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Performance of LAPACK

Note: this chapter presents some performance figures for LAPACK routines. The figures are provided for illustration only, and should not be regarded as a definitive up-to-date statement of performance. They have been selected from performance figures obtained in 1999 during the development of version 3.0 of LAPACK. All reported timings were obtained using the optimized version of the BLAS available on each machine. Performance is affected by many factors that may change from time to time, such as details of hardware (cycle time, cache size), compiler, and BLAS. We attempted to obtain reliable timings by making multiple runs, but we do not guarantee the reproducibility of these numbers. To obtain up-to-date performance figures, use the timing programs provided with LAPACK.

- Factors that Affect Performance
  - Vectorization
  - Data Movement
  - Parallelism
- The BLAS as the Key to Portability
- Block Algorithms and their Derivation
- Examples of Block Algorithms in LAPACK
  - Factorizations for Solving Linear Equations
  - QR Factorization
  - Eigenvalue Problems
- LAPACK Benchmark