A scalable thread scheduling co-processor based on data-flow principles

Large synchronization and communication overhead will become a major concern in future extreme-scale machines (e.g., HPC systems, supercomputers). These systems will push upwards performance limits by adopting chips equipped with one order of magnitude more cores than today. Alternative execution models can be explored in order to exploit the high parallelism offered by future massive many-core chips. This paper proposes the integration of standard cores with dedicated co-processing units that enable the system to support a fine-grain data-flow execution model developed within the TERAFLUX project. An instruction set architecture extension for supporting fine-grain thread scheduling and execution is proposed. This instruction set extension is supported by the co-processor that provides hardware units for accelerating thread scheduling and distribution among the available cores. Two fundamental aspects are at the base of the proposed system: the programmers can adopt their preferred programming model, and the compilation tools can produce a large set of threads mainly communicating in a producer-consumer fashion, hence enabling data-flow execution. Experimental results demonstrate the feasibility of the proposed approach and its capability of scaling with the increasing number of cores. We present a data-flow based co-processor supporting the execution of fine-grain threads.We propose a minimalistic core ISA extension for data-flow threads.We propose a two-level hierarchical scheduling co-processor that implements the ISA extension.We show the scalability of the proposed system through a set of experimental results.