MathGL is a library for making high-quality scientific graphics under Linux and Windows, fast data plotting and handling of large data arrays, working in window and console modes, and easily embedding into other programs. It has more than 40 general types of graphics for 1d, 2d, and 3d data arrays. It can export graphics to raster and vector (EPS or SVG) formats. It has an OpenGL interface and can be used from console programs. It has functions for data handling and MGL language scripting for simplification of data plotting. It has several types of transparency and smoothed lightning, vector fonts and TeX-like formula drawing, an arbitrary curvilinear coordinate system, and many other useful things.
The ATLAS (Automatically Tuned Linear Algebra Software) project is an ongoing research effort focusing on applying empirical techniques in order to provide portable performance. It provides C and Fortran77 interfaces to a portably efficient BLAS implementation, as well as a few routines from LAPACK.
GetDP is a general finite element solver using mixed elements to discretize de Rham-type complexes in one, two, and three dimensions. The main feature of GetDP is the closeness between the input data defining discrete problems (written by the user in ASCII data files) and the symbolic mathematical expressions of these problems.
DISLIN is a high-level, easy-to-use plotting library for displaying data as curves, bar graphs, pie charts, 3D-colour plots, surfaces, contours, and maps. Several output formats are supported, such as X11, VGA, PostScript, PDF, CGM, HPGL, TIFF, and PNG. Plotting extensions for the interpreter-based languages Perl, Python, and Java are also supported for most operating systems.
Hoard is a scalable memory allocator (malloc replacement) for multithreaded applications. Hoard can dramatically improve your application's performance on multicore machines. No changes to your source are necessary; just link it in. Hoard scales linearly up to at least 64 processors. Supported platforms include Linux, Solaris, Mac OS X, and Windows.
librsb is a library for sparse matrix computations featuring the Recursive Sparse Blocks (RSB) matrix format. This format allows cache-efficient and multithreaded (that is, shared memory parallel) operations on large sparse matrices. The most common operations necessary to iterative solvers are available (matrix-vector multiplication, triangular solution, rows/columns scaling, diagonal extraction/setting, blocks extraction, norm computation, formats conversion). The RSB format is especially well-suited for symmetric and transposed multiplication variants. On these variants, librsb has been found to be faster than Intel MKL's implementation for CSR. Most numerical kernels code is auto-generated, and the supported numerical types can be chosen by the user at buildtime. librsb implements the Sparse BLAS standard, as specified in the BLAS Forum documents.