Dynamic Control of Computation Consistency in the Parallel Dataflow Computing System

When developing high-performance multiprocessor computing systems, much attention is paid to ensuring uninterrupted operation, both in terms of hardware and software. In traditional computing systems, software is the main focus in address­ing these issues. The article discusses the solution to the issue of ensuring uninterrupted operation for the parallel dataflow computing system (PDCS), which implements the dataflow computational model with a dynamically formed context. Due to the features of the PDCS, it is proposed to implement this type of control in hardware, which will increase its efficiency, since the computational process will be controlled in dynamics, and not only in statics.

Introduction to Dataflow Computing

This chapter presents the possibilities for obtaining significant performance gains based on advanced implementations of algorithms using the dataflow hardware. A framework built on top of the dataflow architecture that provides tools for advanced implementations is also described. In particular, the authors point out to the following issues of interest for accelerating algorithms: (1) the dataflow paradigm appears as suitable for executing certain set of algorithms for high performance computing, namely algorithms that work with big data, as well as algorithms that include a lot of repetitions of the same set of instructions; (2) dataflow architecture could be configured using appropriate programming tools that can define hardware by generating VHDL files; (3) besides accelerating algorithms, dataflow architecture also reduces power consumption, which is an important security factor with edge computing.