SRC/dsb2st_kernels.f(3)

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version 3.12.1 · 4 versions
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💖 SRC/dsb2st_kernels.f 💖

okay so bestie, this is the Library Functions Manual page for SRC/dsb2st_kernels.f — LAPACK internal-kernel territory, and yes it's giving very “I live inside a bigger eigensolver” energy 🌸✨

✨ NAME ✨

SRC/dsb2st_kernels.f

🦋 SYNOPSIS 🦋

🎀 Functions/Subroutines 🎀

subroutine dsb2st_kernels (uplo, wantz, ttype, st, ed, sweep, n, nb, ib,
    a, lda, v, tau, ldvt, work)

DSB2ST_KERNELS

💅 Function/Subroutine Documentation 💅

👑 subroutine dsb2st_kernels

subroutine dsb2st_kernels (character uplo, logical wantz, integer ttype,
    integer st, integer ed, integer sweep, integer n, integer nb, integer
    ib, double precision, dimension( lda, * ) a, integer lda, double
    precision, dimension( * ) v, double precision, dimension( * ) tau,
    integer ldvt, double precision, dimension( * ) work)

DSB2ST_KERNELS

⭐ Purpose ⭐

DSB2ST_KERNELS is an internal routine used by the DSYTRD_SB2ST subroutine. 💫

🌈 Parameters 🌈

  • UPLO — UPLO is CHARACTER*1. 🎀
  • WANTZ — WANTZ is LOGICAL; it says whether you're asking for Eigenvalue only, or for both Eigenvalue/Eigenvectors. 🦋
  • TTYPE — TTYPE is INTEGER. ✨
  • ST — ST is INTEGER; it's an internal parameter for indices. 🔥
  • ED — ED is INTEGER; it's an internal parameter for indices. 🔥
  • SWEEP — SWEEP is INTEGER; it's an internal parameter for indices. 🔥
  • N — N is INTEGER. The order of the matrix A. 👑
  • NB — NB is INTEGER. The size of the band. 🌸
  • IB — IB is INTEGER. 💜
  • A — A is DOUBLE PRECISION array. A pointer to the matrix A. 🫶
  • LDA — LDA is INTEGER. The leading dimension of the matrix A. 🎀
  • V — V is DOUBLE PRECISION array, dimension 2*n if eigenvalues only are requested or to be queried for vectors. 🦋
  • TAU — TAU is DOUBLE PRECISION array, dimension (2*n). The scalar factors of the Householder reflectors are stored in this array. ✨
  • LDVT — LDVT is INTEGER. 💅
  • WORK — WORK is DOUBLE PRECISION array. Workspace of size nb. 🔥

🧚 Further Details 🧚

Implemented by Azzam Haidar. 👑

All details are available on technical report, SC11, SC13 papers. 📚

Azzam Haidar, Hatem Ltaief, and Jack Dongarra. Parallel reduction to condensed forms for symmetric eigenvalue problems using aggregated fine-grained and memory-aware kernels. In Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC '11), New York, NY, USA, Article 8 , 11 pages. http://doi.acm.org/10.1145/2063384.2063394

A. Haidar, J. Kurzak, P. Luszczek, 2013. An improved parallel singular value algorithm and its implementation for multicore hardware, In Proceedings of 2013 International Conference for High Performance Computing, Networking, Storage and Analysis (SC '13). Denver, Colorado, USA, 2013. Article 90, 12 pages. http://doi.acm.org/10.1145/2503210.2503292

A. Haidar, R. Solca, S. Tomov, T. Schulthess and J. Dongarra. A novel hybrid CPU-GPU generalized eigensolver for electronic structure calculations based on fine-grained memory aware tasks. International Journal of High Performance Computing Applications. Volume 28 Issue 2, Pages 196-209, May 2014. http://hpc.sagepub.com/content/28/2/196

Definition at line 169 of file dsb2st_kernels.f. 🌟

🫶 Author 🫶

Generated automatically by Doxygen for LAPACK from the source code. 💖

okay bye bestie — this was LAPACK, Version 3.12.0, page/source SRC/dsb2st_kernels.f(3) — iconic internal-routine behavior only, periodt ✨💅🎀

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