RaftLib
Original author(s) | Jonathan Beard |
---|---|
Initial release | late 2014 |
Stable release | 0.9
/ January 2020 |
Preview release | 1.0a
/ May 18, 2020 |
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 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:
#include<raft>
#include<raftio>
#include<cstdlib>
#include<string>
classhi:publicraft::kernel
{
public:
hi():raft::kernel()
{
output.addPort<std::string>("0");
}
virtualraft::kstatusrun()
{
output["0"].push(std::string("Hello World\n"));
return(raft::stop);
}
};
int
main(intargc,char**argv)
{
/** instantiate print kernel **/
raft::print<std::string>p;
/** instantiate hello world kernel **/
hihello;
/** make a map object **/
raft::mapm;
/** add kernels to map, both hello and p are executed concurrently **/
m+=hello>>p;
/** execute the map **/
m.exe();
return(EXIT_SUCCESS);
}