Slides:
https://github.com/boostcon/cppnow_presentations_2017/blob/master/05-18-2017_thursday/parallel_programming_with_raftlib_streaming_and_dataflow_concurrency_via_concise_cpp_iostream_like_operators__jonathan_beard__cppnow_05-18-2017.pdfVideo:
https://www.youtube.com/watch?v=IiQ787fJgmUAlmost every commodity compute device from cell phone to server has a heterogeneous multicore processor inside it. To use these complex cores, we must write code that can execute in parallel. Effective use of multicore hardware with today’s tools requires that a programmer know a lot about the hardware. This was feasible with a single core, and two cores, but how about a hundred? What happens with cores that are of different types? How about multiple memory types? How about effectively programming these systems with differing link types for each of these processor-memory combinations? This hardware complexity is not well accommodated by current software models. RaftLib aims to abstract away this complexity to make authoring performant parallel applications in C++ as simple as possible, while giving the experienced programmer the control they desire without the boiler-plate code that often comes with lower-level APIs. It utilizes the familiar semantics of stream operators to link multiple parallel actors into a parallel, streaming application. RaftLib is built as a C++ template library, enabling programmers to utilize the robust C++ standard library along with RaftLib’s parallelization framework. RaftLib enables a programmer to write C++ code that will execute in multiple processes, multiple threads, user space threads, on distributed nodes, and with optional extensions, on accelerators without learning dozens of complex interfaces. This session covers the pitfalls of programming parallel hardware, offers RaftLib as a solution, and we'll walk programmers through how to use it effectively.
