As the era of computer architectures dominated by serial processors comes to a close, the convergence of several unprecedented changes in processor design has produced a broad consensus that much of the essential software infrastructure of computational science and engineering is utterly obsolete. Math libraries have historically been in the vanguard of software that must be quickly adapted to such design revolutions because they are the common, low-level software workhorses that do all the most basic mathematical calculations for many different types of applications. The Sustained Innovation for Linear Algebra Software (SILAS) project updates two of the most widely used numerical libraries in the history of Computational Science and Engineering---LAPACK and ScaLAPACK, (abbreviated Sca/LAPACK)---enhancing and hardening them for this ongoing revolution in processor architecture and system design. SILAS creates a layered package of software components, capable of running at every level of the platform deployment pyramid, from the desktop to the largest supercomputers in the world. It achieves three complementary objectives: 1) Wherever possible, SILAS delivers seamless access to the most up-to-date algorithms, numerical implementations, and performance, by way of Sca/LAPACK programming interfaces that are familiar to many computational scientists; 2) Wherever necessary, SILAS makes advanced algorithms, numerical implementations and performance capabilities available through new interface extensions; and 3) SILAS provides a well engineered conduit through which new discoveries at the frontiers of research in these areas can be channeled as quickly as possible to all the application communities that depend on high performance linear algebra. The improvements and innovations included in SILAS derive from a variety of sources. They represent the results (including designs and well tested prototypes) of the PIs' own algorithmic and software research agenda, which has targeted multicore, hybrid and extreme scale system architectures. They are an outcome of extensive and on-going interactions with users, vendors, and the management of large NSF and DOE supercomputing facilities. They flow from cross-disciplinary engagement with other areas of computer science and engineering, anticipating the demands and opportunities of new architectures and programming models. And finally, they come from the enthusiastic participation of the research community in developing and offering enhanced versions of existing Sca/LAPACK codes.
The primary impact of SILAS is a direct function of the importance of the Sca/LAPACK libraries to many branches of computational science. The Sca/LAPACK libraries are the community standard for dense linear algebra and have been adopted and/or supported by a large community of users, computing centers, and HPC vendors. Learning to use them is a basic part of the education of a computational scientist or engineer in many fields and at many academic institutions. Application domains where Sca/LAPACK have historically been heavily used include (among a host of other examples) airplane wing design, radar cross-section studies, flow around ships and other off-shore constructions, diffusion of solid bodies in a liquid, noise reduction, and diffusion of light through small particles. Moreover, the list of application partners working with SILAS to enhance and transform these libraries for next generation platforms expands this traditional list to include quantum chemistry, adaptive mesh refinement schemes, computational materials science, geophysical flows, stochastic simulation and database research for "big data". No other numerical library can claim this breadth of integration with the community. Thus, there is every reason to believe that enhancing these libraries with state of the art methods and algorithms and adapting them for new and emerging platforms (reaching up to extreme scale), will have a correspondingly large impact on the research and education community, government laboratories, and private industry.
