title: ublas vs. matrix template library (MTL4)
body: <p>I'm writing a software for hyperbolic partial differential equations in c++. Almost all notations are vector and matrix ones. On top of that, I need the linear algebra solver. And yes, the vector's and matrix's sizes can vary considerably (from say 1000 to sizes that can be solved only by distributed memory computing, eg. clusters or similar architecture). If I had lived in utopia, I'd had had linear solver which scales great for clusters, GPUs and multicores.</p>
  
  <p>When thinking about the data structure that should represent the variables, I came accros the boost.ublas and MTL4.
  Both libraries are blas level 3 compatible, MTL4 implements sparse solver and  is much faster than ublas. They both don't have implemented support for multicore processors, not to mention parallelization for distributed memory computations. On the other hand, the development of MTL4 depends on sole effort of 2 developers (at least as I understood), and I'm sure there is a reason that the ublas is in the boost library. Furthermore, intel's mkl library includes the example for binding their structure with ublas. 
  I'd like to bind my data and software to the data structure that will be rock solid, developed and maintained for long period of time. </p>
  
  <p>Finally, the question. What is your experience with the use of ublas and/or mtl4, and what would you recommend? </p>
  
  <p>thanx,
  mightydodol</p>