Dynamic load balancing of plasma particle-in-cell simulations: The taskfarm alternative
Particle-in-cell (PIC) simulations frequently exhibit some degree of inhomogeneity in the distribution of particles. When running such codes in parallel, this inhomogeneity results in an imbalance of the particle-associated workload. As a remedy, plasma PIC simulations commonly make use of a dynamic...
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Veröffentlicht in: | Computer physics communications 2002-08, Vol.147 (1), p.741-744 |
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description | Particle-in-cell (PIC) simulations frequently exhibit some degree of inhomogeneity in the distribution of particles. When running such codes in parallel, this inhomogeneity results in an imbalance of the particle-associated workload. As a remedy, plasma PIC simulations commonly make use of a dynamic domain decomposition that adjusts itself according to the momentary distribution of particles. We present and evaluate an alternative dynamic load-balancing method: a taskfarm-based scheme, where the total particle-associated work is traded among all processors according to their individual workload. It will be shown to be very efficient for simulations with highly inhomogeneous particle distributions. |
doi_str_mv | 10.1016/S0010-4655(02)00389-2 |
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It will be shown to be very efficient for simulations with highly inhomogeneous particle distributions.</description><subject>Accelerators and propulsion</subject><subject>Exact sciences and technology</subject><subject>Ion and plasma propulsion</subject><subject>Ion thruster</subject><subject>MPI</subject><subject>Parallel efficiency</subject><subject>Particle-in-cell method</subject><subject>Physics</subject><subject>Physics of gases, plasmas and electric discharges</subject><subject>Physics of plasmas and electric discharges</subject><subject>PIC simulation</subject><subject>Plasma beam</subject><subject>Plasma devices</subject><subject>Plasma simulation</subject><subject>Taskfarm</subject><issn>0010-4655</issn><issn>1879-2944</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><recordid>eNqFkEtv1DAQgC1UpG63_IRKvoDgkHYmjhOHC0ILtJVW4kARR2viBxicB3a20v57st2KHnuakeab18fYBcIlAtZX3wAQiqqW8i2U7wCEaovyBVuhapakraoTtvqPnLKznH8DQNO0YsV-fNoP1AfD40iWdxRpMGH4yUfPp0i5Jz5RmoOJrghDYVyMPId-F2kO45Df87tfjs-U_3hKPac4uzQspXt3zl56itm9eoxr9v3L57vNTbH9en27-bgtjKjVXFhrvK1E4wlrUEZ0JZJFKb0l6gQKrBGtANl0nUcUlRU1CYG-rVRLWFZizd4c505p_LtzedZ9yIczaXDjLuuyASVAqQWUR9CkMefkvJ5S6CntNYI-aNQPGvXBkYZSP2jU5dL3-nEBZUPRp4Og_NQslJTL7Qv34ci55dv74JLOJrjBOBuSM7O2Y3hm0z-gVob_</recordid><startdate>20020801</startdate><enddate>20020801</enddate><creator>Othmer, C.</creator><creator>Schüle, J.</creator><general>Elsevier B.V</general><general>Elsevier Science</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope></search><sort><creationdate>20020801</creationdate><title>Dynamic load balancing of plasma particle-in-cell simulations: The taskfarm alternative</title><author>Othmer, C. ; Schüle, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-ddcfd437fa1608c3b21ad155fdaab3131611d3057bbf1134d36a331f9489a1243</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Accelerators and propulsion</topic><topic>Exact sciences and technology</topic><topic>Ion and plasma propulsion</topic><topic>Ion thruster</topic><topic>MPI</topic><topic>Parallel efficiency</topic><topic>Particle-in-cell method</topic><topic>Physics</topic><topic>Physics of gases, plasmas and electric discharges</topic><topic>Physics of plasmas and electric discharges</topic><topic>PIC simulation</topic><topic>Plasma beam</topic><topic>Plasma devices</topic><topic>Plasma simulation</topic><topic>Taskfarm</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Othmer, C.</creatorcontrib><creatorcontrib>Schüle, J.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Computer physics communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Othmer, C.</au><au>Schüle, J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamic load balancing of plasma particle-in-cell simulations: The taskfarm alternative</atitle><jtitle>Computer physics communications</jtitle><date>2002-08-01</date><risdate>2002</risdate><volume>147</volume><issue>1</issue><spage>741</spage><epage>744</epage><pages>741-744</pages><issn>0010-4655</issn><eissn>1879-2944</eissn><coden>CPHCBZ</coden><abstract>Particle-in-cell (PIC) simulations frequently exhibit some degree of inhomogeneity in the distribution of particles. When running such codes in parallel, this inhomogeneity results in an imbalance of the particle-associated workload. As a remedy, plasma PIC simulations commonly make use of a dynamic domain decomposition that adjusts itself according to the momentary distribution of particles. We present and evaluate an alternative dynamic load-balancing method: a taskfarm-based scheme, where the total particle-associated work is traded among all processors according to their individual workload. It will be shown to be very efficient for simulations with highly inhomogeneous particle distributions.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/S0010-4655(02)00389-2</doi><tpages>4</tpages></addata></record> |
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subjects | Accelerators and propulsion Exact sciences and technology Ion and plasma propulsion Ion thruster MPI Parallel efficiency Particle-in-cell method Physics Physics of gases, plasmas and electric discharges Physics of plasmas and electric discharges PIC simulation Plasma beam Plasma devices Plasma simulation Taskfarm |
title | Dynamic load balancing of plasma particle-in-cell simulations: The taskfarm alternative |
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