{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T22:57:15Z","timestamp":1777676235128,"version":"3.51.4"},"reference-count":21,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2004,5,1]],"date-time":"2004-05-01T00:00:00Z","timestamp":1083369600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["The International Journal of High Performance Computing Applications"],"published-print":{"date-parts":[[2004,5]]},"abstract":"<jats:p>\n                    We estimate that a novel architecture massively parallel computer, the QCDOC, can integrate molecular dynamics equations for 10\n                    <jats:sup>5<\/jats:sup>\n                    particles interacting via long-range forces (including Coulomb) for 1\u201310 s of simulated time using several weeks of computing time using 8000 or 10,000 processors. This number of atoms is typical for biological molecules. The two main conclusions we reach are as follows. (1) This is an increase of more than one order of magnitude in simulated time over current simulations. (2) The novel architecture, with 24 parallel channels of low latency communication per processor, allows improved long-range communication and an unusual degree of fine-scale parallelism, compared to conventional switch-based architectures. The technical heart of the paper is a detailed analysis of the computing time used in the Ewald method as a function of the required accuracy, the size of the molecular dynamics cell, and the hardware design parameters.\n                  <\/jats:p>","DOI":"10.1177\/1094342004044010","type":"journal-article","created":{"date-parts":[[2004,5,27]],"date-time":"2004-05-27T08:40:00Z","timestamp":1085647200000},"page":"183-195","source":"Crossref","is-referenced-by-count":3,"title":["Performance Models on QCDOC for Molecular Dynamics with Coulomb Potentials"],"prefix":"10.1177","volume":"18","author":[{"given":"Y.","family":"Deng","sequence":"first","affiliation":[{"name":"DEPARTMENT OF APPLIED MATHEMATICS, STONY BROOK UNIVERSITY, STONY BROOK,                        NY 11794, USA AND CENTER FOR DATA INTENSIVE COMPUTING, BROOKHAVEN NATIONAL                        LABORATORY, UPTON, NY 11973, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J.","family":"Glimm","sequence":"additional","affiliation":[{"name":"DEPARTMENT OF APPLIED MATHEMATICS, STONY BROOK UNIVERSITY, STONY BROOK,                        NY 11794, USA AND CENTER FOR DATA INTENSIVE COMPUTING, BROOKHAVEN NATIONAL                        LABORATORY, UPTON, NY 11973, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J. W.","family":"Davenport","sequence":"additional","affiliation":[{"name":"CENTER FOR DATA INTENSIVE COMPUTING, BROOKHAVEN NATIONAL LABORATORY,                        UPTON, NY 11973, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"X.","family":"Cai","sequence":"additional","affiliation":[{"name":"UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA, HEFEI 230026, CHINA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"E.","family":"Santos","sequence":"additional","affiliation":[{"name":"DEPARTMENT OF COMPUTER SCIENCE, VIRGINIA TECH., BLACKSBURG, VA 24061, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2004,5,1]]},"reference":[{"key":"atypb1","unstructured":"Allen, M. P. and Tildesley, D. J. 1987. Computer Simulation of Liquids. 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