even allocate such a large amount of memory. Instead it defines a parameter, Kp, to give best use of the L2 cache. Panels are limited to Kp in length. It first tries to allocate (in the jik case) . If that fails it tries . (If that fails it uses the no-copy version of GEMM, but this case is unlikely for reasonable choices of cache edge.) Kp is a function of cache edge and NB. LAPACK When integrating the ATLAS BLAS with LAPACK an important consideration is the choice of blocking factor for LAPACK. If the ATLAS blocking factor is small enough the blocking factor of LAPACK could be set to match that of ATLAS. To take advantage of recursive factorization, ATLAS provides replacement routines for some LAPACK routines. These simply overwrite the corresponding LAPACK routines from Netlib. Need for installation Installing ATLAS on a particular platform is a challenging process which is typically done by a system vendor or a local expert and made available to a wider audience. For many systems, architectural default parameters are available; these are essentially saved searches plus the results of hand tuning. If the arch defaults work they will likely get 10-15% better performance than the install search. On such systems the installation process is greatly simplified. References External links User contribution to ATLAS A Collaborative guide to ATLAS Development The FAQ has links to the Quick reference guide to BLAS and Quick reference to ATLAS LAPACK API reference Microsoft Visual C++ Howto for ATLAS C (programming language) libraries Fortran libraries Numerical linear algebra Numerical software Software using the BSD license