RaftLib

RaftLib
File:Rl.svg
Original author	Jonathan Beard
Initial release	late 2014
Stable release	0.9 / January 2020 (2020-01)
Preview release	1.0a / May 18, 2020 (2020-05-18)
Written in	C++
Operating system	Linux, macOS, Windows
Type	Data analytics, HPC, Signal Processing, Machine Learning, Algorithms, Big Data
License	Apache License 2.0
Website	www.raftlib.io

RaftLib 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. 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:

<syntaxhighlight lang=Cpp> import <raft>; import <raftio>;

import std;

using String = std::string;

using RaftKernel = raft::kernel; using RaftKernelStatus = raft::kstatus; using RaftMap = raft::map; using RaftPrint = raft::print;

class HelloWorld : public RaftKernel { public:

   HelloWorld() {
       output.addPort<String>("0"); 
   }

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

};

int main(int argc, char* argv[]) {

   // instantiate print kernel
   RaftPrint<String> p;

   // instantiate hello world kernel
   HelloWorld hello;

   // make a map object
   RaftMap m;

   // add kernels to map, both hello and p are executed concurrently
   m += hello >> p;

   // execute the map
   m.exe();

   return 0;

} </syntaxhighlight>

External links

• Official website
• RaftLib User Wiki
• RaftLib on GitHub
• CPPNow RaftLib Tutorial Session
• A Short Introduction to Stream Processing
• Parallel BZip2 Implementation Using RaftLib