RaftLib
Original author(s)Jonathan Beard
Initial releaselate 2014 (late 2014)
Stable release
0.9 / January 2020 (2020-01)
Preview release
1.0a / May 18, 2020 (2020-05-18)
Written inC++
Operating systemLinux, macOS, Windows
TypeData analytics, HPC, Signal Processing, Machine Learning, Algorithms, Big Data
LicenseApache License 2.0
Websitewww.raftlib.io

RaftLib[1] is a portable parallel processing system that aims to provide extreme performance while increasing programmer productivity. It enables a programmer to assemble a massively parallel program (both local and distributed) using simple iostream-like operators. RaftLib handles threading, memory allocation, memory placement, and auto-parallelization of compute kernels.[2] It enables applications to be constructed from chains of compute kernels forming a task and pipeline parallel compute graph. Programs are authored in C++ (although other language bindings are planned).

Example

Here is a Hello World example for demonstration purposes:[3]

#include <raft>
#include <raftio>
#include <cstdlib>
#include <string>

class hi : public raft::kernel
{
public:
    hi() : raft::kernel()
    {
       output.addPort< std::string >( "0" ); 
    }

    virtual raft::kstatus run()
    {
        output[ "0" ].push( std::string( "Hello World\n" ) );
        return( raft::stop ); 
    }
};

int
main( int argc, char **argv )
{
    /** instantiate print kernel **/
    raft::print< std::string > p;
    /** instantiate hello world kernel **/
    hi hello;
    /** make a map object **/
    raft::map m;
    /** add kernels to map, both hello and p are executed concurrently **/
    m += hello >> p;
    /** execute the map **/
    m.exe();
    return( EXIT_SUCCESS );
}

References

  1. ↑ "RaftLib: A C++ Template Library for High Performance Stream Parallel Processing" (PDF). Retrieved 2016-08-10.
  2. ↑ "Online Modeling and Tuning of Parallel Stream Processing Systems" (PDF). Retrieved 2016-08-10.
  3. ↑ "Hello World Example". Retrieved 2016-08-10.
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