FPGA-based machine learning with anti-aging mechanisms View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2009-2011

FUNDING AMOUNT

290000 CNY

ABSTRACT

As machine learning applications are widely used, the calculation speed of machine learning algorithms is becoming one of the main driving force. Meanwhile, with the reliability issues of the hardware platforms, such as the aging mechanisms and the impact of soft errors, the platform reliability of machine learning will become a hot issue. This project will study the FPGA-based "anti-aging" machine learning. Firstly, the parallelism will be explored and multi-level reliability and performance will be analyzed. Secondly, for a variety of machine learning algorithms, "anti-aging" FPGA functional unit and the connection library will be established. Based on the method of choosing modules from the library, an FPGA-based implementation and acceleration of reliable machine learning will be proposed. At the same time, the project will study the characteristics of run-time dynamic reconfiguration to further improve the life of machine learning. Finally, a general and efficient FPGA-based "anti-aging" machine learning framework will be explored. The research project will be able to effectively address the speed / reliability / design complexity issues of the machine learning applications and promote the development of machine learning research, to make it faster and better services for the national economy. More... »

URL

http://npd.nsfc.gov.cn/projectDetail.action?pid=60870001

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