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.
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.
The National Space Science Data Center's (NSSDC) Common Data Format (CDF) is a self-describing data abstraction for the storage and manipulation of multidimensional data in a platform- and discipline-independent fashion. It consists of a scientific data management package (known as the "CDF Library") that allows programmers and application developers to manage and manipulate scalar, vector, and multi-dimensional data arrays.
CFITSIO is a library of C and Fortran subroutines for reading and writing data files in the FITS (Flexible Image Transport System) data format. It simplifies the task of writing software that deals with FITS files by providing an easy to use set of high-level routines that insulate the programmer from the internal complexities of the FITS file format.
TAU (Tuning and Analysis Utilities) is a set of tools for analyzing the performance of C, C++, Fortran and Java programs. It collects much more information than is available through prof or gprof, the standard Unix utilities, including per-process, per-thread, and per-host information, inclusive and exclusive function times, profiling groups that allow you to organize data collection, access to hardware counters on some systems, per-class and per-instance information, the ability to separate data for each template instantiation, start/stop timers for profiling arbitrary sections of code, and support for collection of statistics on user-defined events.
Cactus is a general, modular, parallel environment for solving systems of partial differential equations. The code has been developed over many years by a large international collaboration of numerical relativity and computational science research groups and can be used to provide a portable platform for solving any system of partial differential equations.