ALGORITHMS FOR EFFICIENT VECTORIZATION OF REPEATED SPARSE POWER-SYSTEM NETWORK COMPUTATIONS

AYKANAT C., OZGU O., GÜVEN A. N.

IEEE TRANSACTIONS ON POWER SYSTEMS, cilt.10, sa.1, ss.448-456, 1995 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 10 Sayı: 1
  • Basım Tarihi: 1995
  • Doi Numarası: 10.1109/59.373970
  • Dergi Adı: IEEE TRANSACTIONS ON POWER SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.448-456
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Standard sparsity-based algorithms used in power system applications need to be restructured for efficient vectorization due to the extremely short vectors processed, Further, intrinsic architectural features of vector computers such as chaining and sectioning should also be exploited for utmost performance, This paper presents novel data storage schemes and vectorization algorithms that resolve the recurrence problem, exploit chaining and minimize the number of indirect element selections in the repeated solution of sparse linear system of equations widely encountered in various power system problems, The proposed schemes are also applied and experimented for the vectorization of power mismatch calculations arising in the solution phase of FDLF which involves typical repeated sparse power network computations. The relative performances of the proposed and existing vectorization schemes are evaluated, both theoretically and experimentally on IBM 3090/VF.