Design method for heterogeneous reconfigurable diagram calculation accelerator system on the basis of FPGA (Field Programmable Gate Array)

Abstract

The invention discloses a design method for a heterogeneous reconfigurable diagram calculation accelerator system on the basis of an FPGA (Field Programmable Gate Array). A whole accelerator system comprises a PC (Personal Computer) heterogeneous module and an FPGA heterogeneous module. The design method comprises the following specific steps that: firstly, loading a driving module required for starting the FPGA, and starting equipment, including the PCIe (Peripheral Component Interface Express) DMA (Direct Memory Access) and the like of the FPGA; according to the vertex number and the edge number of diagram data which needs to be processed, selecting a diagraph calculation accelerator engine; preprocessing the diagram data after the accelerator engine is selected; transmitting the processed diagram data to the onboard DDR (Double Data Rate) of an FPGA development board through the PCIe DMA; starting the accelerator to begin to read graph data from the appointed address of the onboardDDR; distributing the graph data to different processing units to be processed and calculated by the controller; after each processing unit calculates and processes the data, sending a result to a calculation result collection module; and writing the result back to the onboard DDR by the collection module, and reading the result from the onboard DDR by the PC after the whole diagram data finishesbeing processed. The method has the characteristics of being high in performance, energy efficiency, power consumption and the like.

Description

technical field [0001] The invention relates to the field of computer hardware acceleration, in particular to an FPGA-based graph computing accelerator system design method. Background technique [0002] In the real world, a graph can be used to represent the relationship between different entities. It is an abstraction of the relationship model between entities. A lot of information can be stored in the graph structure, so it has a wide range of applications in practice, such as: social network Analysis, web page map search, product recommendation system establishment, traffic network analysis, and biomedical information analysis, etc. In today's era of big data, the scale of graphs is becoming larger and larger. For example, the number of Facebook users reached 2.2 billion in July 2014, and the number of relationships between users reached hundreds or even hundreds of billions. If the relationship between these users Stored in the form of graph edges, the storage capacity...

AI Technical Summary

Problems solved by technology

In the design and implementation of graph computing systems at the software level, there are often some inefficient and unavoidable problems at the software level, such as low utilization of off-chip bandwidth and low effective computing rate.

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