Data flow compilation optimization method oriented to multi-core cluster

An optimization method and a technology of data flow, applied in the field of computer compilation, can solve the optimization problem of processing core storage allocation and communication optimization, the compilation optimization method does not optimize the architecture characteristics of the multi-core cluster system, and does not make full use of system hardware resources Program execution efficiency and other issues to achieve the effect of improving locality and cache utilization, reducing overhead, and low communication overhead

Active Publication Date: 2014-08-06
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

However, there are the following defects: (1) each calculation and communication scheduled to the processing core is separated, and an independent communication time is allocated for it in the pipeline, thus increasing the communication overhead; (2) the processing is not considered The underlying storage allocation optimization problem and communication optimization problem

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  • Data flow compilation optimization method oriented to multi-core cluster
  • Data flow compilation optimization method oriented to multi-core cluster
  • Data flow compilation optimization method oriented to multi-core cluster

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[0025] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0026] Such as figure 1 Shown is the structural frame diagram of this embodiment in the flow compilation system. After the data flow program is parsed by the front end of the data flow compiler, an intermediate representation - Synchronous Data Flow (SDF) will be generated, and then the task will be processed in sequence. Division and scheduling, hierarchical pipeline scheduling, cache optimiza...

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Abstract

The invention discloses a data flow compilation optimization method oriented to a multi-core cluster system. The data flow compilation optimization method comprises the following steps that task partitioning and scheduling of mapping from calculation tasks to processing cores are determined; according to task partitioning and scheduling results, hierarchical pipeline scheduling of pipeline scheduling tables among cluster nodes and among cluster node inner cores is constructed; according to structural characteristics of a multi-core processor, communication situations among the cluster nodes, and execution situations of a data flow program on the multi-core processor, cache optimization based on cache is conducted. According to the method, the data flow program and optimization techniques related to the structure of the system are combined, high-load equilibrium and high parallelism of synchronous and asynchronous mixed pipelining codes on a multi-core cluster are brought into full play, and according to cache and communication modes of the multi-core cluster, cache access and communication transmission of the program are optimized; furthermore, the execution performance of the program is improved, and execution time is shorter.

Description

technical field [0001] The invention belongs to the technical field of computer compilation, and more specifically, relates to a multi-core cluster-oriented data flow compilation optimization method. Background technique [0002] With the development of semiconductor technology, multi-core processors have been verified as a viable platform for exploiting parallelism. Multi-core cluster parallel system has become an important parallel computing platform design due to its powerful parallel computing capability and good scalability. The multi-core cluster system provides powerful computing and processing capabilities, but also puts more burdens on compilers and programmers to effectively develop coarse-grained parallelism between cores. Dataflow programming provides a viable approach to exploit the parallelism of multicore architectures. In this model, each node represents a computing task, and each edge represents the data flow between computing tasks. Each computing task i...

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Application Information

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IPC IPC(8): G06F9/45G06F9/50
Inventor 于俊清张维维唐九飞何云峰管涛
Owner HUAZHONG UNIV OF SCI & TECH
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