%0 Conference Proceedings
%T On Retargeting the AI Programming Framework to New Hardwares
%+ CAS Institute of Computing Technology (ICT)
%+ University of Chinese Academy of Sciences [Beijing] (UCAS)
%A Zhao, Jiacheng
%A Chang, Yisong
%A Li, Denghui
%A Xia, Chunwei
%A Cui, Huimin
%A Zhang, Ke
%A Feng, Xiaobing
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 15th IFIP International Conference on Network and Parallel Computing (NPC)
%C Muroran, Japan
%Y Feng Zhang
%Y Jidong Zhai
%Y Marc Snir
%Y Hai Jin
%Y Hironori Kasahara
%Y Mateo Valero
%I Springer International Publishing
%3 Network and Parallel Computing
%V LNCS-11276
%P 39-51
%8 2018-11-29
%D 2018
%R 10.1007/978-3-030-05677-3_4
%K Retarget
%K AI programming framework
%K FPGA
%K Sunway
%Z Computer Science [cs]Conference papers
%X Nowadays, a large number of accelerators are proposed to increase the performance of AI applications, making it a big challenge to enhance existing AI programming frameworks to support these new accelerators. In this paper, we select TensorFlow to demonstrate how to port the AI programming framework to new hardwares, i.e., FPGA and Sunway TaihuLight here. FPGA and Sunway TaihuLight represent two distinct and significant hardware architectures for considering the retargeting process. We introduce our retargeting processes and experiences for these two platforms, from the source codes to the compilation processes. We compare the two retargeting approaches and demonstrate some preliminary experimental results.
%G English
%Z TC 10
%Z WG 10.3
%2 https://inria.hal.science/hal-02279561/document
%2 https://inria.hal.science/hal-02279561/file/477597_1_En_4_Chapter.pdf
%L hal-02279561
%U https://inria.hal.science/hal-02279561
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC10
%~ IFIP-NPC
%~ IFIP-WG10-3
%~ IFIP-LNCS-11276