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This file documents the GNU Scientific Library (GSL), a collection of numerical routines for scientific computing. It corresponds to release 1.15 of the library. Please report any errors in this manual to bug-gsl@gnu.org . More information about GSL can be found at the project homepage, http://www.gnu.org/software/gsl/ . Printed copies of this manual can be purchased from Network Theory Ltd at http://www.network-theory.co.uk/gsl/manual/ . The money raised from sales of the manual helps support the development of GSL.

Scientific Library -- Reference Manual

http://www.gnu.org/software/gsl/manual/html_node/index.html#Top

http://www.inf.puc-rio.br/~roberto/struct/

This library offers basic facilities to convert Lua values to and from C structs. Its main functions are struct.pack , which packs multiple Lua values into a struct-like string; and struct.unpack , which unpacks multiple Lua values from a given struct-like string. The fist argument to both functions is a format string , which describes the layout of the structure. The format string is a sequence of conversion elements, which respect the current endianess and the current alignment requirements. Initially, the current endianess is the machine's native endianness and the current alignment requirement is 1 (meaning no alignment at all). http://www.inf.puc-rio.br/~roberto/struct/
http://incubator.apache.org/hama/

Welcome to Hama project

Apache Hama is a pure BSP(Bulk Synchronous Parallel) computing framework on top of HDFS (Hadoop Distributed File System) for massive scientific computations such as matrix, graph and network algorithms. Currently, it has the following features: Today, many practical data processing applications require a more flexible programming abstraction model that is compatible to run on highly scalable and massive data systems (e.g., HDFS, HBase, etc). A message passing paradigm beyond Map-Reduce framework would increase its flexibility in its communication capability. Bulk Synchronous Parallel (BSP) model fills the bill appropriately. Some of its significant advantages over MapReduce and MPI are: