource utilization of specific level and specific index from different aspects, such as system performance evaluation [<xref ref-type="bibr" rid="scirp.77806-ref1">1</xref>] , application performance tuning, and job scheduling capability optimization [<xref ref-type="bibr" rid="scirp.77806-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.77806-ref3">3</xref>] . There is no unified, objective, quantitative assessment of the effectiveness of resource applications and evaluation models. In this paper, the overall calculation of resources will be taken into account, extracting the key indicators at all levels, adopting the way of the use of expert assessment and objective measurement method of combining, and conducting a quantitative assessment of the effectiveness of the application of resources. The scientific and accurate analysis and evaluation of the application efficiency of active computing resources can not only promote the optimal use of active resources, improving the effective utilization of resources, but also for the future resource construction and resource management allocation to provide a reference basis for quantification.</p></sec><sec id="s2"><title>2. Application of Meteorological High Performance Computing Resources</title><p>Meteorological high-performance computing resources includes high-perfor- mance computer hardware infrastructure and resource management and application software environment. The high performance computer is the hardware support platform for the numerical model operation. The resource management and application soft environment is the software service environment in which the numerical model runs.</p><p>Meteorological high-performance computing resources are an indispensable technical support for the development of numerical models. At present, the major meteorological numerical model business applications include the GRAPES (Global and Regional Assimilation and Prediction System) weather model [<xref ref-type="bibr" rid="scirp.77806-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.77806-ref5">5</xref>] and the BCC_CSM (Beijing Climate Center Climate System Model) [<xref ref-type="bibr" rid="scirp.77806-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.77806-ref7">7</xref>] independently developed by our country. GRAPES global model horizontal resolution of 25 km, vertical 60 layers, the level of resolution in 2020 to 10 km encrypted resolution, the vertical level increased to 90. The BCC_CSCM model is a climate system model consisting of four components: atmosphere, ocean, land and sea ice. Its atmospheric component model BCC_AGCM (Beijing Climate Center Atmospheric General Circulation Model) has a horizontal resolution of about 50 km and a vertical 26 layers, and is scheduled to be encrypted to 30 km, the vertical layer number increased to 70. With the numerical model in terms of time, scope, etc. more accurate, in time and space resolution, update frequency and so on more sophisticated development, the demand for computing resource capacity is growing. The demand for computing resource quality of service (including services such as parallel computing, application support software, etc.) is increasing [<xref ref-type="bibr" rid="scirp.77806-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.77806-ref9">9</xref>] . The goal of computing resources construction, from the initial simple focus on capacity-building, transition to both the ability and quality of service stage. The management of computing resources is shifted from the initial coarse-grained local allocation to the fine-grained global sharing deployment phase [<xref ref-type="bibr" rid="scirp.77806-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.77806-ref11">11</xref>] .</p><p>At present, the meteorological industry, high-performance computing resources mainly in the national, regional deployment, include IBM Flex P460 and other systems. Although the geographical distribution is different, but logically unified into the pool of computing resources, can be pre-allocated pool of resources for unified scheduling for the national and regional numerical model business, scientific research work to provide technical services (In accordance with the known application requirements and resource supply capacity, pre-se- lected system ready in the data environment, to achieve the application of resource scheduling operation). To achieve the system computing and storage resource usage, the main application of the resource occupancy will be monitored and evaluated. Carrying out some technical researches [<xref ref-type="bibr" rid="scirp.77806-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.77806-ref13">13</xref>] of parallel algorithm optimization, heterogeneous parallel acceleration and so on. But overall, the soft power of application is still relatively weak, to be further strengthened.</p></sec><sec id="s3"><title>3. Assessment of Significance and Methods</title><sec id="s3_1"><title>3.1. Significance of Assessment</title><p>The demand of computing resources is increasing and the scale of resource construction is increasing. The application of active computing resources is to carry out scientific and accurate analysis and evaluation. On the one hand, it can promote the optimized use of active resources, make the system function more perfect, balanced performance, can be efficient and stable continuous operation, improve the efficiency of resource utilization. On the other hand, it can provide quantitative reference for future resource construction and resource management allocation. At the same time, the introduction of the energy efficiency of the output assessment, can promote the efficient use of energy to achieve the goal of green energy.</p></sec><sec id="s3_2"><title>3.2. Evaluation Methods</title><p>At present, the application of meteorological high-performance computing resource evaluation mainly adopts experts’ evaluative and objective measurement method.</p><p>Expert evaluation method is a kind of expert judgment, interactive evaluation method. The main users of high-performance computing resources are divided into business class, major task class, scientific research category and several other categories, and use satisfaction, ease of use of resources, and relying on high- performance computing resources obtained by the application of industry content and other research content will be investigated for national and regional users of high-performance computing resource respectively. According to the research results, there is a subjective assessment of the effectiveness the application of high-performance computing resources. Expert evaluation method can be closely integrated with the specific circumstances of the evaluation, so that the evaluation has a strong targeted.</p><p>Objective measurement algorithm is an objective and quantitative measurement of the use of high-performance computing resources, model computing efficiency and infrastructure support for supporting computing resources [<xref ref-type="bibr" rid="scirp.77806-ref14">14</xref>] . According to the measurement results, the application of high-performance computing resources will be assessed objectively. Objective measurement algorithm is relatively fixed, operable and easy to use.</p></sec></sec><sec id="s4"><title>4. The Initial Establishment of the Evaluation System</title><sec id="s4_1"><title>4.1. Evaluation Process</title><p>At this stage, the majority of meteorological departments provide high-per- formance computing resources for users in the field free of charge. In order to carry out comprehensive assessment of the application of resources and provide a clear quantitative indicator, the application value B of meteorological high- performance computing resource will be established. According to the multivariate characteristics of computing resources, the assessment index of grading is determined, and the corresponding calculation method of utility value is set up for each evaluation index, and the comprehensive benefit value is obtained after the aggregation, which forms the evaluation system of application efficiency of meteorological high performance computing resources [<xref ref-type="bibr" rid="scirp.77806-ref15">15</xref>] . As shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>.</p></sec><sec id="s4_2"><title>4.2. Assessment Indicators</title><p>The level of computing resources, for example, CPU cycles and memory, required by various computing tasks greatly varies depending upon the nature of the task. For example, word processing tasks can generally be run on a microcomputer that is dedicated to a particular person. Simulation tasks such as those for simulating the operation of a circuit, on the other hand, generally require relatively large levels of computing resources. Thus, simulation tasks are often performed on systems other than the microcomputers. Meteorological high- performance computing resources are hierarchical, including, high-performance computer hardware, system software and application software. As the fundamental driving force of high performance computing system, energy is the bottom layer of high performance computing resources, as shown in <xref ref-type="fig" rid="fig2">Figure 2</xref>.</p><p>Aiming at the complexity of high-performance computing resource application, a three-level evaluation index is established. The first indicators are for the use of high-performance computer overall efficiency. The secondary level index include the overall service satisfaction, infrastructure benefits, resource usage</p><fig id="fig1"  position="float"><label><xref ref-type="fig" rid="fig1">Figure 1</xref></label><caption><title> Evaluation process</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/11-2170371x2.png"/></fig><fig id="fig2"  position="float"><label><xref ref-type="fig" rid="fig2">Figure 2</xref></label><caption><title> The level of computing resources</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/11-2170371x3.png"/></fig><p>benefits, model computation benefits and application benefits, benefits assessment (the “overall use of satisfaction assessment index”), evaluation of the effectiveness of resource use, model evaluation and evaluation of the effectiveness of the application of industry evaluation indicators. According to the characteristics of each class of secondary indexes, a three-level indicator is established, which can reflect the actual use situation. According to the importance of the two, three indicators, we set different weights, and the same level within the sum of the weights of the indicators equals 1. At different stages of development, we can adjust the content and weight of the secondary and tertiary indicators. Assessment indicators are divided into two types of subjective assessment and objective assessment. The first level indicator contains many secondary level indicators, and the secondary indicators contain many third-level indicators. As shown in <xref ref-type="table" rid="table1">Table 1</xref>.</p></sec><sec id="s4_3"><title>4.3. Evaluation Method</title><p>The benefit value B of meteorological high performance computing resource is calculated by the benefit value of each secondary index, and the benefit value of each secondary index is calculated from the value of the third-class index. The indicators at different levels represent different aspects of the use of high-per- formance computing resources. In order to form a quantitative and comprehensive assessment of the use of resources, setting a total score <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x4.png" xlink:type="simple"/></inline-formula> for each of the three indicators, the three indicators of the actual compliance rate is<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x5.png" xlink:type="simple"/></inline-formula>, then the value of the three indicators is<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x6.png" xlink:type="simple"/></inline-formula>.</p><p>The benefits of each secondary index were evaluated synthetically by linear- weighted summation method. Assume a secondary index contains third level indicators a total of n can be expressed as<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x7.png" xlink:type="simple"/></inline-formula>. The weight set corresponding to each three-level index can be expressed as <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x8.png" xlink:type="simple"/></inline-formula>. The corresponding benefit value is <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x9.png" xlink:type="simple"/></inline-formula>. Then the value of the secondary indicators is<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x10.png" xlink:type="simple"/></inline-formula>, where<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x11.png" xlink:type="simple"/></inline-formula>,<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x12.png" xlink:type="simple"/></inline-formula>.</p><p>Similarly, using the linear-weighted summation method assesses B value of</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> The application benefit evaluation index of high-performance computing resource</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >First level indicator</th><th align="center" valign="middle" >Secondary level indicator (weight)</th><th align="center" valign="middle" >Third level indicator (weight)</th></tr></thead><tr><td align="center" valign="middle"  rowspan="5"  >Application benefit of high performance computing resources</td><td align="center" valign="middle" >Overall service satisfaction (10%)</td><td align="center" valign="middle" >Satisfaction (100%)</td></tr><tr><td align="center" valign="middle" >Resource usage benefits (30%)</td><td align="center" valign="middle" >Occupancy rate (40%) Available rate (40%) Convenience (20%)</td></tr><tr><td align="center" valign="middle" >Model computational benefits (30%)</td><td align="center" valign="middle" >Computational efficiency (60%) Effectiveness (40%)</td></tr><tr><td align="center" valign="middle" >Application benefits (20%)</td><td align="center" valign="middle" >Application effect (100%)</td></tr><tr><td align="center" valign="middle" >Infrastructure benefits (10%)</td><td align="center" valign="middle" >Energy consumption output (100%)</td></tr></tbody></table></table-wrap><p>the use resources of high-performance computing resources comprehensively. Contains secondary indicators in total of n, can be expressed as <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x13.png" xlink:type="simple"/></inline-formula>. The corresponding weight set can be expressed as <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x14.png" xlink:type="simple"/></inline-formula>. And the corresponding benefit value is <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x15.png" xlink:type="simple"/></inline-formula>. Then the high-performance computing resource application benefit value is<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x16.png" xlink:type="simple"/></inline-formula>, where <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x17.png" xlink:type="simple"/></inline-formula> and<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/11-2170371x18.png" xlink:type="simple"/></inline-formula>.</p></sec></sec><sec id="s5"><title>5. Summary and Prospect</title><p>The application of high performance computing resources in meteorology has achieved initial results, which can be applied to the annual analysis of the investment efficiency of meteorological high performance computing resources in China and provided reference for the construction of next generation high performance computing system. As the basic support of the numerical model, the computing resources tend to be intensified in the business layout and geographical distribution. With the construction and application of computing resources based on the unified data service environment, dynamic resource scheduling and more refined management can be realized through the resource application and management soft environment, improving the computing efficiency of the model and realizing the cooperative development in different places. By gradually perfecting the evaluation index selection and measurement method, the evaluation system will adapt to it, and make the assessment of the application of computing resources more comprehensive, objective and scientific, and the assessment results will be more in line with the actual situation. And the results of the evaluation work will be applied step by step in all phases of the life cycle of high performance computing resources. Standardization, objectivity, normalization of services is the future application of high-performance computing resources evaluation of the development trend [<xref ref-type="bibr" rid="scirp.77806-ref16">16</xref>] . In order to meet the growing demand for meteorological numerical model operational system for the high performance computing application service environment, we provide the application platform of numerical model stable and efficient operation, and carry out the construction work of meteorological high performance computing application service environment. The application requirements of the in-depth analysis plan and design the initial implementation of the construction program, including the unified application of systems and application planning, model software application framework construction and so on. The meteorological numerical model operational and scientific research works are carried out to provide a strong technical support and protection. For the optimization of the measurement method, we will conduct further research in the future.</p></sec><sec id="s6"><title>Acknowledgements</title><p>This work was supported by China Special Fund for Meteorological Research in the Public Interest (GYHY201306062), National Key R&amp;D Program of China (2016YFA0602102), and National Natural Science Foundation of China (41275076).</p></sec><sec id="s7"><title>Cite this paper</title><p>Wei, M. and Wang, B. (2017) Evaluation of the Application Benefit of Meteorological High Performance Computing Resources. Journal of Geoscience and Environment Protection, 5, 153-160. https://doi.org/10.4236/gep.2017.57012</p></sec></body><back><ref-list><title>References</title><ref id="scirp.77806-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Wei, M., Sun, J. and Shen, Y. (2013) Performance Evaluation Method of High Performance Computing System and Its Application. 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