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        <datestamp>2025-01-19T23:58:49Z</datestamp>
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          <dc:title>パイプライン型アルゴリズムによる並列共役勾配法の安定性評価</dc:title>
          <dc:title xml:lang="en">Evaluations of Stability of Parallel Conjugave Gradient Methods based on Pipelined Algorithms</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>中島, 研吾</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>荻田, 武史</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Kengo, Nakajima</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Takeshi, Ogita</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:subject subjectScheme="Other">線形方程式の解法</jpcoar:subject>
          <datacite:description descriptionType="Other">パイプライン型アルゴリズムによる共役勾配法は，本来のアルゴリズムを保存しつつ，漸化式の適用によって計算順序を変更した手法であり，特に超並列環境では，MPI-3 のサポートする非同期集団通信関数によって，内積における集団通信と計算をオーバーラップさせることによって高いスケーラビリティを得られることが知られている．一方で，計算順序の変更により丸め誤差の伝播挙動が本来と異なるため，特に悪条件問題において収束が不安定となる場合がある．本研究では，悪条件問題におけるパイプライン型アルゴリズムによる共役勾配法の挙動を分析し，効率的で安定な計算手法について検討する．</datacite:description>
          <datacite:description descriptionType="Other">The Conjugate Gradient (CG) Method based on the pipelinede algorithm introduces recurrent relations to the standard CG algorithm. Although the sequence of operations of such CG is different from that of the standard CG, the algorithm has not changed. The CG based on the pipelined algorithms with functions for asynchronous collective communications supported in the MPI-3 standard can hide overhead of global collective communications by overlapping communications and computations. On the other hand, the change of sequence of computation affects the convergence, because rounding errors may be propagated differently. This effect is significant in ill-conditioned problems. In the present work, we analyze behaviors of the CG based on pipelined algorithms in ill-conditioned problems, and investigate robust and efficient method for computation.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2018-12-10</datacite:date>
          <dc:language>jpn</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_18gh">technical report</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/192851</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">2188-8841</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AN10463942</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告ハイパフォーマンスコンピューティング（HPC）</jpcoar:sourceTitle>
          <jpcoar:volume>2018-HPC-167</jpcoar:volume>
          <jpcoar:issue>26</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>9</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2020-12-10</datacite:date>
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