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Volumn , Issue , 2004, Pages

Data flow algorithms in the tapenade tool for automatic differentiation

Author keywords

Adjoint algorithm; Adjoint code; Automatic differentiation; Data flow analysis; Dependence Graph

Indexed keywords

ADJOINT CODES; ADJOINTS; AUTOMATIC DIFFERENTIATIONS; DEPENDENCE GRAPHS; NUMERICAL PROGRAMS; PARALLELIZATIONS; PROGRAM TRANSFORMATIONS; STATIC-ANALYSIS ALGORITHM;

EID: 84893513026     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4)

References (10)
  • 6
    • 0003319841 scopus 로고    scopus 로고
    • Evaluating derivatives: Principles and techniques of algorithmic differentiation
    • A. Griewank. Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation. SIAM, Frontiers in Applied Mathematics, 2000.
    • (2000) SIAM, Frontiers in Applied Mathematics
    • Griewank, A.1
  • 10
    • 84886853228 scopus 로고    scopus 로고
    • Reducing the memory requirement in reverse mode automatic differentiation by solving TBR flow equations
    • LNCS. Springer
    • U. Naumann. Reducing the memory requirement in reverse mode automatic differentiation by solving TBR flow equations. In Proceedings of the IOCS 2000 Conference on Computational Science, Part II, LNCS. Springer, 2002.
    • (2002) Proceedings of the IOCS 2000 Conference on Computational Science, Part II
    • Naumann, U.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.