5. Conclusions and perspectives

The use of low end Intel SMP computers inside Beowulf or c.o.w. can help in getting better performances when applications does not consume a lot of memory bandwidth: we have always to remember that a cluster of single processors nodes has twice aggregate memory bandwidth of an equivalent cluster of dual SMP with the same number of processors. In linear Algebra a lots of high level computation kernel use block methods and the blasth library could help in these cases as we see for LU factorization. The perspectives for this work are important because we need to work on more LAPACK routines to provide a useful library. There is also work to do on matrix matrix product and LU factorization to improve acceleration in small cases and our choice of simple parallelization for LU cannot be ideal for more processors. Porting to other platforms such as alpha systems is an ongoing work and theses systems can change scalability results for high bandwidth consuming BLAS such as ddot and dgemv making the blasth library more interesting.