This Article 
 Bibliographic References 
 Add to: 
Why Computer Architecture Matters
May/June 2008 (vol. 10 no. 3)
pp. 59-63
Cosmin Pancratov, University of Richmond
Jacob M. Kurzer, University of Richmond
Kelly A. Shaw, University of Richmond
Matthew L. Trawick, University of Richmond
Over the course of a three-part series, the authors will walk through the implementation of a simple but computationally intensive algorithm and show how a series of incremental refinements to the code yields significant performance gains. In this first installment, they concentrate on instruction selection and scheduling.

1. J.L. Hennessy and D.A. Patterson, Computer Architecture: A Quantitative Approach, 3rd ed., Morgan Kaufmann, 2003.
2. P.M. Chaikin and T.C. Lubensky, Principles of Condensed Matter Physics, Cambridge Univ. Press, 1995.
3. J.P. Shen and M.H. Lipasti, Modern Processor Design: Fundamentals of Superscalar Processing, McGraw Hill Higher Education, 2005.

Index Terms:
orientational correlation function algorithms, computational science, computer architecture, education
Cosmin Pancratov, Jacob M. Kurzer, Kelly A. Shaw, Matthew L. Trawick, "Why Computer Architecture Matters," Computing in Science and Engineering, vol. 10, no. 3, pp. 59-63, May-June 2008, doi:10.1109/MCSE.2008.87
Usage of this product signifies your acceptance of the Terms of Use.