Heterogeneous computing platform and acceleration method on basis of heterogeneous computing platform

Abstract

The invention discloses a heterogeneous computing platform. The platform comprises a host and a plurality of programmable devices, wherein the host is connected with each of the programmable devices; the host is used for initializing the programmable devices, carrying out parallel scheduling on each programmable device, sending computing data to each programmable device and obtaining a computing result; and each programmable device is used for processing the distributed computing data in parallel. The plurality of programmable devices of the heterogeneous computing platform can carry out computation at the same time, and the operation speed of the whole heterogeneous computing platform is equal to the sum of operation speeds of the programmable devices; compared with the heterogeneous computing platform with only one programmable device in the prior art, the whole operation speed and degree of parallelism of the heterogeneous computing platform are improved, so that the computing efficiency is improved, and the requirements, for the operation speed of the heterogeneous computing platform, of more and more complicated algorithms and data with larger and larger scales can be better satisfied. The invention furthermore provides an acceleration method on the basis of the heterogeneous computing platform.

Description

technical field [0001] The invention relates to the field of deep learning, in particular to a heterogeneous computing platform and an acceleration method based on the heterogeneous computing platform. Background technique [0002] With the advent of the era of big data, massive data and complex data processing require high hardware computing capabilities. Traditional CPU computing capabilities cannot support large-scale data calculations. Computing devices such as GPUs (Graphics Processing Units) and FPGAs (Field-Programmable Gate Arrays) have attracted the attention of researchers in related fields. . [0003] In the prior art, research institutions are mostly devoted to research on how to use CPU+FPGA heterogeneous computing platform for hardware acceleration and improve the running speed. However, the current research is mostly limited to the realization of single-machine single-card. Single-machine single-card refers to the configuration of an FPGA accelerator card fo...

AI Technical Summary

Problems solved by technology

With the development of complex algorithms such as deep learning, it is difficult for a single-machine single-card computing platform to meet its demand for computing speed

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