Large matrices often have few known entries.
Excel, the world's most popular spreadsheet, can now handle ridiculously large matrices of numbers (one million rows, 16,000 columns).
If a precompiled LAPACK library is used, ensure ZGEEV is thread safe for large matrices.
Also manipulating such large matrices makes it necessary to to think about computer systems issues.
The emergence of large matrices in many applications has brought with it a slew of new algorithms and tools.
A further refinement, a two-dimensional matrix partitioning scheme, enhances performance for large matrices or machines with small caches.
Over the past few years, matrix analysis and numerical linear algebra on large matrices has become a thriving field.
Manipulating such large matrices makes it necessary to think about distributed systems issues such as communication cost.
(e) Compute closure matrices efficiently in a way that avoids inverting large matrices as described in Stolcke's paper (see base.ClosureMatrix).
However, on FPGAs these scalable solutions for large matrices are rarely found.
Aiming at the denoising of large matrices, nullspace based denoising (NBD) is introduced.
