Accelerating recurrent neural networks in analytics servers: Comparison of FPGA, CPU, GPU, and ASIC

FPL 2016 - 26th International Conference on Field-Programmable Logic and Applications

Volumn , Issue , 2016, Pages

  Nurvitadhi, Eriko ^a   Sim, Jaewoong ^a   Sheffield, David ^a   Mishra, Asit ^a   Krishnan, Srivatsan ^a   Marr, Debbie ^a  

^a INTEL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATION SPECIFIC INTEGRATED CIRCUITS; COMPUTATION THEORY; COMPUTER CIRCUITS; FIELD PROGRAMMABLE GATE ARRAYS (FPGA); RECONFIGURABLE HARDWARE;

DENSE MATRICES; FINE-GRAINED PARALLELISM; HIGHER FREQUENCIES; LANGUAGE MODEL; MULTI-CORE CPUS; RECONFIGURABLE FABRICS; RECURRENT NEURAL NETWORK (RNNS); STATE OF THE ART;

RECURRENT NEURAL NETWORKS;

EID: 84994813371     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FPL.2016.7577314     Document Type: Conference Paper

References (11)

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