SSB2ST_KERNELS(3)

💖 NAME 💖

okay so this is the Library Functions Manual page for SSB2ST_KERNELS(3), and the source file path is literally /home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/ssb2st_kernels.f — no cap, that’s the whole NAME situation bestie 🫶

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✨ SYNOPSIS ✨

🧚 Functions/Subroutines 🧚

       subroutine SSB2ST_KERNELS (uplo, wantz, ttype, st, ed, sweep, n, nb, ib,
           a, lda, v, tau, ldvt, work)
           SSB2ST_KERNELS

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🌈 Function/Subroutine Documentation 🌈

here’s the full signature, bestie — copying it exactly so nobody comes for me 💅

   subroutine SSB2ST_KERNELS (character uplo, logical wantz, integer ttype,
       integer st, integer ed, integer sweep, integer n, integer nb,
       integer ib, real, dimension( lda, * ) a, integer lda, real, dimension( * ) v,
       real, dimension( * ) tau, integer ldvt, real, dimension( * ) work)
       SSB2ST_KERNELS

🎯 Purpose 🎯

SSB2ST_KERNELS is an internal routine used by the SSYTRD_SB2ST subroutine. that’s the vibe ✨

💅 Parameters 💅

• UPLO — UPLO is CHARACTER*1.
• WANTZ — WANTZ is LOGICAL; it indicates whether eigenvalues are requested, or both eigenvalues/eigenvectors.
• TTYPE — TTYPE is INTEGER.
• ST — ST is INTEGER; internal parameter for indices.
• ED — ED is INTEGER; internal parameter for indices.
• SWEEP — SWEEP is INTEGER; 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 REAL array. A pointer to the matrix A.
• LDA — LDA is INTEGER. The leading dimension of the matrix A.
• V — V is REAL array, dimension 2*n if eigenvalues only are requested or to be queried for vectors.
• TAU — TAU is REAL array, dimension (2*n). The scalar factors of the Householder reflectors are stored in this array.
• LDVT — LDVT is INTEGER.
• WORK — WORK is REAL 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

📍 also the docs drop this exact line: Definition at line 170 of file ssb2st_kernels.f.

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👑 Author 👑

Generated automatically by Doxygen for LAPACK from the source code.

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okay bestie, that’s the whole page! 🫶 Cute sign-off from the footer: this is LAPACK, Version 3.12.0, with footer path /home/abui...t_kernels.f(3) — and no separate date was printed on this page, so that’s the date-ish info we’ve got 💖✨